Choosing the optimal battery technology is pivotal to avoid future consequences. This comprehensive guide delves into the intricacies that distinguish NiMH and Lithium Ion batteries – their fundamental properties, performance across applications, etc. and equips readers for informed decision-making.

NiMH vs Lithium Ion Batteries: A Comprehensive Comparison for Engineers

Consider the following details when conducting power profiling:<ol start="1" type="1"><li>Hardware and sensor configurations: Analyze the components and sensors used in the device and their power consumption characteristics.&nbsp;Understand how different hardware configurations impact energy usage.</li><li>Firmware settings: Examine the firmware settings and configurations to identify any potential areas where power consumption can be optimized. Adjust settings and parameters to achieve more efficient power usage.</li><li>Communication parameters: Evaluate the communication parameters used by the device, such as transmission frequency and data rate. Analyze how different communication settings affect power consumption and battery life.</li><li>Use cases and corner cases: Consider the different use cases and scenarios in which the device will be deployed. Investigate how the device's behavior and power consumption vary under different conditions. Pay special attention to corner cases that may have unique power consumption patterns.</li></ol>Continuous benchmarking is crucial throughout the product development process. Utilize UART clever printouts and correlate them with power consumption to identify specific components or features that may be draining energy. This analysis will provide valuable insights on areas that can be optimized for improved power efficiency. Remember to turn off UART once the analysis is complete to avoid any impact on the final product.Additionally, consider network variables that can impact power consumption. Import network log files to understand how factors like distance to the gateway or Node B, weather conditions, and device density within the network influence power consumption. These variables can significantly affect how the battery is drained and should be taken into account when estimating battery life.By iteratively calculating battery life based on power consumption profiles throughout the development project, developers gain valuable knowledge and intuition about the factors that affect the power profile. This understanding allows them to maintain the desired power profile despite changes in the development stack, ensuring optimal power usage and battery life.<h2>Refined battery selection with battery profiling</h2>Understanding the power consumption behavior of an IoT device goes beyond relying solely on data sheet information. It involves conducting a critical analysis to assess the battery's performance in the unique scenario relevant to your project. This process provides insights into the battery's efficiency, stability, and suitability for the deployment.<h2 id="isPasted">Defining a Battery Profile</h2>A battery profile is not just a general overview; it is a tailored description of how a battery discharges under specific loads in particular environments. You can find such profiles in the battery's data sheets. To select the ideal battery for your solution, you need to <a href="https://www.qoitech.com/battery-toolbox/" target="_blank">create profiles</a> that align with your device's power requirements. Additionally, it is beneficial to profile several battery alternatives from different brands, batches, and temperatures to gain a thorough understanding of their behavior.<img border="0" width="605" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351007606-1713351007606.jpeg" alt="En bild som visar skärmbild, Multimedieprogram, programvara, GrafikprogramvaraAutomatiskt genererad beskrivning" class="fr-fic fr-dii">By following these steps, you can gain a deeper understanding of the power consumption behavior of your IoT device and make informed decisions when selecting the most appropriate battery for your project.<h2>Accelerated Battery Profile</h2>To create a battery discharge profile that aligns with your device's current consumption profile, you may need several months or even years. Thus, it is essential to develop an accelerated discharge profile. Here are some best practices to create an accurate and helpful profile:Maintain High Discharge Consistency: Coin cell batteries are particularly sensitive to high discharge, so it is crucial to match your device's peak current. Lithium-ion rechargeable batteries can withstand higher discharge currents, while alkaline batteries fall in between.Shorten Cycle Time: Determine the low discharge time the battery requires to recover.Increase Sleep Current: Ensure the battery can recover even in high discharge. Consult with Manufacturers: Seek assistance from battery manufacturers to verify your assumptions for the batteries you want to profile.<h2>Accuracy Considerations</h2>It's worth noting that precisely matching the discharged energy in the accelerated profile to the original profile may not be feasible, which could affect the profile's accuracy. The less acceleration used, the more accurate the results, but this method's level of accuracy is usually adequate for IoT implementations. It ensures a comprehensive real-world understanding of the battery's performance, contributing to successful IoT solutions.<h2>Profiling Different Battery Chemistries</h2>Here is an example from a customer case with LoRaWAN waste management IoT device. For this specific application, we profiled two distinct electro-chemistries encompassing six brands, including multiple samples from each brand. The profiling was carried out at room temperature, using an accelerated battery profile developed with input from battery manufacturers. Comparing samples from multiple manufacturers allowed us to evaluate how different form factors and chemical compositions influenced the results. Profiling the batteries in various environments could be the next logical step to observe the available capacity deviation from these controlled profiles, given that the profiling occurred at room temperature.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351055997-otii-arc-battery-profiling.png" style="width: 100%px;" class="fr-fic fr-dib">Battery profiling set-up with Otii Arc ProBattery Profile AnalysisLM17500: Three samples of this battery were profiled, yielding an average capacity of approximately 3050 mAh before reaching the cut-off point, slightly higher than the data sheet capacity of 3000 mAh.CR123A: Two batteries were profiled, with an average capacity of about 1600 mAh, consistent with the data sheet for that specific temperature.Interestingly, alkaline batteries exhibited significant variations in available capacity based on the manufacturer, which is a crucial consideration if customers will be responsible for battery replacement.AAA: These batteries had capacities ranging from 1080 to 1150 mAh, with an average of around 1100 mAh. The data sheet indicated a capacity of 1200 mAh.AA: The AA batteries showed a wider range of capacities, from 2420 to 2730 mAh, with an average of approximately 2590 mAh. For example, the data sheet for Varta indicated a capacity of 2950 mAh.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351084975-battery.png" style="width: 100%px;" class="fr-fic fr-dib">Batteries profiled in this studyOur profiling process identified performance nuances across different battery brands, chemistries, and form factors. These insights are crucial for making informed decisions specific to the device and use case, going beyond the data sheet capacities. Conducting profiling in diverse environmental conditions, particularly temperature, could further enhance our understanding and contribute to a more resilient IoT device design. You want to see more details from this study? Download the <a href="https://www.qoitech.com/whitepaper/powering-iot-devices/" target="_blank" id="isPasted">white paper</a>.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351110704-picture6.png" style="width: 100%px;" class="fr-fic fr-dib">Battery profiles graphed for lithium manganese batteries from Saft and GP.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351132266-picture7.png" style="width: 100%px;" class="fr-fic fr-dib">Battery profiles graphed for alkaline batteries (AA and AAA) from five different brands.<h2 id="isPasted">Replaying the Battery Profiles</h2>Accurately measured battery profiles provide a more realistic and tailored understanding of the battery's capacity for a specific application, surpassing the information provided in mere data sheets when estimating battery life. By directly applying the profiled battery discharge to the device instead of using a standard power supply, you can determine the actual usable capacity and further enhance the accuracy of the estimation. The actual usable capacity depends on the behavior of the device itself, and in some cases, we have encountered as low as 20% of the measured capacity. Tools such as <a href="https://www.qoitech.com/otii-ace/" target="_blank">Otii Ace Pro</a> with <a href="https://www.qoitech.com/battery-toolbox/" target="_blank">Battery Toolbox</a> can replicate these battery profiles, effectively serving as profiled batteries for the IoT device. By adjusting the used capacity in the battery emulator of these instrumentsand monitoring when the device either shuts down or reboots, you can uncover the true, realistic usable capacity. This ensures a more precise understanding of the battery's potential in the context of the specific application.<img border="0" width="605" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1713351148170-1713351148170.png" alt="Battery emulation with OtiiBattery Toolbox. MEasured and saved battery profile can be replayed to mimic the actual usable capacity and battery behaviour." class="fr-fic fr-dii">Battery emulation with Otii Battery Toolbox<h2>Conclusion</h2>We propose a technique for selecting the ideal battery: initial selection based on a defined use case and data sheet, power profiling of the IoT device and the battery for the use case, and a refined battery selection using device power behavior to assess the battery's real-world performance for the specific use case and device. This nuanced approach enables developers to make well-informed decisions that boost battery life.

