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At least 505 records · Page 28

Tuning of lattice oxygen reactivity and scaling relation to construct better oxygen evolution electrocatalyst

Developing efficient and low-cost electrocatalysts for oxygen evolution reaction is crucial in realizing practical energy systems for sustainable fuel production and energy storage from renewable energy sources. However, the inherent linear scaling relation for most catalytic materials imposes a theoretical overpotential ceiling, limiting the development of efficient electrocatalysts. Herein, using modeled Na x Mn 3 O 7 materials, we report an effective strategy to construct better oxygen evolution electrocatalyst through tuning both lattice oxygen reactivity and scaling relation via alkali metal ion mediation. Specifically, the number of Na + is linked with lattice oxygen reactivity, which is determined by the number of oxygen hole in oxygen lone-pair states formed by native Mn vacancies, governing the barrier symmetry between O–H bond cleavage and O–O bond formation. On the other hand, the presence of Na + could have specific noncovalent interaction with pendant oxygen in *OOH to overcome the limitation from linear scaling relation, reducing the overpotential ceiling. Combining in situ spectroscopy-based characterization with first-principles calculations, we demonstrate that an intermediate level of Na + mediation (NaMn 3 O 7 ) exhibits the optimum oxygen evolution activity. This work provides a new rational recipe to develop highly efficient catalyst towards water oxidation or other oxidative reactions through tuning lattice oxygen reactivity and scaling relation.

36 MATERIALS SCIENCE↗

Molecular simulation and artificial intelligence for the circular economy of bioenergy and bioproducts

The concept of the circular bioeconomy is a carbon neutral, sustainable system with zero waste. One vision for such an economy is based upon lignocellulosic biomass. This lignocellulosic circular bioeconomy requires CO 2 absorption from biomass growth and the efficient deconstruction of recalcitrant biomass into solubilized and fractionated biopolymers, which are then used as precursors for the sustainable production of high-quality liquid fuels, chemical bioproducts, and bio-based materials. Here, in this study, we summarize the roles that molecular dynamics (MD) simulations and machine learning (ML) are playing in overcoming several fundamental challenges hindering the adoption of a circular bioeconomy. Specifically, we discuss the role of MD and ML/AI in overcoming lignocellulose recalcitrance by designing biomass pretreatment methods to efficiently produce solubilized cellulose/lignin/hemicellulose and of that in improving energy-intensive manufacturing of biomass-based materials and their structural and mechanical properties. Quantum mechanical methods and MD simulations, in addition to offering a mechanistic understanding of biomass deconstruction and biomaterials design, can provide meaningful structural, energetics, and physiochemical properties as inputs to train AI/ML models. The ML models can guide the experimental prioritization of materials/solvents and process parameters that significantly accelerate the development of biofuel and biomaterial components of the circular bioeconomy.

Smith, Jeremy C. [Oak Ridge National Laboratory (O↗

Economic Long-Duration Electricity Storage by Using Low-Cost Thermal Energy Storage and High-Efficiency Power Cycle (ENDURING)

The project involved considerable industry participation including General Electric (GE, power cycle analysis), Babcock & Wilcox (B&W), Allied Mineral Products (insulation materials), and Worley-Advisian (system integration). They provided insights on their products or services for component and system designs. The project successfully achieved the project goals of demonstrating technology feasibility for long duration energy storage with a technology path towards 5c/kWh levelized cost of storage. The project has generated four patent applications (one awarded patent and three under review), three published journal papers, a draft book chapter, and five manuscripts under preparation, with several conference papers and numerous presentations including invited talks. An intellectual properties (IP) option agreement has been signed with an U.S. manufacturer, with interests from energy developers. Four related projects with $5.5 million DOE funding support more developments for long duration energy storage and broad industry decarbonization.

