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Machine learning makes smarter batteries

Renewable energies, such as wind and solar energy are naturally intermittent. To balance their demand and supply, batteries of, for example, electric vehicles can be charged and act as an energy buffer for the power grid. Cars spend most of their time idle and could, at the same time, feed their electricity back into the grid. While this is still a dream of the future, commercialization of electric and hybrid vehicles is already creating a growing demand for long-lasting batteries, both for driving as well as grid buffering. Consequently, methods for evaluating the state of the battery will become increasingly important.

The long duration of battery health tests is a problem, hindering the rapid development of new batteries. Better battery life forcasting methods are therefore urgently needed but are extremely difficult to develop. Now, Severson and her colleagues report in the journal Nature Energy that machine learning can help to predict computer battery life by creating computer models. The published algorithms use data from early-stage charge and discharge cycles.

Normally, a figure of merit describes the health of a battery. It quantifies the ability of the battery to store energy relative to its original state. The health status is 100% when the battery is new and decreases with time. This is similar to the state of charge of a battery. Estimating the state of charge of a battery is, in turn, important to ensure safe and correct use. However, there is no consensus in the industry and science as to what exactly a battery’s health status is or how it should be determined.

The state of health of a battery reflects two signs of aging: progressive capacity decline and impedance increase (another measure of electrical resistance). Estimates of the state of charge of a battery must therefore take into account both the drop in capacity and the increase in impedance.

Lithium ion batteries, however, are complex systems in which both capacity fade and impedance increase are caused by multiple interacting processes. Most of these processes cannot be studied independently since they often occur in simultaneously. The state of health can therefore not be determined from a single direct measurement. Conventional health assessment methods include examining the interactions between the electrodes of a battery. Since such methods often intervene directly in the system “battery”, they make the battery useless, which is hardly desired.

A battery’s health status can also be determined in less invasive ways, for example using adaptive models and experimental techniques. Adaptive models learn from recorded battery performance data and adjust themselves. They are useful if system-specific battery information are not available. Such models are suitable for the diagnosis of aging processes. The main problem, however, is that they must be trained with experimental data before they can be used to determine the current capacity of a battery.

Experimental techniques are used to evaluate certain physical processes and failure mechanisms. This allows the rate of future capacity loss to be estimated. Unfortunately, these methods can not detect any intermittent errors. Alternative techniques use the rate of voltage or capacitance change (rather than raw voltage and current data). In order to accelerate the development of battery technology, further methods need to be found which can accurately predict the life of the batteries.

Severson and her colleagues have created a comprehensive data set that includes the performance data of 124 commercial lithium-ion batteries during their charge and discharge cycles. The authors used a variety of rapid charging conditions with identical discharge conditions. This method caused a change of the battery lives. The data covered a wide range of 150 to 2,300 cycles.

The researchers then used machine learning algorithms to analyze the data, creating models that can reliably predict battery life. After the first 100 cycles of each experimentally characterized battery their model already showed clear signs of a capacity fade. The best model could predict the lifetime of about 91% data sets studied in the study. Using the first five cycles, batteries could be classified into categories with short (<550 cycles) or long lifetimes.

The researchers’ work shows that data-driven modeling using machine learning allows forecasting the state of health of lithium-ion batteries. The models can identify aging processes that do not otherwise apparent in capacity data during early cycles. Accordingly, the new approach complements the previous predictive models. But at Frontis Energy, we also see the ability to combine generated data with models that predict the behavior of other complex dynamic systems.

(Photo: Wikipedia)

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Faster photoelectrical hydrogen

Achieving high current densities while maintaining high energy efficiency is one of the biggest challenges in improving photoelectrochemical devices. Higher current densities accelerate the production of hydrogen and other electrochemical fuels.

Now a compact, solar-powered, hydrogen-producing device has been developed that provides the fuel at record speed. In the journal Nature Energy, the researchers around Saurabh Tembhurne describe a concept that allows capturing concentrated solar radiation (up to 474 kW/m²) by thermal integration, mass transport optimization and better electronics between the photoabsorber and the electrocatalyst.

The research group of the Swiss Federal Institute of Technology in Lausanne (EPFL) calculated the maximum increase in theoretical efficiency. Then, they experimentally verified the calculated values ​​using a photoabsorber and an iridium-ruthenium oxide-platinum based electrocatalyst. The electrocatalyst reached a current density greater than 0.88 A/cm². The calculated conversion efficiency of solar energy into hydrogen was more than 15%. The system was stable under various conditions for more than two hours. Next, the researchers want to scale their system.