Once the first prototype of your IoT device becomes available, it is essential to start power profiling and estimating battery life. This process involves gaining a comprehensive understanding of the device's configuration and power consumption characteristics within its specific deployment context.

How to pick the right battery for an IoT device: A waste management case study

New chemistries for batteries, semiconductors and more could be easier to manufacture, thanks to a new approach to making chemically complex materials that researchers at the University of Michigan and Samsung’s Advanced Materials Lab have demonstrated.&nbsp;Their new recipes use unconventional ingredients to make battery materials with fewer impurities, requiring fewer costly refinement steps and increasing their economic viability.“Over the past two decades, many battery materials with enhanced capacity, charging speed and stability have been designed computationally, but have not made it to market,” said <a href="https://mse.engin.umich.edu/people/whsun" target="_blank" rel="noreferrer noopener">Wenhao Sun</a>, the Dow Early Career Professor of Materials Science and Engineering at U-M and the corresponding author of the study published in Nature Synthesis.<iframe width="640" height="360" src="https://www.youtube.com/embed/9WxUQoFuEWs?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>“A lot of times, a simple material is a good starting point, but when you add a little bit of compound A and a little bit of compound B, magic happens and you get big improvements in capacity or charging rate. However, these chemically complex materials are often difficult to manufacture at scale with high purity.”Battery materials are typically made by mixing several different oxide powders and firing them in an oven. However, these powders react in a sequence rather than all at the same time. The first two ingredients to react are usually those that release the most energy upon reacting. The first reaction results in an intermediate compound that then reacts with the remaining powder, and so on, until no more reactions are possible.If the chemical bonds in the intermediate compounds are difficult to break, they might not fully react with the other ingredients. When they don’t fully react, the intermediates hang around as undesired impurities in the final material.“We designed a strategy to make impurity-free materials more reliably,” said <a href="https://mse.engin.umich.edu/people/jiadongc" target="_blank" rel="noreferrer noopener">Jiadong Chen</a>, the first author of the study and a U-M doctoral student in materials science and engineering and scientific computing. “The trick is to only work with two ingredients at a time, and deliberately make unstable intermediates that will react completely with the remaining ingredients.”To test this strategy, Sun’s team designed 224 different recipes to create 35 different known materials containing elements used in today’s batteries and next-generation ‘beyond-lithium’ batteries.&nbsp;The researchers then partnered with Samsung Semiconductor’s Advanced Materials Lab in Cambridge, Massachusetts, to test if their recipes produced these 35 materials with fewer impurities than conventional recipes. Samsung’s automated robotic lab can synthesize up to 24 different battery materials every 72 hours.Robotic arms handle the ingredients and operate the lab equipment that assesses the purity of the resulting materials. Meanwhile, computers automatically record the results of each experiment, creating a database that researchers can use to determine which recipes worked best.“With the automatic lab, we could broadly test our hypothesis on diverse battery chemistries,” Chen said.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712996666658-battery-materials-featured-1920x1081+%281%29.jpg" style="width: 100%px;" class="fr-fic fr-dib">ASTRAL, Samsung’s robotic lab, uses automated robotic arms to manipulate lab equipment, reagents and samples. As the lab makes battery materials according to a pre-programmed recipe, it automatically records data on the quality of the materials along the way. The records allow researchers to evaluate a large number of recipes in a reproducible manner. Photo credit: Advanced Materials Lab, Samsung Advanced Institute of Technology-America, Samsung Semiconductor.The experiments confirmed that the new recipes with ingredients designed to be unstable tended to produce cleaner products. The new recipes improved the materials’ purity by up to 80%, and six of the target materials could only be made with new recipes.Blueprints for the robotic lab were detailed in the team’s report, which Sun hopes will enable more chemistry labs to adopt robotic labs for both science and materials manufacturing.“We need more data—not just from successful recipes but also the unsuccessful ones—to improve materials manufacturing strategies. More robotic labs will help generate the needed data,” Sun said.These labs are within reach for most research institutions and could significantly speed up materials development, the researchers say.“The startup cost for the robotic equipment is about $120,000—not as high as you might think. But the payoffs in throughput, reliability and data-management are invaluable,” said study co-author Yan Eric Wang, principal engineer and project manager of Samsung’s Advanced Materials Lab.

Mixing unconventional ingredients in just the right order can make complex materials with fewer impurities. The robotic lab that tested the idea could be widely adopted.

Better battery manufacturing: Robotic lab vets new reaction design strategy

As electric vehicle (EV) battery manufacturing expands, so too does the demand for the materials that are essential to their production. Today’s EVs employ several battery technologies with different combinations of materials. Around the world, governments are developing policies to ensure that these materials are readily available and to mitigate supply chain disruption risks.In a <a href="https://www.nature.com/articles/s41467-024-46418-1.epdf?sharing_token=4_W4TX-XN5hf4pPgys28ENRgN0jAjWel9jnR3ZoTv0PnOf5EcsU7quxpqwJX9Xvx1Kknep4kdCq_oWx29xEFTtXCjwgDK1nPtYAm1mMCWM14HjSs6N-aU6tNprpaHHnVJjkVY3-GfWzbWhoDa3vv-COI28ukJIlSa6QTFEIpTSQ%3D" rel="noopener" target="_blank">recent publication in Nature Communications</a>, a team of researchers from the Department of Engineering and Public Policy at Carnegie Mellon University provides analysis of the relationship between electric vehicle battery chemistry and supply chain vulnerability for four critical minerals—lithium, cobalt, nickel, and manganese—across particular countries that are key contributors to production. The primary lithium ion battery chemistries used in EVs today are lithium iron phosphate (LFP), nickel manganese cobalt (NMC), and nickel cobalt aluminum (NCA), which each depend on varying amounts of these minerals. The authors, Anthony Cheng, <a href="https://engineering.cmu.edu/directory/bios/fuchs-erica.html" target="_blank">Erica Fuchs</a>, <a href="https://engineering.cmu.edu/directory/bios/karplus-valerie.html" target="_blank">Valerie Karplus</a>, and <a href="https://engineering.cmu.edu/directory/bios/michalek-jeremy.html" target="_blank">Jeremy Michalek</a>, find that effectively reducing vulnerabilities to disruption related to any particular country may require addressing multiple layers of upstream supply relationships.<blockquote>We need to anticipate new potential supply chain vulnerabilities so that we can act strategically to mitigate risk.<cite>Jeremy Michalek, Professor, Mechanical Engineering and Engineering and Public Policy</cite></blockquote>“In the 1970s, several global oil supply disruptions sent shock waves through the economy, with motorists waiting in long lines to fill up,” says Michalek, a professor of engineering and public policy and mechanical engineering and who also serves as director of <a href="https://www.cmu.edu/cit/veg/" rel="noopener" target="_blank">Carnegie Mellon’s Vehicle Electrification Group</a>. “As we shift away from gasoline toward electric vehicles, we need to anticipate new potential supply chain vulnerabilities so that we can act strategically to mitigate risk.”By mapping the supply chains of the four critical materials, calculating a vulnerability index, and using a network flow optimization to bound uncertainties, the study finds that production at multiple supply chain steps is highly concentrated in single countries. In particular, production at multiple stages of the supply chain across battery technologies occurs in China, primarily due to its role in materials refining and cathode production.“Our approach provides a new measure of energy security as we move beyond fossil fuels,” says Karplus, a professor of engineering and public policy and associate director of the <a href="https://www.cmu.edu/energy/" rel="noopener" target="_blank">Wilton E. Scott Institute for Energy Innovation</a>.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712184833930-0319-em-ev-supply-chain.png" style="width: 100%px;" class="fr-fic fr-dib">A Sankey diagram for global flows of lithium that available data suggest are involved in battery material supply chains.&nbsp;Source:&nbsp;Nature CommunicationsA supply chain disruption centered in one country could occur for any number of reasons, ranging from geopolitical strategy to political or economic instability, a natural disaster, or another pandemic. Last year, China restricted exports of graphite, another key material used in batteries. Countries that make EVs, like the U.S., have an interest in diversifying supply chains to reduce disruption risks such as this.Additionally, the research finds that the levels of vulnerability vary based on the lithium-ion battery chemistry. For example, the LFP chemistry may currently be more vulnerable to supply disruptions in China, but NMC chemistries depend on more critical materials, resulting in more pathways for disruptions from other countries to affect the supply chain, such as the Democratic Republic of Congo or South Africa.As efforts are made to diversify the supply chain and incentivize domestic production, the authors note that a comprehensive approach must be considered beyond battery cell and pack production, including minerals extraction, processing, and component production.“The U.S. Inflation Reduction Act provides major incentives to diversify the supply chain and build more batteries in the U.S.,” says Michalek. “We’re actively working to analyze how this policy may incentivize changes in different parts of the supply chain and in battery technology.”The findings in this research can be useful to policymakers as they seek to identify specific bottlenecks, key relationships, and potential levers for reduction of supply chain vulnerabilities.