25 ENERGY STORAGE↗

Efficient Screening of Bi–Metallic Electrocatalysts for Glycerol Valorization

Glycerol is a byproduct of biodiesel production and, as such, it is of limited economic value. By means of electrooxidation, glycerol can be used as a feedstock for scalable hydrogen production, in addition to conversion to value-added products. The development of novel and efficient catalytic electrode materials for the anodic side of the reaction is a key towards a hydrogen-based energy economy. In the present study, a computational screening protocol combining DFT, scaling relations, and microkinetic modeling allows for a rational selection of novel catalysts that can deliver efficient glycerol electrooxidation, low cost of production, and environmental sustainability. Activity and chemical selectivity towards hydrogen production on pure metal catalysts is discussed in terms of volcano-shaped plots. We find that the selectivity in the glycerol oxidation reaction is influenced by a different energy landscape when in the presence of water and best classified by a comparison of O—H and C—H bond-breaking barriers. In addition, we screened 3570 bi-metallic catalysts in the AB (L1 0 ) and A 3 B (L1 2 ) ordered structures for activity, stability, price, and toxicity. By filtering based on the criteria for toxicity, resistance to oxidation, miscibility, and price, we have identified 5 L1 0 structured catalysts (AgPd, AuPd, PtSb, CuPt, and AgPt) and 20 L1 2 catalysts (Ga 3 Ta, In 3 Ta, Ir 3 W, Ir 3 Mo, Cu 3 Pt, Ir 3 Ta, Ir 3 Re, Pd 3 Bi, Pd 3 Cu, Pd 3 W, Pd 3 Co, Pd 3 Sn, Pd 3 Mo, Pd 3 Ag, Pd 3 Ga, Pd 3 Ta, Au 3 Ru, Pd 3 In, Au 3 Ir, and Pd 3 Au) that are all predicted to show high activity. We also identify an additional 37 L1 0 and 92 L1 2 structured electrocatalysts with an anticipated medium-high activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Critical Material Supply Chain Analysis: Magnetocalorics

Understanding manufacturing cost and supply chain implications of technologies is critical to aid adoption of next-generation energy solutions, such as advanced heating ventilation and air conditioning (HVAC) equipment for building energy efficiency. This report provides insights into the market, regulatory, technology, and cost drivers most impacting the adoption of magnetocaloric refrigeration (MCR) systems in the U.S., with a focus on the rare earth materials requirements, manufacturing costs of key components, and detail on the supply chain of critical materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE↗

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗

Oxidation‐Driven Enhancement of Intrinsic Properties in MXene Electrodes for High‐Performance Flexible Energy Storage

Abstract MXenes, a novel class of 2D materials, exhibit great potential for energy storage due to their unique layered structure and excellent electrical conductivity. However, improving the intrinsic electrochemical storage capacity of MXenes remains a significant challenge, often requiring the incorporation of other Faradaic materials. Oxidation, in particular, poses a key issue that impacts the capacity of MXene devices. In this study, controlled oxidation is employed to create nanoscale holes within MXene, transforming them into holey MXene (H‐MXene) nanosheets. These porous structures shorten ion transport distances and increase ion transport pathways, thereby significantly enhancing the electrochemical storage capacity of MXenes. The resulting H‐MXene micro‐supercapacitors (MSCs) demonstrate exceptional performance, achieving an aerial capacitance 2.5 times that of unmodified MXene electrodes, along with excellent cycling stability, retaining 91.7% of their capacitance after 10 000 cycles. Additionally, a flexible integrated system combining energy storage and sensing functionalities is developed, showcasing its scalability in self‐powered sensing applications. The incorporation of self‐healing polyurethane (PU) enables the device to retain 90% of its storage capacity after undergoing self‐healing. This study presents a novel approach for developing high‐performance MXene‐based energy storage devices and provides valuable insights into efficient ion transport and storage in 2D materials.

Cheng, Yongfa [Department of Materials Science and↗

An experimental database of cell performance for vanadium redox flow battery

The continual growth in energy demand has resulted in the deployment of renewable energy generators to reduce the impact of fossil fuel dependence. However, these generators often suffer from intermittency and require energy storage when there is over-generation and the subsequent release of this stored energy at high demand. One promising energy storage technology which can provide a solution to improve energy management and grid stability, is the redox flow battery. Among the numerous flow battery systems, vanadium redox flow battery is the most iconic solution to large scale energy storage, giving a more efficient link between energy production, especially from renewables, and energy demand. The aim of the current database is to characterize the performance of the cell design and to provide training/validation data for physical model or data-driven model. The database includes hundreds of experimental cell performance data of vanadium redox flow battery with various current densities for multiple charge-discharge cycles. All the cell parameters, chemical parameters, material parameters, operation parameters and thermodynamic parameters of the cell system are listed. Coulomb, voltaic and energy efficiencies are also provided. The database will be helpful for researchers in the field of redox flow batteries.