The produced hydrogen can be used in fuel cells for power generation, which is why the developed system is suitable for energy storage. The hydrogen-powered generation of electricity emits only pure water. However, the clean and fast production of hydrogen is still a challenge. In the photoelectric method, materials similar to those of solar modules were used. The electrolytes were based on water in the new system, although ammonia would also be conceivable. Sunlight reaching these materials triggers a reaction in which water is split into oxygen and hydrogen. So far, however, all photoelectric methods could not be used on an industrial scale.

2 H2O → 2 H2 + O2; ∆G°’ = +237 kJ/mol (H2)

The newly developed system absorbed more than 400 times the amount of solar energy that normally shines on a given area. The researchers used high-power lamps to provide the necessary “solar energy”. Existing solar systems concentrate solar energy to a similar degree with the help of mirrors or lenses. The waste heat is used to accelerate the reaction.

The team predicts that the test equipment, with a footprint of approximately 5 cm, can produce an estimated 47 liters of hydrogen gas in six hours of sunshine. This is the highest rate per area for such solar powered electrochemical systems. At Frontis Energy we hope to be able to test and offer this system soon.

(Photo: Wikipedia)

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Ammonia energy storage #3

As a loyal reader or loyal reader of our blog, you will certainly remember our previous publications on ammonia energy storage. There, we describe possible ways to extract ammonia from the air, as well as the recovery of its energy in the form of methane (patent pending WO2019/079908A1). Since global food production requires large amounts of ammonia fertilizers, technologies for extraction from air is already very mature. These technologies are essentially all based on the Haber-Bosch process, which was industrialized at the beginning of the last century. During this process, atmospheric nitrogen (N2) is reduced to ammonia (NH3). Despite the simplicity of the molecules involved, the cleavage of the strong nitrogen−nitrogen bonds in N2 and the resulting nitrogen−hydrogen bonds pose a major challenge for catalytic chemists. The reaction usually takes place under harsh conditions and requires a lot of energy, i.e. high reaction temperatures, high pressures and complicated combinations of reagents, which are also often expensive and energy-intensive to manufacture.

Now, a research group led by Yuya Ashida has published an article in the renowned journal Nature, in which they show that a samarium compound in aqueous solution combined with a molybdenum catalyst can form ammonia from atmospheric nitrogen. The work opens up new possibilities in the search for ways to ammonia synthesis under ambient conditions. Under such conditions, less energy is required to produce ammonia, resulting in higher energy efficiency for energy storage. In today’s Haber-Bosch process, air and hydrogen gas are combined via an iron catalyst. The resulting global ammonia production of this process ranges from 250 to 300 tonnes per minute, delivering fertilizers that provide nearly 60% of the world’s population (The Alchemy of Air, available at Amazon).

Comparison of different approaches to produce ammonia. Top: In the industrial Haber-Bosch synthesis of ammonia (NH3), nitrogen gas (N2) reacts with hydrogen molecules (H2), typically in the presence of an iron catalyst. The process requires high temperatures and pressures, but is thermodynamically ideal because only little energy is wasted on side reactions. Center: Nitrogenase enzymes catalyze the reaction of six-electron (e) nitrogen and six protons (H+) under ambient conditions to form ammonia. However, two additional electrons and protons form one molecule of H2. The conversion of ATP (the biological energy “currency”) into ADP drives the reaction. This reaction has a high chemical overpotential. It consumes much more energy than is needed for the actual ammonia forming reaction. Bottom: In the new reaction proposed by Ashida and colleagues, a mixture of water and samarium diiodide (SmI2) is converted to ammonia using nitrogen under ambient conditions and in the presence of a molybdenum catalyst. SmI2 weakens the O−H bonds of the water and generates the hydrogen atoms, which then react with atmospheric nitrogen.

On industrial scale, ammonia is synthesized at temperatures that exceed 400°C and pressures of approximately 400 atmospheres. These conditions are often referred to as “harsh”. During the early days, these harsh conditions were difficult to control. Fatal accidents were not uncommon in the early years of the Haber-Bosch development. This has motivated many chemists to find “milder” alternatives. After all, this always meant searching for new catalysts to lower operating temperatures and pressures. The search for new catalysts would ultimately reduce capital investment in the construction of new fertilizer plants. Since ammonia synthesis is one of the largest producers of carbon dioxide, this would also reduce the associated emissions.