A recent study analyzes the relationship between electric vehicle battery chemistry and supply chain vulnerability for four critical minerals—lithium, cobalt, nickel, and manganese—across particular countries that are key contributors to production.

Anticipating and reducing EV battery supply disruptions

Powerful, safe and environmentally friendly – sodium-ion batteries have many advantages over conventional batteries. Since they do not contain critical raw materials such as lithium or cobalt, they could also make applications such as stationary energy storage and electromobility much cheaper. However, there is currently a lack of the necessary energy storage materials for production. The start-up Litona, founded at the Karlsruhe Institute of Technology (KIT), wants to produce them on an industrial scale. From April 22nd to 26th, 2024, Litona will be presenting itself at the KIT stand at “Energy Solutions” (Hall 13, Stand C76) at the Hannover Messe.&nbsp;Prussian White, a “chemical relative” of the well-known dye Prussian Blue, is essentially based on sodium, iron and manganese. “As an energy storage material, it can be used on the cathode, i.e. the positive pole of a sodium-ion battery,” says Sebastian Büchele from the Institute for Applied Materials at KIT and founder of Litona. “Such batteries are cheap and all the raw materials they contain are widely available. I am convinced that we will soon be able to use them on a mass scale in electric vehicles and grid storage.” The question, however, is who produces them. The European industry is facing a major problem here. “It is currently difficult even for research institutions to obtain Prussian White in sufficient quantities. Hardly any company in Europe produces it,” reports the scientist. “Research and transfer of future-oriented sodium-ion technology will be extremely slowed down.”<h2 id="isPasted">Prussian White for mass production</h2>Since Büchele also wanted to research sodium ion technology, he decided to synthesize Prussian white himself. This work at KIT not only resulted in a high-quality cathode material, but also an innovative process for its production. With the aim of serving a larger market, he founded the start-up Litona together with the chemist Tom Bötticher. “Competitors had problems scaling the production of Prussian White analogues,” says Büchele. “We believe we have solved this. We have also developed methods to further enhance our material.”<h2>Opportunity for European industry</h2>To validate the scaling steps and optimize the material for use in next-generation batteries, Litona used KIT's infrastructure. In the meantime, the two founders are already working on setting up their own state-of-the-art production facility. “We consciously chose Germany as a location,” emphasizes co-founder Bötticher. “We believe in the potential of European battery production. When it comes to lithium-ion batteries, Asia has been ahead in recent years. Sodium-ion technology is now a huge opportunity for a new beginning in Europe. We don’t just want to watch.”<h2>Litona at the Hannover Messe 2024</h2>The start-up Litona will be presenting itself at this year's Hannover Messe from April 22nd to 26th at the KIT stand at “Energy Solutions” (Hall 13, Stand C76).<hr><h2>About Litona</h2>Litona was founded in August 2023 with the aim of supplying the European industry with sodium-ion energy storage materials. However, the young company does not want to rule out developing its own sodium-ion batteries in the future. The founders are currently in discussions with well-known investors from the deep tech scene.&nbsp;Further information:&nbsp;<a href="https://www.litona-batteries.de/" target="_blank">https://www.litona-batteries.de/</a>

Litona founder Sebastian Büchele shows a bottle of the energy storage material Preußisch Weiß for sodium-ion batteries. (Photo: Markus Breig, KIT)

Litona, a spin-off from KIT, produces the cathode material Prussian White for next-generation batteries

Battery material for the sodium-ion revolution

In this episode, we discuss a breakthrough from an EPFL researcher which promises to finally make hydrogen a feasible source of energy by extracting it efficiently from ammonia. 