Gao, Peiyuan↗

Ultra-fast non-equilibrium synthesis of cathode materials for Li-ion batteries

Synthesis of cathode materials plays an important role in determining the production efficiency, cost and performance of lithium-ion batteries. However, the conventional synthesis methods always experience a slow heating rate and involve a complicated multi-step reaction process and sluggish reaction dynamics, leading to high energy and long time consuming. Herein, we report a high-temperature shock (HTS) strategy for the ultra-fast synthesis of cathode materials in seconds. The HTS process experiences an ultra-high heating rate, leading to a non-equilibrium reaction and fast reaction kinetics and avoiding high energy and long time consuming. Mainstream cathode materials (such as LiMn 2 O 4 , LiCoO 2 , LiFePO 4 , and Li-rich layered oxide/NiO heterostructured material) are successfully synthesized with pure phases, oxygen vacancies, ultra-small particle sizes and good electrochemical performance. In conclusion, the HTS process not only provides an efficient synthesis approach for cathode materials but also can be extended beyond lithium-ion batteries.

25 ENERGY STORAGE↗

Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells

In the design of organic solar cells, there has been a need for materials with high power conversion efficiencies. Scharber’s model is commonly used to predict efficiency; however, it exhibits poor performance with new non-fullerene acceptor (NFA) devices, since it was designed for fullerene-based devices. In this work, an empirical model is proposed that can be a more accurate alternative for NFA organic solar cells. Additionally, many screening studies use computationally expensive methods. A model based on using semiempirical simplified time-dependent density functional theory (sTD-DFT) as an alternative method can accelerate the calculations and yield a similar accuracy. The models presented in this paper, termed organic photovoltaic efficiency predictor (OPEP) models, have shown significantly lower errors than previous models, with OPEP/B3LYP yielding errors of 1.53% and OPEP/sTD- DFT of 1.55%. As a result, the proposed computational models can be used for the fast and accurate screening of new high-efficiency NFAs/donor pairs.

14 SOLAR ENERGY↗

Embedded acoustic sensing and monitoring techniques for small modular reactors

The goal of this project was to study the applicability of specific innovative instrumentation techniques for assessing parameters needed for safe small modular reactor operation and safeguarding of nuclear material. Small modular reactor core designs are currently being developed to provide energy more effectively and efficiently than in the past because they can be built as modules at fabrication sites and then transported to a power-producing facility. However, these modules and/or the final core will often be sealed and not accessible again until disposal. Instead of instruments that access the core directly, during and after operation, to monitor flux/dose and structural integrity, as current power plants use, new sensors need to be designed that can be built into the reactor initially to determine operating history, structural integrity through operation of the system, and nuclear material accountancy after shutdown and before disposition of the core. Embedded sensors already exist that can provide neutron flux, gamma dose, and temperatures, but techniques to expand upon these for assessing structural health and material inventory in the system over time need to be developed. Structural health assessments include the detection and imaging of cracks in the components that could eventually cause radioactive fission products to be released.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Energy filtering–induced ultrahigh thermoelectric power factors in Ni 3 Ge

Traditional thermoelectric materials rely on low thermal conductivity to enhance their efficiency but suffer from inherently limited power factors. Innovative pathways to optimize electronic transport are thus crucial. Here, we achieve ultrahigh power factors in Ni 3 Ge-based systems through an unconventional thermoelectric materials design principle. When overlapping flat and dispersive bands are engineered to the Fermi level, charge carriers can undergo intense interband scattering, yielding an energy filtering effect similar to what has long been predicted in certain nanostructured materials. Via a multistep DFT-based screening method developed here, we find a family of L1 2 -ordered binary compounds with ultrahigh power factors up to 11 mW m −1 K −2 near room temperature, which are driven by an intrinsic phonon-mediated energy filtering mechanism. Our comprehensive experimental and theoretical study of these intriguing materials paves the way for understanding and designing high-performance scattering-tuned metallic thermoelectrics.