Like many other chemists before them, the authors have been inspired by nature. Nitrogenase enzymes carry out the biological conversion of atmospheric nitrogen into ammonia, a process called nitrogen fixation. On recent Earth, this process is the source of nitrogen atoms in amino acids and nucleotides, the elemental building blocks of life. In contrast to the Haber-Bosch process, nitrogenases do not use hydrogen gas as a source of hydrogen atoms. Instead, they transfer protons (hydrogen ions, H+) and electrons (e) to each nitrogen atom to form N−H bonds. Although nitrogenases fix nitrogen at ambient temperature, they use eight protons and electrons per molecule N2. This is remarkable because the stoichiometry of the reaction requires only six each. This way, nitrogenases provide the necessary thermodynamic drive for nitrogen fixation. The excess of hydrogen equivalents means that nitrogenases have a high chemical overpotential. That is, they consume much more energy than would actually be needed for nitrogen fixation.

The now published reaction is not the first attempt to mimic the nitrogenase reaction. In the past, metal complexes were used with proton and electron sources to convert atmospheric nitrogen into ammonia. The same researchers have previously developed 8 molybdenum complexes that catalyze nitrogen fixation in this way. This produced 230 ammonia molecules per molybdenum complex. The associated overpotentials were significant at almost 1,300 kJ per mole nitrogen. In reality, however, the Haber-Bosch process is not so energy-intensive given the right catalyst is used.

The challenge for catalysis researchers is to combine the best biological and industrial approaches to nitrogen fixation so that the process proceeds at ambient temperatures and pressures. At the same time, the catalyst must reduce the chemical overpotential to such an extent that the construction of new fertilizer plants no longer requires such high capital investments. This is a major challenge as there is no combination of acids (which serve as a proton source) and reducing agents (the electron sources) available for the fixation at the thermodynamic level of hydrogen gas. This means that the mixture must be reactive enough to form N−H bonds at room temperature. In the now described pathway with molybdenum and samarium, the researchers have adopted a strategy in which the proton and electron sources are no longer used separately. This is a fundamentally new approach to catalytic ammonia synthesis. It makes use of a phenomenon known as coordination-induced bond weakening. In the proposed path, the phenomenon is based on the interaction of samarium diiodide (SmI2) and water.

Water is stable because of its strong oxygen-hydrogen bonds (O−H). However, when the oxygen atom in the water is coordinated with SmI2, it exposes its single electron pair and its O−H bonds are weakened. As a result, the resulting mixture becomes a readily available source of hydrogen atoms, protons and electrons, that is. The researchers around Yuya Ashida use this mixture with a molybdenum catalyst to fix nitrogen. SmI2-water mixtures are therefore particularly suitable for this type of catalysis. In them, a considerable coordination-induced bond weakening was previously measured, which was used inter alia for the production of carbon-hydrogen bonds.

The extension of this idea to catalytic ammonia synthesis is remarkable for two reasons. First, the molybdenum catalyst facilitates ammonia synthesis in aqueous solution. This is amazing because molybdenum complexes in water are usually degraded. Second, the use of coordination-induced bond weakening provides a new method for nitrogen fixation at ambient conditions. This also avoids the use of potentially hazardous combinations of proton and electron sources which are a fire hazard. The authors’ approach also works when ethylene glycol (HOCH2CH2OH) is used instead of water. Thus, the candidates for proton and electron sources are extended by an additional precursor.

Ashida and colleagues propose a catalytic cycle for their process in which the molybdenum catalyst initially coordinates to nitrogen and cleaves the N−N bond to form a molybdenum nitrido complex. This molybdenum nitrido complex contains the molybdenum-nitrogen triple bond. The SmI2-water mixture then delivers hydrogen atoms to this complex, eventually producing ammonia. The formation of N−H bonds with molybdenum nitrido complexes represents a significant thermodynamic challenge since the N−H bonds are also weakened by the molybdenum. Nevertheless, the disadvantages are offset by the reduction of the chemical overpotential. The SmI2 not only facilitates the transfer of hydrogen atoms, but also keeps the metal in a reduced form. This prevents undesired molybdenum oxide formation in aqueous solution.

The new process still has significant operational hurdles to overcome before it can be used on an industrial scale. For example, SmI2 is used in large quantities, which generates a lot of waste. The separation of ammonia from aqueous solutions is difficult in terms of energy consumption. However, if the process were used for energy storage in combination with our recovery method, the separation would be eliminated from the aqueous solution. Finally, there is still a chemical overpotential of about 600 kJ/mol. Future research should focus on finding alternatives to SmI2. These could be based, for example, on metals that occur more frequently than samarium and promote coordination-induced bond weakening as well. As Fritz Haber and Carl Bosch have experienced, the newly developed method will probably take some time for development before it becomes available on industrial scale.