Podcast: How Hydrogen Will Replace Batteries

Several technologies have suddenly come into the spotlight in measures against global warming. Typical examples of these technologies include solar and wind power generation, electric vehicles (EVs), power semiconductors, and fuel cells. Among these technologies, batteries have been viewed as important and widely used for some time. However, batteries are an electrical component whose importance has risen to another level in recent years (Fig. 1).<h2>Larger-Capacity, Higher-Voltage, and Longer-Life Batteries Are Sought for EVs and Energy Storage Systems (ESSs)</h2>Batteries, long used in toys, flashlights and other devices, are now an indispensable source of power for notebooks, smartphones, and other mobile devices. However, devices and equipment that were previously used by burning fossil fuels are now being electrified. Moreover, the use of renewable energy is being promoted. Against this backdrop, new usage scenarios for batteries are rapidly expanding. A strong desire has now emerged for batteries with greater performance, reliability, and safety than ever before.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1711015890630-bms-img0001.jpg" style="width: 100%px;" class="fr-fic fr-dib">Fig. 1: Batteries Are Becoming Increasingly Important as a Technology That Boosts the Achievement of Carbon NeutralityFor example, extremely advanced batteries are sought when electrifying the means of mobility that have conventionally used powerful engines as sources of power and heat such as EVs, electric ships, and airplanes. Those batteries need to meet all advanced requirements including a larger capacity to lengthen the continuous use time, higher input/output to enable rapid charging/discharging from small to large power, a longer cycle life with no deterioration over a long time even when repeatedly charged/discharged, and improved safety to allow use even under various temperatures, vibrations, shocks, and other environmental conditions.However, even with the batteries used in new scenarios like such EVs, the basic structure and materials used are not that different from conventional batteries used in smartphones. Lithium ion secondary batteries, the most user-friendly batteries from various perspectives including capacity, output, and life span, are being used without major improvements.The operating voltage of each lithium ion secondary battery cell (the smallest element of a battery) is approximately 4 V when fully charged and approximately 2 V when discharged. The operating voltage is also similar in batteries for smartphones. Moreover, the capacity realized by one cell is approximately 26 Ah for those installed in the latest EVs. The capacity of batteries for smartphones is approximately 3 Ah. Certainly, that means they are a little large. Nevertheless, we can still say they are small considering that they are used to power heavy machines like EVs.&nbsp;In fact, EV motors are driven at a high-voltage power of 400 V to 800 V. The capacity of the batteries that must be installed in EVs to obtain a practical traveling range is large at 50 kWh or more. Combining 1,000 or more cells and then arranging them in a series or parallel realizes the specifications of batteries for EVs. Batteries that have been given a higher voltage and larger capacity by combining a certain number of cells are called modules. Furthermore, a collection of multiple modules is referred to as a pack.It is necessary to resolve certain issues to adopt this method of combining small cells to make large batteries.In general, there are individual differences in the capacity, input/output, and other characteristics of each cell. Those differences arise from variations in materials and manufacturing. When cells are charged/discharged repeatedly, individual differences also arise in their strength against stress from the environment such as charging/discharging. Therefore, the individual differences of each cell tend to become larger. These individual differences have a major impact on the life span, output, and other characteristics of modules comprising many cells and the pack overall. That is because the characteristics of the module or pack will conform to the characteristics of the cell with the weakest performance and stress resistance among those used. Generally, there are fluctuations (referred to as "stress strength") in the temperature of the environment surrounding each cell and the voltage and current during charging/discharging. Therefore, the less resistant the cell, the higher the degree of deterioration. In particular, if the capacity is reduced, the power fails, or another problem arises due to over-charging (over-discharging), overheating, and internal short circuits, it may become impossible to control or drive the vehicle. That may even lead to an accident.<h2>What Is a Battery Management System – a Key System to Effectively Use Batteries?</h2>Against this background, it is necessary to set up an operating environment where it is possible to minimize the deterioration of each cell to maintain the performance of the modules comprising a combination of multiple cells and the packs and ensure the safe use of them over a longer period. A Battery Management System (BMS) is the control system that plays the role of closely monitoring and controlling the operation and status of each cell to achieve that purpose.The operation and status of each cell is constantly monitored with high precision and high resolution in a BMS. Sensors that detect the voltage, current, temperature, leakage, and other factors are used to monitor the operation and status of cells. The system controls the charging/discharging to compensate for slight inconsistences and imbalances in individual cells or modules. This maintains the balance so that the characteristics are as uniform as possible. As a result, the operating life span and performance of the modules and packs are maximized while ensuring their safety (Fig. 2).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1711015915237-bms-img0002_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 2: Cell Balancing - the Main Function of a BMSThe software control in the microcomputer then checks the collected data against the usage range determined from the battery specifications and design to perform operations like the following: (1) charging/discharging control to prevent over-charging and over-discharging, which impairs safety by causing cells to deteriorate, (2) charging/discharging control to prevent dangerous over-current, (3) management of the temperature to enable safe and smooth operation, (4) calculation of the state of charge (SOC), and (5) equalization of the cell voltage to maximize the traveling range and life span (referred to as "cell balancing"). Furthermore, if over-charging, overheating, or another abnormality is detected, the BMS sends alerts to the other in-vehicle systems and informs the control circuits that have the function to disconnect the output power to prevent accidents from occurring.There are two methods to the cell balancing function, which is an important function of a BMS. One is the passive method, in which a discharge switch is used to forcibly discharge cells with a high voltage and to convert the difference in capacity with cells with a low voltage into heat to equivalize the voltage. The other is the active method. In the active method, current is exchanged between adjacent cells with an unbalanced capacity and voltage to equalize the charging status of the cells. It is necessary to employ the active method to fully utilize the battery's potential without spare.The performance of a BMS is determined by the diversity and precision of its embedded control functions. However, an important condition to realize this is a high level of precision in the sensors that detect the operation and status of the cells and in the many electronic components used in BMS circuits (Fig. 3). In addition, a large number of cells must be monitored. Therefore, the BMS circuit configuration itself is becoming more complex. This means smaller and lighter sensors and components are being sought.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1711015936852-bms-img0003.jpg" style="width: 100%px;" class="fr-fic fr-dib">Fig. 3: Components Used in BMS Circuits (Source: Application guides "BMS (Battery management system)")<h2 id="isPasted">Wireless BMSs: Installed with Many Wireless Modules</h2>Conventional BMSs predict the operation and status of each cell by checking the data collected with the sensors against the rules and control range input in advance. Consideration is now being given to introducing technology that predicts the operation and status of each cell with even greater precision by allowing artificial intelligence (AI) to learn the trends in electrochemical phenomena in batteries. It is expected that utilization of this technology called "AI BMS" will enable the prediction of cell performance during rapid charging and the early detection of cell deterioration.&nbsp;In addition, attention has been focusing in recent years on the introduction of wireless BMSs (wBMSs). This is a wireless version of the control line that connects the modules and the BMS, making it possible to reduce the number of cables between the modules. This reduces the weight and makes it easier to wire to difficult-to-access locations. It seems it is possible to reduce the length of the cables by approximately 10 m per vehicle as well as the number of connectors, transformers, and other components associated with the wire connections when this technology is applied to a BMS for EVs. Furthermore, installing cells in that empty space will also make it possible to increase the battery capacity. Nevertheless, the risk of failure increases due to instability in the signal transmission line environment compared to a wired connection.A movement is already emerging to apply wBMSs to EVs and large energy storage systems (ESSs). It is essential to apply highly reliable and low-latency wireless technology to realize wBMSs. Semiconductor manufacturers that develop wireless ICs often propose the use of wireless technology with their own standards. Nevertheless, many of them use 2.4 GHz ISM band radio. It is likely that many small and highly reliable wireless modules will be used in EV and ESS batteries. The applications to which wBMSs can be applied will continue to expand in the future as wireless modules evolve.<hr id="isPasted"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1711016070057-1711016070057.png" class="fr-fic fr-dii">If you have any questions based on this article that you would like to discuss with an expert at Murata, don't hesitate to reach out. There's an entire team ready to support you with your question.<a href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" target="_blank" rel="nofollow" class="button-main-action">GET IN TOUCH</a>

Several technologies have suddenly come into the spotlight in measures against global warming. Typical examples of these technologies include solar and wind power generation, electric vehicles (EVs), power semiconductors, and fuel cells. 

Battery management systems improve safety and efficiency and to support battery utilization

Battery Type: Electrochemistry, Capacity, and Energy DensityConsider the application and device form factor when choosing the battery. Coin cell batteries are compact and suitable for low-power devices with minimal energy needs but have limited capacity and are non-rechargeable. Lithium-ion (Li-ion) or lithium-polymer (Li-poly) batteries offer higher capacity, rechargability, and longer lifespans, making them suitable for devices with higher power demands and longer lifecycles. Customized batteries may be necessary for devices with unconventional form factors.Capacity, measured in mAh or Wh, refers to the amount of charge a battery can store, while energy density relates to the amount of energy stored per unit volume or weight. Selecting a battery with sufficient capacity and energy density ensures extended device operation without frequent battery replacements.Voltage and Discharge CharacteristicsEnsure the battery voltage aligns with the device's voltage requirements over its entire lifespan. Understand the discharge rate influenced by the application's use, such as data transmission frequency, intensity, and duration. These factors impact battery characteristics, including discharge rate and voltage drop over time, ultimately affecting power consumption and runtime.TemperatureTemperature significantly affects battery performance. Extreme temperatures can impact capacity, discharge rate, and lifespan. Select a battery with an operating temperature range suitable for the device's environmental conditions.Battery and Device Shelf LifeConsider battery conditions, such as self-discharge, both before integration into the IoT device and once integrated. Aging and self-discharge affect performance, so understanding these parameters during product development and post-market deployment is crucial.Cost and LifespanEvaluate upfront cost and total cost of ownership over the battery's lifespan. Assess the battery's expected lifespan and balance it with the device's operational duration to optimize cost-effectiveness.By considering these factors, developers can choose the right battery for their IoT devices, ensuring optimal performance, longevity, and cost-effectiveness. Relying solely on data sheets is not sufficient. Further tests need to be done due to the device-specific conditions and batteries. This will be adressed in the following blogpost. If you can’t wait, download the&nbsp;<a href="https://www.qoitech.com/whitepaper/powering-iot-devices/" target="_blank">white paper</a>.

