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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Single-Crystalline Ni-Rich LiNi x Mn y Co 1– x – y O 2 Cathode Materials: A Perspective

To drive electrical vehicles for long-range, the energy density of Li-ion batteries must be further enhanced, which requires high-energy cathode materials. Among them, Ni-rich LiNi x Mn y Co 1–x–y O 2 (x > 0.5, NMC) is one of the most promising candidates. However, traditional poly-crystal (PC) NMC materials, whose particles are secondary clusters consisting of many primary crystalline particles, are susceptible to pulverization along the inter grain/particle boundaries, resulting in poor cycle stability. Recently, single crystal (SC)-NMC cathodes are proposed as they are believed to have several merits such as high structural integrity, lower interface with electrolyte, and potentially better energy storage performance. Nevertheless, several queries, such as the merits of SC structure and the mechanism for their structure degradation, are still controversial and required to be addressed. Here, in this study, the synthesis parameters, properties, energy storage as well as safety of SC- and PC-NMC cathodes with various Ni contents are critically reviewed, for clarifying the merits and drawbacks of SC. Furthermore, the study focuses on the recent advances of insight mechanisms and strategies for stabilizing the structure/interface by doping, morphology engineering, surface coating, and composition tailoring. The remaining challenges, safety concerns, and perspectives to enhance the electrochemical performance of SC-NMC cathodes for electric vehicle application are followed.

25 ENERGY STORAGE↗
DOE OSTI2023

Thermochromic Halide Perovskite Windows with Ideal Transition Temperatures

Abstract Urban centers across the globe are responsible for a significant fraction of energy consumption and CO 2 emission. As urban centers continue to grow, the popularity of glass as cladding material in urban buildings is an alarming trend. Dynamic windows reduce heating and cooling loads in buildings by passive heating in cold seasons and mitigating solar heat gain in hot seasons. Here, reduced energy consumption in highly glazed buildings in a mesoscopic building energy model is demonstrated when thermochromic windows are employed. Savings are realized across eight disparate climate zones of the United States. The model is used to determine ideal critical transition temperatures of 20–27.5 °C for thermochromic windows based on metal halide perovskite materials. Ideal transition temperatures are realized experimentally in composite metal halide perovskite films composed of perovskite crystals and an adjacent reservoir phase. The transition temperature is controlled by cointercalating methanol, instead of water, with methylammonium iodide and tailoring the hydrogen‐bonding chemistry of the reservoir phase. Thermochromic windows based on metal halide perovskites represent a clear opportunity to mitigate the effects of energy‐hungry buildings.

14 SOLAR ENERGY↗
DOE OSTI2023

Rational Design of Fluorinated Electrolytes for Low Temperature Lithium‐Ion Batteries

Abstract Nonaqueous carbonate electrolytes are commonly used in commercial lithium‐ion battery (LIB). However, the sluggish Li + diffusivity and high interfacial charge transfer resistance at low temperature (LT) limit their wide adoption among geographical areas with high latitudes and altitudes. Herein, a rational design of new electrolytes is demonstrated, which can significantly improve the low temperature performance below −20 °C. This electrolyte is achieved by tailoring the chemical structure, i.e., altering the fluorination position and the degree of fluorination, of ethyl acetate solvent. It is found that fluorination adjacent to the carbonyl group or high degree of fluorination leads to a stronger electron‐withdrawing effect, resulting in low atomic charge on the carbonyl oxygen solvating sites, and thus low binding energies with Li + ions at LT. The optimal electrolyte 2,2,2‐trifluoroethyl acetate (EA‐f) shows significantly improved cycle life and C‐rate of a NMC622/graphite cell when cycled at −20 °C and −40 °C, respectively. In addition to superior LT performance, the electrolyte is nonflammable and tolerant for high voltage charging all owing to its fluorine content. This work provides guidance in designing next‐generation electrolytes to address the critical challenge at subzero temperatures.

25 ENERGY STORAGE↗
DOE OSTI2023

Nanocrystal‐Enabled Perovskite Heterojunctions in Photovoltaic Applications and Beyond

Abstract Heterojunctions are used to tailor the properties of semiconductors in optoelectronic devices, yet for emerging devices composed of metal halide perovskites, fabricating perovskite/perovskite heterojunctions has proved challenging due to solvent incompatibilities and rapid homogenization due to ion migration. Recent studies have demonstrated various strategies for using perovskite nanocrystals as a component to fabricate perovskite/perovskite heterojunctions, either with a perovskite thin film or a second nanocrystal layer. Heterojunctions such as these can impart many advantages of both bulk and nanocrystalline perovskite morphologies. This perspective focuses on recent developments of solution‐processed perovskite heterojunctions for solar cells and novel optoelectronic devices, in particular, highlighting the demonstrated and potential advantages of nanocrystal‐enabled fabrication strategies. A central tenet of this perspective is that the synthesis and dispersion of perovskite nanocrystals in non‐polar organic solvents offers a key processing advantage over traditional perovskite precursor solutions in polar solvents since the former allows for layer‐by‐layer deposition without dissolving an underlying perovskite film or crystal. This processing advantage, coupled with nanocrystal size control and ligand chemistry, enables perovskite heterojunctions with highly tunable optical and electrical properties. Such heterojunctions may enable disruptive technological advances in broad classes of devices such as solar cells, photodetectors, sensors, and (in)coherent photon sources with tunable polarization.