Science & Technology - Other Topics↗

Substitution of Pb with (Li 1/2 Bi 1/2 ) in PbZrO 3 -based antiferroelectric ceramics

PbZrO 3 -based antiferroelectric (AFE) ceramics are promising dielectrics for high-energy-density capacitors due to their reversible phase transitions during charge–discharge cycles. In this work, a new composition series, [Pb 0.93–x La 0.02 (Li 1/2 Bi 1/2 ) x Sr 0.04 ][Zr 0.57 Sn 0.34 Ti 0.09 ]O 3 , with Li + and Bi 3+ substitution of Pb 2+ at x=0 , 0.04, 0.08, 0.12, 0.16 is investigated for the microstructure evolution, ferroelectric (FE) and dielectric properties. It is found that Li + and Bi 3+ substitution can significantly reduce the sintering temperature and simultaneously enhance the dielectric breakdown strength. An ultrahigh energy efficiency (94.0%) and a large energy density (3.22J/cm 3 ) are achieved in the composition of x = 0.12 with a low sintering temperature (1075°C).

36 MATERIALS SCIENCE↗

Selective Recovery of Critical Minerals from Simulated Electronic Wastes Via Reaction‐Diffusion Coupling

Abstract Atom‐ and energy‐efficient chemical separations are urgently needed to meet the surging demand for critical materials that has strained supply chains and threatened environmental damage. In this study, we used reaction‐diffusion coupling to separate iron, neodymium, and dysprosium ions from model feedstocks of permanent magnets, which are typically found in electronic wastes. Feedstock solutions were placed in contact with a hydrogel loaded with potassium hydroxide and/or dibutyl phosphate, resulting in complex precipitation patterns as the various metal ions diffused into the reaction medium. Specifically, we observed the precipitation of up to 40 mM of iron from the feedstock, followed by the enrichment of 73 % dysprosium, and the extraction of >95 % neodymium product at a further distance from the solution‐gel interface. We designed a series of experiments and simulations to determine the relevant ion diffusivities, D Nd =5.4×10 −10 and D Dy =5.1×10 −10 m 2 /s, and precipitation rates, k Nd =1.0×10 −5 and k Dy =5.0×10 −3 m 9 mol −3 s −1 , which enabled a numerical model to be established for predicting the distribution of products in the reaction medium. Our proof‐of‐concept study validates reaction‐diffusion coupling as an effective and versatile approach for critical materials separations, without relying on ligands, membranes, resins, or other specialty chemicals.

Wang, Qingpu [Physical and Computational Sciences ↗

Evolution of thermo-mechanical properties of concrete with calcium aluminate cement and special aggregates for energy storage

Highlights: • CAC Concrete with stable aggregates is suitable for high temperatures with cycles. • Concrete suffered performance changes after the first thermal cycle (dehydration). • Subsequent thermal cycles showed stabilization and slight performance decreases. With the ever-expanding presence of solar energy, the design of cost-efficient heat energy storage systems is becoming increasingly relevant. Concrete is a potential solid material for these systems but raises questions of its response at high temperatures in operating conditions. This work studies concrete designed with calcium aluminate cement and three types of aggregates that are stable at high temperatures. The designed concrete mixes were exposed to thermal cycles (290–550 °C), and their thermal fatigue response was evaluated with mechanical, cracking, thermal, and microstructural analyses at room temperature after heat cycles. The obtained results show that the main changes are mostly produced after the first thermal cycle and are stabilized during successive thermal cycles, with only a slight decrease in the thermo-mechanical properties. The results showed stabilization of cracking, crack widths between 10 and 80 μm, reduction of compressive strength, around 50–65%, and reduction of the thermal conductivity by 30%.

36 MATERIALS SCIENCE↗