Choosing the appropriate battery for IoT devices is critical to ensure optimal performance and longevity. There are several factors to consider when selecting a battery that aligns with the specific requirements of the application, allowing for reliable and long-lasting power supply.

Choosing the Right IoT Battery

With the U.S. government’s goal to reduce emissions from transportation as part of a net-zero climate goal by 2050, efficient and reliable batteries are a necessity. A collaborative team of researchers led by the McKelvey School of Engineering at Washington University in St. Louis is working toward that goal by developing an energy storage system that would have a much higher energy density than existing systems.With $1.5 million from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E), Xianglin Li, associate professor of mechanical engineering &amp; materials science, will lead a multi-institutional team to develop a lithium-air (Li-air) battery with ionic liquids to deliver efficient, reliable and durable performance for high-energy and high-power applications. The Phase I, 18-month funding is part of $15 million ARPA-E awarded to 12 projects across 11 states to advance next-generation, high-energy storage solutions to speed electrifying the aviation, railroad and maritime transportation sectors.Funded through the Pioneering Railroad, Oceanic and Plane ELectrification with 1K energy storage systems (<a href="https://arpa-e.energy.gov/technologies/programs/propel-1k" target="_blank">PROPEL-1K</a>) program, projects aim to develop emission-free energy storage systems with “1K” technologies capable of achieving or exceeding 1,000-Watt-hour per kilogram (Wh/kg) and 1,000 Watt-hour per liter (Wh/L).“The current commercially available lithium-ion batteries have the specific energy of around 200 watt-hour per kilogram, and those would not work because 1,000 watt-hour per kilogram is beyond their thermodynamic limit,” Li said. “We need to increase that specific energy density by four to five times, so this is a very aggressive goal.”If successful, PROPEL-1K technologies would electrify regional flights traveling as far as 1,000 miles with up to 100 people, all North American railroads, and all vessels operating exclusively in U.S. territorial waters, the agency said.&nbsp;Li’s team’s concept would use pure lithium in the anode because it has the highest energy density. They will use a very thin separator with unique properties to transfer the lithium ion back and forth. The cathode must contain catalysts that make the electrochemical reaction of oxygen reduction and evolution reactions happen quickly and efficiently.“All of these components must be put together almost perfectly, because that 1,000 watt-hour per kilogram is near the limit of any energy storage technology,” Li said. “That's why we have a large team with complementary experts on different parts of this whole system. My team will lead the overall design of the system and focus on the cathode where the oxygen reaction would occur.”For the proposed Li-air flow battery, the team will use a unique electrolyte: ionic liquids with high oxygen solubility, low viscosity, ultra-low volatility and high ionic conductivity. The team will also customize catalysts and lithium metal protection membranes to enhance battery performance while reducing power consumption during electrolyte circulation. Preliminary experimental results have shown a tenfold increase in capacity by using a circulating electrolyte.“Commercial batteries use organic electrolytes, but because our Li-air cell is an open system, that electrolyte would evaporate over time,” Li said. “Ionic liquid is a salt that acts like a liquid but does not evaporate and can flow at room temperature.”Co-principal investigators on the project include Peng Bai, associate professor, and Vijay Ramani, the Roma B. &amp; Raymond H. Wittcoff Distinguished University Professor, both in the Department of Energy, Environmental &amp; Chemical Engineering in McKelvey Engineering; Mark Shiflett, Foundation Distinguished Professor at the University of Kansas; Ivan Vlassiouk, senior research staff at the Oak Ridge National Laboratory; James Saraidaridis, principal research engineer at Raytheon Technologies Research Center; and Sherry Quinn, electrochemist at Powerit. Together, they will work to develop a prototype that may be further developed and taken to market.The team also will conduct an economic analysis of its Li-air flow battery systems to the aviation, railroad and maritime transportation sectors to highlight the importance of advancing energy storage technologies beyond the current Li-ion battery technology.

With $1.5 million from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E), Xianglin Li, associate professor of mechanical engineering & materials science, will lead a multi-institutional team to develop a lithium-air (Li-Air) battery with ionic liquids to deliver efficient, reliable and durable performance for high-energy and high-power applications. (Credit: iStock photo)

With the U.S. government’s goal to reduce emissions from transportation as part of a net-zero climate goal by 2050, efficient and reliable batteries are a necessity.

Efficient lithium-air battery under development to speed electrification of vehicles

According to the Global EV Outlook from IEA, the EV stock reaches 145 million in 2030, accounting for 7% of the road vehicle fleet. However, one of the main challenges facing EVs is the battery, which determines the performance, range, safety, and cost of the vehicle. The battery enclosure is the protective structure that houses the battery cells and modules. The article explores different materials and design considerations for enclosures to optimize and supercharge EV performance. &nbsp;<h2 dir="ltr">Steel vs. Aluminium vs. Carbon Fiber</h2>Steel is a traditional material that offers high strength and durability. However, steel is heavy and prone to corrosion, which can reduce the energy efficiency and lifespan of the battery. In addition, steel has high thermal conductivity, which affects the battery performance and safety. Aluminum, in contrast, is preferred due to its lightweight and high strength-to-weight ratio. It is also more resistant to corrosion than steel.Sounds like aluminum wins in every way, no material is without its challenges, however. There is also the poor impact performance of metal materials. Carbon fiber reinforced polymer (CFRP), a newer and more innovative composite material, offers lightweight, anti-impact, durable and flexible performance. However, it is also more expansive. Moreover,<a href="https://www.sae.org/news/2021/01/novel-materials-approach-to-ev-battery-box-design" target="_blank">&nbsp;its thermal expansion mismatch with the battery cells</a>, which makes it still a cautious choice.<h2 dir="ltr">Design to Improve Cooling Efficiency</h2>Other than material selection, the factors such as structure optimization, thermal management system, etc., are also crucial. The modular design with multiple cooling channels and the use of cooling fins and heat sinks can enhance the cooling efficiency of the battery pack. Therefore, the surface area for heat transfer increased, allowing air or liquid to flow through the channels. If the heat, generated by battery cells during operation, is not dissipated properly, can reduce the lifespan of the battery, and even cause safety hazards.<h2 dir="ltr">Multi-layered Housing Structure</h2>Another important aspect of the battery pack housing design is the protection against mechanical and thermal shocks. A multi-layered housing structure consisting of an outer layer of aluminum or steel, a middle layer of insulation material, and an inner layer of polymer film can balance the pros and cons of different materials.This structure protects against physical damage to the battery cells from external impacts or vibrations, and protects against thermal runaway, which can occur when the battery overheats and triggers a chain reaction leading to a fire or explosion. The insulation layer prevents heat from spreading to adjacent cells and absorbs impact energy, while the polymer film acts as a barrier to prevent oxygen from entering the battery and fueling the combustion.<h2 dir="ltr">On-demand Manufacturing Accelerates Your Enclosure Development</h2>Before launching battery packs to the market, you need to conduct many prototyping verifications. RPWORLD is happy to support alongside your auto part development with 20-years’ experience and expertise. Choose RPWORLD, you will get:<ul><li dir="ltr">Fast delivery in as little as 7 days to help you ahead of competitions.</li><li dir="ltr">One-stop manufacturing including CNC machining, injection molding and more to bring your design to life under one roof.</li><li dir="ltr">Design optimization and manufacturability advice to mitigate production risks.</li><li>00+ high-performance engineering materials to suite your different needs.</li></ul>

According to the Global EV Outlook from IEA, the EV stock reaches 145 million in 2030, accounting for 7% of the road vehicle fleet. However, one of the main challenges facing EVs is the battery, which determines the performance, range, safety, and cost of the vehicle.