14 SOLAR ENERGY↗
DOE OSTI2024

Ultrathin Microporous Transport Layers: Implications for Low Catalyst Loadings, Thin Membranes, and High Current Density Operation for Proton Exchange Membrane Electrolysis

Porous transport layers (PTL) and their surface properties have the potential to improve the performance of proton exchange membrane water electrolyzers (PEMWE), which is imperative to reduce feedstock costs and lead to their widespread implementation. This work introduces a novel generation of titanium microporous layers (MPLs) with ultra-low thicknesses of approx. 20 um which reduces raw material costs. They also feature advanced interfacial properties tailored to maximize catalyst utilization at low Ir-loadings. The bulk morphology and surface properties of the hierarchically structured PTLs are assessed by X-ray tomographic microscopy. The low surface roughness of the MPL allows the use of thinner membranes since it minimizes possible deformations in the membrane. Cells containing the MPLs outperformed those containing state-of-the-art commercially available PTL materials by up to 100 mV at 7 A cm-2 in combination with low-loaded catalyst-coated membranes of 0.4 mgIr cm-2. Hydrogen crossover is also reduced, especially at low current densities, leading to a larger turndown ratio which can enable more cost-effective operating strategies. Finally, these rationally designed MPLs also lead to high catalyst utilization by overcoming the naturally occurring high in-plane resistance of low-loaded catalyst layers.

hydrogen crossover↗
DOE OSTI2023

Harnessing Electrochemical‐Mechanical Couplings to Improve the Reliability of Solid‐State Batteries

Abstract One key barrier to using lithium‐metal anode batteries is that metal dendrites can penetrate solid electrolytes, causing short‐circuits and battery failures. It is established that this failure is likely caused by crack propagation due to electrodeposition‐induced stresses from lithium metal. This study explores ways to harness these electrochemical‐mechanical couplings to control dendrite growth and improve battery reliability using a phase‐field model and targeted fracture experiments. The results show that dendrite growth can be effectively mitigated by applying mechanical stresses or tailoring the material's fracture toughness. This study also outlines the requirements for compressive stress to halt or deflect dendrites as a function of the overpotential and discusses the role of microstructure in this process.

Monismith, Scott↗
DOE OSTI2024

Platinum/Tantalum Carbide Core–Shell Nanoparticles with Sub‐Monolayer Shells for Methanol and Oxygen Electrocatalysis

Abstract Core–shell architectures provide great opportunities to improve catalytic activity, but achieving nanoparticle stability under electrochemical cycling remains challenging. Herein, core–shell nanoparticles comprising atomically thin Pt shells over earth‐abundant TaC cores are synthesized and used as highly durable electrocatalysts for the methanol oxidation reaction (MOR) and the oxygen reduction reaction (ORR) needed to drive direct methanol fuel cells (DMFCs). Characterization data show that a thin oxidic passivation layer protects the TaC core from undergoing dissolution in the fuel cell‐relevant potential range, enabling the use of partially covered Pt/TaC core–shell nanoparticles for MOR and ORR with high stability and enhanced catalytic performance. Specifically, at the anode the surface‐oxidized TaC further enhances MOR activity compared to conventional Pt nanoparticles. At the cathode, the Pt/TaC catalyst feature increases tolerance to methanol crossover. These results show unique synergistic advantages of the core–shell particles and open opportunities to tailor catalytic properties for electrocatalytic reactions.

Chemistry↗
DOE OSTI2025

Alternative Solid‐State Synthesis Route for Highly Fluorinated Disordered Rock‐Salt Cathode Materials for High‐Energy Lithium‐Ion Batteries

Abstract Fluorination has been identified as a key element for enabling the stable cycling of earth‐abundant manganese‐based disordered rock salt (DRX) cathodes. However, fluorination in the DRX bulk remains a challenge for scalable solid‐state synthesis. In this study, a tailored reaction pathway is proposed to synthesize a highly fluorinated DRX. It is demonstrated for the first time that the unconventional precursors, Li 6 MnO 4 , MnF 2 , and TiO 2 , can avoid the formation of Mn‐based intermediates (such as Li 2 (Mn,Ti)O 3, LiMnO 2 , and Mn 3 O 4 ), which, once formed, persist until the synthesis temperature reaches close to or above that required for fluorine volatility. Therefore, this method can form a highly fluorinated DRX with a composition of Li 1.23 Mn 0.40 Ti 0.37 O 2−y F y ( y = 0.29–0.34) at a low temperature (800 °C) relative to that required for conventional DRX solid‐state reactions (≥900 °C). Li 1.23 Mn 0.40 Ti 0.37 O 2−y F y ( y = 0.29–0.34) delivers a specific capacity above 300 mAh g −1 and a specific energy of 980 Wh kg −1 at 30 °C. Detailed characterization reveals that this DRX phase reversibly utilizes Mn 2+/3+ redox in the low‐voltage region and Mn 3+/4+ redox in the middle‐voltage range, whereas reversible oxygen redox is observed at high potentials.