(Photo: Wikipedia)

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A Durable Aluminum-Air-Battery

Non-rechargeable batteries, which depend on a reaction between aluminum and oxygen, can store significantly more energy than conventional lithium-ion batteries. The biggest limitation of such aluminum-air batteries is their short shelf life. An improved battery design could help eliminate this limitation. Aluminum and air batteries are based on the property of aluminum to corrode, which is also their weak spot:

4 Al + 3 O2 + 6H2O → 4 Al (OH)3

While an aluminum-air battery is not used, its electrodes corrode causing unwanted discharge. This self-discharge drastically shortens the shelf life of the battery. Brandon Hopkins, of the Massachusetts Institute of Technology in Cambridge, and his colleagues developed an aluminum-air battery that uses a conventional electrolyte during operation. When stored, however, the electrolyte is replaced by oil. Their article was recently published in the journal Science.

The new battery reaches a storage capacity of almost 900 Wh / kg. This makes the prototype comparable to other aluminum-air batteries. In contrast, the new corrosion protection extends the storage time 10,000-fold. The authors suggest that such a battery could be used in long-range drones and grid-independent power generation. At Frontis Energy, we believe that batteries with high storage capacity and durability can be used almost anywhere, for example for sensors and other applications.

(Photo: George Hodan)

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Ammonia energy storage #1

The ancient, arid landscapes of Australia are not only fertile soil for huge forests and arable land. The sun shines more than in any other country. Strong winds hit the south and west coast. All in all, Australia has a renewable energy capacity of 25 terawatts, one of the highest in the world and about four times higher than the world’s installed power generation capacity. The low population density allows only little energy storage and electricity export is difficult due to the isolated location.

So far, we thought the cheapest way to store large amounts of energy was power-to-gas. But there is another way to produce carbon-free fuel: ammonia. Nitrogen gas and water are enough to make the gas. The conversion of renewable electricity into the high-energy gas, which can also be easily cooled and converted into a liquid fuel, produces a formidable carrier for hydrogen. Either ammonia or hydrogen can be used in fuel cells.

The volumetric energy density of ammonia is almost twice as high than that of liquid hydrogen. At the same time ammonia can be transported and stored easier and faster. Researchers around the world are pursuing the same vision of an “ammonia economy.” In Australia, which has long been exporting coal and natural gas, this is particularly important. This year, Australia’s Renewable Energy Agency is providing 20 million Australian dollars in funding.

Last year, an international consortium announced plans to build a $10 billion combined wind and solar plant. Although most of the 9 terawatts in the project would go through a submarine cable, part of this energy could be used to produce ammonia for long-haul transport. The process could replace the Haber-Bosch process.

Such an ammonia factories are cities of pipes and tanks and are usually situated where natural gas is available. In the Western Australian Pilbara Desert, where ferruginous rocks and the ocean meet, there is such an ammonia city. It is one of the largest and most modern ammonia plants in the world. But at the core, it’s still the same steel reactors that work after the 100 years-old ammonia recipe.

By 1909, nitrogen-fixing bacteria produced most of the ammonia on Earth. In the same year, the German scientist Fritz Haber discovered a reaction that could split the strong chemical bond of the nitrogen, (N2) with the aid of iron catalysts (magnetite) and subsequently bond the atoms with hydrogen to form ammonia. In the large, narrow steel reactors, the reaction produces 250 times the atmospheric pressure. The process was first industrialized by the German chemist Carl Bosch at BASF. It has become more efficient over time. About 60% of the introduced energy is stored in the ammonia bonds. Today, a single plant produces and delivers up to 1 million tons of ammonia per year.

Most of it is used as fertilizer. Plants use nitrogen, which is used to build up proteins and DNA, and ammonia delivers it in a bioavailable form. It is estimated that at least half of the nitrogen in the human body is synthetic ammonia.

Haber-Bosch led to a green revolution, but the process is anything but green. It requires hydrogen gas (H2), which is obtained from pressurized, heated steam from natural gas or coal. Carbon dioxide (CO2) remains behind and accounts for about half of the emissions. The second source material, N2, is recovered from the air. But the pressure needed to fuse hydrogen and nitrogen in the reactors is energy intensive, which in turn means more CO2. The emissions add up: global ammonia production consumes about 2% of energy and produces 1% of our CO2 emissions.

Our microbial electrolysis reactors convert the ammonia directly into methane gas − without the detour via hydrogen. The patent pending process is particularly suitable for removing ammonia from wastewater. Microbes living in wastewater directly oxidize the ammonia dissolved in ammonia and feed the released electrons into an electric circuit. The electricity can be collected directly, but it is more economical to produce methane gas from CO2. Using our technology, part of the CO2 is returned to the carbon cycle and contaminated wastewater is purified:

NH3 + CO2 → N2 + CH4