Supercharge EV's Performance with Optimized Battery Enclosures

<h2 id="isPasted">How Nanotechnology Is Inspiring the Next Generation of Batteries</h2>Rechargeable batteries are an important part of many modern-day technologies. Researchers, manufacturers and end-user companies are always looking to improve the efficiencies of batteries, making them safer, smaller, and more lightweight to fit in the requirements of new technologies—that is, the consumer desire to have higher-powered, smaller, and more lightweight electronic devices. Conventional fabrication methods, electrochemistries, and materials will take batteries technologies only so far, so a lot of interest in recent years has been around using nanomaterials within the electrodes.Nothing is wrong with current battery technologies—as showcased by the 2019 Nobel Prize in Chemistry, which honored the scientists behind the Li-ion battery—but change is inevitable. Without an ever-changing electronics industry, technological advances made in the past few decades would not have been possible.While lithium-ion (Li-ion) batteries are ubiquitous nowadays, their efficiencies aren’t overly impressive. They are much safer than other batteries while still having a good energy density, so there is room for improvement. Other types of batteries are gaining traction at both fundamental and commercial levels, but a drive to improve the already-established Li-ion batteries by incorporating nanomaterials into them has begun.<h2>Why Nanomaterials?</h2>The switch to trialing nanomaterials over bulkier materials is for many of the same reasons that other industries have made the switch (or have looked to make the switch). A number of properties can be harvested for a small amount of nanomaterials being included in a device (or within another material).Not all nanomaterials are suitable for batteries, as some nanomaterials are inherently insulating in nature. Rather, it is the conductive nanomaterials that are of use in battery systems, such as those of solid-state nature, or those which are incredibly thin (for example, some 2D materials). Luckily, the use of nanomaterials in electrodes is not a completely new invention. It is merely a natural progression to make systems more effective without altering the internal workings of the technology. While the inclusion of nanomaterials might slightly alter the specific mechanisms of how the ions move into the electrodes (because of different-sized/geometry atomic holes) via different architectures, the general operational mechanism of the batteries remains the same. This means that any safety or efficiency issues that arise can be pinpointed much easier than trying to develop a new type of battery from scratch. Sometimes, improving the status quo is better than trying to develop something completely novel.Many of the nanomaterials trialed have high electrical conductivity, and with this comes a high charge carrier mobility. These properties stem from nanomaterials having a very active surface–and a very high surface area–compared to bulkier materials. In some cases, the active surface is the whole nanomaterial (2D materials). Given that nanomaterials are inherently thin, they are a lot more flexible–even the inorganic materials–than bulk materials, meaning that they are more useful for the batteries used in flexible and wearable technologies (Figure 1).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1709117096314-Flexible+Graphene+Image.webp" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: The inherently thin nature of nanomaterials, as shown in this graphene sheet, means they are more flexible than bulk materials and thereby more suitable for batteries used in flexible and wearable technologies. (Source: BONNINSTUDIO/Shutterstock.com)Despite their small size, a lot of nanomaterials are very stable and are resistant to high temperatures, harsh chemicals, and high physical stresses. While this can’t be said for all nanomaterials, enough of them are stable and conductive enough for battery electrodes. One disadvantage of nanomaterials is their higher cost because of the more complex fabrication methods required to make them. However, because only a small amount is needed for the same (or better) properties than bulkier materials, the cost is a lot less than many people believe. The small addition of nanomaterials also means that less waste is often produced, and the batteries are more lightweight than when bulk materials are used.<h2>Graphene is the Front-Runner</h2>Of all the nanomaterials being trialed, graphene is the front-runner and is found in more prototypes than any other type of nanomaterial. A number of companies now commercially manufacture graphene batteries for different industrial sectors. Reportedly, some big cellphone manufacturers might use graphene batteries in some next-generation phones in the near future (graphene is already used in the cooling systems of some phones).Graphene exhibits some of the best recorded-values of almost all the properties that nanomaterials can exhibit, meaning that making compromises between the beneficial properties of different materials can often be negated by using graphene. Additionally, given that many batteries already use graphite—many graphene layers stacked on top of each other—it is a much more natural progression than other materials, and systems have been developed that use graphite-graphene electrodes.Graphene has one of the highest electrical conductivity and charge carrier mobilities known in the materials world. Moreover, it has an incredibly high tensile strength and flexibility (more than most nanomaterials and bulk materials), as well as being stable to high temperatures and harsh chemicals. The culmination of properties means that it can be used in a number of environments without its performance being affected, which is important when the batteries and the technologies they are in can get very hot internally, never mind the external heat they can be exposed to. Single-layer graphene is optically transparent, so it has the potential for being used to create transparent electrodes and transparent conductive films that could be used in batteries of the future that need to be invisible to the user.Aside from the properties being more suited to batteries than most other nanomaterials, the industry is in a much better place to cope with huge demands should it arrive. Because the properties and potential for graphene is well-understood, the industry has been preparing and growing in size around the world and graphene can now be produced at scale in a number of different forms. The raw material side is more scalable than other nanomaterials, making it a much more viable commercial option.<h2>Conclusion</h2>There is a drive in modern-day society for more efficient and smaller batteries, regardless of whether the application is consumer phones or remote monitoring equipment. Companies are starting to trial nanomaterials in battery systems because they bring about performance benefits and can make the batteries smaller, while not significantly increasing cost because only a small amount is required. A number of companies manufacture graphene batteries, but while graphene batteries are available for the industrial markets, it might take some time for the high-tech consumer markets (phones, tablets, etc.) to adopt graphene (or other nanomaterials) on a large-scale because the status quo is well-tested and any changes in these markets can take a long time to come to fruition.

Rechargeable batteries are an important part of many modern-day technologies. Researchers, manufacturers and end-user companies are always looking to improve the efficiencies of batteries, making them safer, smaller, and more lightweight to fit in the requirements of new technologies

Nanotechnology Is Inspiring Next-Gen Batteries

LPWAN networks aim to conserve energy by operating devices with minimal power consumption. However, battery utilization efficiency depends on factors such as device power consumption, network connectivity, transmission power, and data rate. Understanding and optimizing these factors are key to achieving desired battery performance and ensuring reliable and uninterrupted device functionality.Efficient battery management not only reduces the frequency of battery replacements but also enhances the sustainability of IoT deployments. This is especially important for applications that require long-term monitoring, such as environmental sensing, asset tracking, and smart agriculture. By extending battery life, organizations can reduce operational costs, minimize environmental impact, and improve the overall viability and scalability of their IoT solutions.<h3>Optimizing Battery Life of LPWAN IoT Devices</h3>Battery life is a critical consideration for the successful deployment of IoT devices with limited power resources. Understanding and managing factors that influence battery life are essential for optimizing power consumption and maximizing operational efficiency.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NTA0NDAxMjM1LW90aWktYmF0dGVyeS1wZXJmb3JtYW5jZS0xMDI0eDc2OC5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib"><h3 id="isPasted">Device Power Consumption&nbsp;<iframe id="645c016f1f67f100087c4425" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/otii-arc-pro?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe></h3>IoT device power consumption significantly affects battery life. Factors such as hardware architecture, sensor configurations, and firmware optimization play a crucial role. Leakage current from various components can cause energy loss. Firmware and software optimization are vital for enhancing battery efficiency. By employing efficient algorithms, minimizing unnecessary background tasks, and optimizing code execution, developers can reduce power consumption in the device's software stack.Implementing power management techniques can have a significant impact on battery life. These techniques may involve dynamically adjusting power levels based on network conditions, reducing power to peripheral components during idle periods, or optimizing data processing and filtering algorithms to minimize power consumption.<h3>Data Rate and Duty Cycle</h3>Data rate and duty cycle determine the frequency and duration of data transmission in LPWAN devices. Lower data rates and duty cycles reduce power consumption but result in longer transmission times. Striking the right balance between data rate, duty cycle, and application requirements is crucial for optimizing battery life while ensuring sufficient data throughput.<h3>Network Connectivity and Protocols</h3>The frequency of network connectivity and the size of message payloads transmitted by LPWAN IoT devices affect power consumption. Low power capabilities of the network, such as power save modes, spreading factor, and adaptive data rate mechanics of cellular and non-cellular LPWAN networks, can further enhance battery life. The choice of messaging protocol can have a negative impact on device longevity due to the level of transmission overhead and required quality of service (QoS). By finding the right balance between power efficiency and communication requirements, developers can maximize battery performance and extend the operational lifespan of their IoT devices.<h3>Sleep Mode and Wake-Up Interval</h3>Effectively utilizing sleep mode is a key strategy for conserving power in IoT devices. By defining appropriate wake-up intervals and adjusting sleep durations based on application requirements, developers can minimize power consumption during idle periods, leading to significant battery savings.<h3>Transmission Power and Range</h3>The transmission power level required for reliable communication affects battery life. Higher transmission power increases range but consumes more power. By optimizing transmission power settings based on the deployment environment and required range, battery life can be prolonged without compromising communication reliability.By considering and fine-tuning these factors, developers can make informed decisions to optimize power consumption and extend the battery life of IoT devices. In the following blogposts, we will delve deeper into strategies and techniques to choose the right battery and implement optimization measures for maximizing battery performance in LPWAN IoT deployments. If you can’t wait, download the <a href="https://www.qoitech.com/whitepaper/powering-iot-devices/" target="_blank">white paper</a>.

Battery performance is crucial for the successful operation of IoT devices, particularly in remote or inaccessible locations. They rely on battery power to sustain their operation over extended periods, and maximizing battery life directly impacts longevity, maintenance costs, and user experience.

Importance of IoT Battery Performance

Sensors that monitor infrastructure, such as bridges or buildings, or are used in medical devices, such as prostheses for the deaf, require a constant supply of power. The energy for this usually comes from batteries, which are replaced as soon as they are empty. This creates a huge waste problem. An EU study forecasts that in 2025, 78 million batteries will end up in the rubbish every day.A new type of mechanical sensor, developed by researchers led by Marc Serra-Garcia and ETH geophysics professor Johan Robertsson, could now provide a remedy. Its creators have already applied for a patent for their invention and have now presented the principle in the journal Advanced Functional Materials.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1706923590408-image0.imageformat.lightbox.847766885.jpg" style="width: 300px;" class="fr-fic fr-dib">Newer models of the sensor are highly miniaturised and fit on a fingertip. (all images: courtesy of Marc Serra-Garcia / Amolf)<h2>Certain sound waves cause the sensor to vibrate</h2>“The sensor works purely mechanically and doesn’t require an external energy source. It simply utilises the vibrational energy contained in sound waves,” Robertsson says.Whenever a certain word is spoken or a particular tone or noise is generated, the sound waves emitted – and only these – cause the sensor to vibrate. This energy is then sufficient to generate a tiny electrical pulse that switches on an electronic device that has been switched off.The prototype that the researchers developed in Robertsson’s lab at the Switzerland Innovation Park Zurich in Dübendorf has already been patented. It can distinguish between the spoken words “three” and “four”. Because the word “four” has more sound energy that resonates with the sensor compared to the word “three”, it causes the sensor to vibrate, whereas “three” does not. That means the word “four” could switch on a device or trigger further processes. Nothing would happen with “three”.Newer variants of the sensor should be able to distinguish between up to twelve different words, such as standard machine commands like “on”, “off”, “up” and “down”. Compared to the palm-sized prototype, the new versions are also much smaller – about the size of a thumbnail – and the researchers are aiming to miniaturise them further.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1706923608776-image1.imageformat.lightbox.523155445.jpg" style="width: 300px;" class="fr-fic fr-dib">High miniaturisation: 100 sound-sensitive elements fit into just 1x1 mm.<h2>Metamaterial without problematic substances</h2>The sensor is what is known as a metamaterial: it’s not the material used that gives the sensor its special properties, but rather the structure. “Our sensor consists purely of silicone and contains neither toxic heavy metals nor any rare earths, as conventional electronic sensors do,” Serra-Garcia says.The sensor comprises dozens of identical or similarly structured plates that are connected to each other via tiny bars. These connecting bars act like springs. The researchers used computer modelling and algorithms to develop the special design of these microstructured plates and work out how to attach them to each other. It is the springs that determine whether or not a particular sound source sets the sensor in motion.<h2>Monitoring infrastructure</h2>Potential use cases for these battery-free sensors include earthquake or building monitoring. They could, for example, register when a building develops a crack that has the right sound or wave energy.There is also interest in battery-free sensors for monitoring decommissioned oil wells. Gas can escape from leaks in boreholes, producing a characteristic hissing sound. Such a mechanical sensor could detect this hissing and trigger an alarm without constantly consuming electricity – making it far cheaper and requiring much less maintenance.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1706923630751-image2.imageformat.lightbox.1424652832.jpg" style="width: 300px;" class="fr-fic fr-dib">Vergrösserter Ausschnitt des schallempfindlichen Sensors neuerer Bauart: Die einzelnen Elemente sind nur wenige Mikrometer gross.<h2>Sensor for medical implants</h2>Serra-Garcia also sees applications in medical devices, such as cochlear implants. These prostheses for the deaf require a permanent power supply for signal processing from batteries. Their power supply is located behind the ear, where there is no room for large battery packs. That means the wearers of such devices must replace the batteries every twelve hours. The novel sensors could also be used for the continuous measurement of eye pressure. “There isn’t enough space in the eye for a sensor with a battery,” he says.“There’s a great deal of interest in zero-energy sensors in industry, too,” Serra-Garcia adds. He no longer works at ETH but at AMOLF, a public research institute in the Netherlands, where he and his team are refining the mechanical sensors. Their aim is to launch a solid prototype by 2027. “If we haven’t managed to attract anyone’s interest by then, we might found our own start-up.”<hr><h2 id="isPasted">Reference</h2>Dubček T, Moreno-Garcia D, Haag T, et al. In-Sensor Passive Speech Classification with Phononic Metamaterials. Adv. Funct. Mater. 2024, 2311877. DOI: <a href="https://doi.org/10.1002/adfm.202311877" target="_blank">external page10.1002/adfm.202311877</a>

prototype of the sound sensor is relatively large. (Photograph: Astrid Robertsson / ETH Zurich)

Researchers at ETH Zurich have developed a sensor that utilises energy from sound waves to control electronic devices. This could one day save millions of batteries.

Sound-powered sensors stand to save millions of batteries

Princeton researchers have created an artificial intelligence (AI) tool to predict the behavior of crystalline materials, a key step in advancing technologies like batteries and semiconductors. Although computer simulations are commonly used in crystal design, the new method relies on a large language model, similar to those that power text generators like ChatGPT.By synthesizing information from text descriptions that include details such as the length and angles of bonds between atoms and measurements of electronic and optical properties, the new method can predict properties of new materials more accurately and thoroughly than existing simulations — and potentially speed up the process of designing and testing new technologies.The researchers developed a text benchmark consisting of the descriptions of more than 140,000 crystals from the&nbsp;<a href="https://next-gen.materialsproject.org/" target="_blank">Materials Project</a>, and then used it to train an adapted version of a large language model called T5, originally created by Google Research. They tested the tool’s ability to predict the properties of previously studied crystal structures, from ordinary table salt to silicon semiconductors. Now that they’ve demonstrated its predictive power, they are working to apply the tool to the design of new crystal materials.The&nbsp;<a href="https://arxiv.org/abs/2310.14029" target="_blank">method</a>, presented Nov. 29 at the Materials Research Society’s Fall Meeting in Boston, represents a new benchmark that could help accelerate materials discovery for a wide range of applications, according to senior study author&nbsp;<a href="https://engineering.princeton.edu/faculty/adji-bousso-dieng" target="_blank">Adji Bousso Dieng</a>, an assistant professor of&nbsp;<a href="https://www.cs.princeton.edu/" target="_blank">computer science</a> at Princeton.Existing AI-based tools for crystal property prediction rely on methods called graph neural networks, but these have limited computational power and can’t adequately capture the nuances of the geometry and lengths of bonds between atoms in a crystal, and the electronic and optical properties that result from these structures. Dieng’s team is the first to tackle the problem using large language models, she said.“We have made tremendous advances in computer vision and natural language,” said Dieng, “but we are not very advanced yet when it comes to dealing with graphs [in AI]. So, I wanted to move from the graph to actually translating it to a domain where we have great tools already. If we have text, then we can leverage all these powerful [large language models] on that text.”The language model-based approach “gives us a whole new way to look at the problem” of designing materials, said study coauthor&nbsp;<a href="https://engineering.princeton.edu/faculty/craig-arnold" target="_blank">Craig Arnold</a>, Princeton’s Susan Dod Brown Professor of&nbsp;<a href="https://mae.princeton.edu/" target="_blank">Mechanical and Aerospace Engineering</a> and vice dean for innovation. “It’s really about, how do I access all of this knowledge that humanity has developed, and how do I process that knowledge to move forward? It’s characteristically different than our current approaches, and I think that’s what gives it a lot of power.”For insights into the challenges of crystal design, Dieng and Ph.D. student&nbsp;<a href="https://scholar.google.com/citations?user=5qnTWQEAAAAJ&hl=en" target="_blank">Andre Niyongabo Rubungo</a> teamed up with Arnold and with&nbsp;<a href="https://engineering.princeton.edu/faculty/barry-rand" target="_blank">Barry Rand</a>, a professor of&nbsp;<a href="https://ece.princeton.edu/people/barry-p-rand" target="_blank">electrical and computer engineering</a> and the&nbsp;<a href="https://acee.princeton.edu/" target="_blank">Andlinger Center for Energy and the Environment</a> who focuses on materials for semiconductors and solar energy. Arnold is interested in laser-material interactions, with applications for energy storage.“The materials in our world are all ones that were developed through scientific hypothesis testing and sometimes luck,” said Rand. This process “leads to good outcomes, but it takes time. Through artificial intelligence methods, we could really accelerate that.” Furthermore, he said, “it allows us to identify things that probably we as humans wouldn’t intuit.”Given a crystal with a particular composition of chemical elements, the team’s method can predict properties including the band gap, which relates to the crystal’s electronic states and conductivity.“If you can predict that with high accuracy, when you then go to do the painstaking work of experimentation, you can have more confidence that it’s going to yield success,” said Rand.Ph.D. student Rubungo received a&nbsp;<a href="https://www.mrs.org/meetings-events/fall-meetings-exhibits/2023-mrs-fall-meeting/meeting-events/other/poster-sessions" target="_blank">best poster award</a> for presenting the work to materials researchers at the fall meeting. Many were surprised by the power of large language models in this context. The field is more accustomed to structured data used as inputs for graph neural networks, but “texts are easier to deal with,” said Rubungo. “It’s easier to include the information you want in your description, and to modify the tool and remove what you don’t want. People were very excited to see that.”As a new tool, he noted, the prediction method has limitations. It uses more computing power and is slower than graph neural networks typically used for this purpose. It could also benefit from expanded training data to boost its ability to predict properties of novel materials.Dieng is pursuing collaborations with other materials researchers, and aims to move the work beyond crystals to a broader variety of materials. “This is a nascent area of research, and what advances research is to have a well-established benchmark that’s well curated,” she said. “We are gathering more data sets into one benchmark that will be hosted at Princeton for researchers to use.”<hr>The paper, “<a href="https://arxiv.org/abs/2310.14029" target="_blank">LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions</a>,” was presented Nov. 29 at the Materials Research Society’s Fall Meeting. Support for the research was provided by the Schmidt DataX Fund at Princeton University, the Schmidt Futures AI2050 Early Career Fellowship, and the U.S. National Science Foundation.

A scanning electron microscope image of tin crystals, stimulated by electricity and growing on a copper surface. A new method developed by Princeton researchers could speed up the process of designing and testing new crystalline materials. Image by Lynn Trahey, Argonne National Laboratory

Princeton researchers have created an artificial intelligence (AI) tool to predict the behavior of crystalline materials, a key step in advancing technologies like batteries and semiconductors. 

Researchers harness large language models to accelerate materials discovery

<section id="isPasted">Polymer-air batteries often face challenges related to stability, kinetics and conductivity. In response, Dr. Jodie Lutkenhaus has developed a method to use a polymer as an anode in these batteries.In a recent article published by<a href="https://www.cell.com/joule/pdf/S2542-4351(23)00355-0.pdf" rel="noopener" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">&nbsp;Joule</a>, Lutkenhaus, associate department head of internal engagement and chemical engineering professor at Texas A&amp;M University,&nbsp;&nbsp;collaborated with chemical engineering professor Dr. Abdoulaye Djire to reveal how these polymers store and exchange charge with the electrolyte.“The cathode reacts with oxygen from air to complete the circuit. We specifically targeted the use of a conjugated polymer with a rigid backbone structure for the anode,” Lutkenhaus said.These features make the polymer both conductive and stable, enabling the necessary reversible reactions required for repeated charging and discharging, she said.Despite the benefits of aqueous polymer-air batteries, including improved safety, reduced cost, higher ionic conductivity and sustainability, their electrochemical performance is limited, the article stated.</section><blockquote>By using a polymer as an electrode, we could change the electrolyte to prevent the formation of carbonates.<cite>Dr. Jodie Lutkenhaus</cite></blockquote><section>“To overcome these limitations, researchers have explored alternative polymer anodes, which have several advantages over metal anodes, including low cost, ease of functionalization and high stability,” according to the article.The battery’s rigid ladder structure, fast kinetics and high electrical conductivity allowed it to undergo 500 cycles with minimal performance loss. Additionally, the article revealed the real-time charge transfer mechanism, demonstrating a fast hydronium ion charge compensation process.The article notes that metal-air batteries have a higher energy density compared to conventional lithium-ion batteries. This is attributed to the oxygen cathode, which offers a much higher capacity than conventional metal oxide cathodes. However, the article highlights limitations in using metal anodes in air batteries due to the stability, cost, and environmental impact of extracting and processing metal resources.Issues like dendrites, passivation and corrosion on the metal anode lead to low utilization and inferior cycling stability in metal-air batteries. Despite the adoption of interfacial modification and electrolyte formulation, these issues can be severe in the presence of oxygen from the air.“The polymer-air battery provides an alternative means of storing energy versus the metal-air battery,” Lutkenhaus said. “The polymer-air battery has a high capacity for energy storage and a very long cycle life.”She explained that having a long cycle life means that people can use their batteries longer before having to recharge them or replace them.&nbsp;&nbsp;“Air-based batteries are promising for high-energy batteries because they have a lower mass than conventional batteries,” Lutkenhaus said. “However, long-term operation of air-based batteries often results in the generation of carbonate deposits that clog the battery and prevent long-term operation. By using a polymer as an electrode, we could change the electrolyte to prevent the formation of carbonates.”</section>

Polymer-air batteries often face challenges related to stability, kinetics and conductivity. In response, Dr. Jodie Lutkenhaus has developed a method to use a polymer as an anode in these batteries.