Avvaru, Venkata Sai↗
DOE OSTI2026

Localized Heterogeneous Nucleation for Vapor‐Assisted Sequential Deposition of Metal Halide Perovskites

Vapor-assisted hybrid two-step deposition, which combines thermally evaporated inorganic layers with solution-processed organic halides to form halide perovskites, has emerged as a scalable and industry-compatible route for textured tandem photovoltaics. However, this process is often hindered by reaction-limited phase formation, particularly when compact, non-porous, and highly crystalline inorganic layers formed by thermal evaporation restrict subsequent conversion, resulting in incomplete reaction and pronounced depth-dependent heterogeneity. In this study, we introduce a strategy to regulate the inorganic precursor layer by incorporating localized heterogeneous nucleation sites. Sparsely distributed hydrophilic metal oxide species serve as effective nucleation centers during vapor deposition, enabling effective control over film morphology and crystal orientation from the early stages of growth. This tailored inorganic framework facilitates the subsequent incorporation of organic halides, alleviating reaction limitations and suppressing residual unreacted precursors. Consequently, the perovskite films exhibit improved stoichiometric uniformity and enhanced optoelectronic quality, enabling wide-bandgap perovskite solar cells with markedly improved performance and operational stability. This work provides important mechanistic insight into crystal growth engineering of vapor-deposited perovskite thin films.

nucleation↗
DOE OSTI2022

Effects of penta‐coordinated Al 3+ sites and Ni defective sites on Ni/ Al 2 O 3 for CO methanation

Abstract Engineering sophisticated structure of Al 2 O 3 and controlling the structure of counterpart metal active sites remain challenges to achieve a high catalytic‐performance in heterogeneous catalysis. Herein, we present a confinement strategy to stabilize homogeneous Ni by penta‐coordinated Al 3+ anchoring sites in Al 2 O 3 . This approach is involved in using a metal–organic framework as host to load Ni 2+ ions, by the aim of producing a confined Ni/Al 2 O 3 catalyst after a standard calcination. Metal–support interaction between Ni and Al 2 O 3 was tailored to be medium to avoid the formation of inactive NiAl 2 O 4 , which favors the generation of more available Ni active sites accessible to the reactants. The resultant Ni/Al 2 O 3 exhibited superior catalytic performance in comparison with the control Ni/Al 2 O 3 in CO methanation owing to the presence of defective sites on sufficient Ni 0 surface. Furthermore, the presence of oxygen vacancies on Al 2 O 3 and hydrogen spillover contributed toward excellent coke resistance properties in the reaction.

Engineering↗
DOE OSTI2025

Computational screening of fly ash zeolite sorbents for boric acid removal

In the United States, many impoundments at coal-fired power plants contain elevated contaminants like arsenic, boron, barium, and selenium. Zeolites synthesized from fly ash show promise as sorbents for these contaminants. However, optimizing sorption capacity is challenging due to numerous possible topologies, silicon to aluminum (Si/Al) ratios, and cation types. In this study, molecular simulations are used to design cationic zeolites for boric acid adsorption. Force field models based on quantum mechanical calculations (PBE + D2) for Na-, Ca-, Mn-, and Fe-exchanged chabazite and LTA are presented. The new D2FF force fields reproduce DFT energies with about half the error of UFF. Zeolite performance depends on Si/Al ratio and cation type, with low Si/Al ratio chabazite (CHA) and phillipsite (PHI) zeolite frameworks exchanged with Ca 2+ or Na + /Ca 2+ mixtures showing the highest adsorption. In conclusion, these findings suggest tailored fly ash-derived zeolites could provide effective boron removal from leachate ponds.

CCR impoundment↗
DOE OSTI2020

Control of the Folding Dynamics of Self-Reconfiguring Magnetic Microbots Using Liquid Crystallinity

Reconfigurable microdevices are being explored in a range of contexts where their life-like abilities to move and change shape are important. While much work has been done to control the motion of these microdevices by engineering their geometry and composition, little is known about their dynamics in complex fluid environments with non-Newtonian rheology. Here in this paper, it is shown how the actuation dynamics of reconfigurable microdevices made by assembly of patchy magnetic microcubes, which are referred to as “microbots,” can be modulated by their interactions with the anisotropic viscoelastic environment of a liquid crystal (LC). The free energy arising from the elastic strain of LC and formation of topological defects around the microbots influences their folding dynamics, which can be tuned by tailoring both the far-field orientation of the LC and the local ordering of the LC at the microbot surfaces. These findings represent a first step toward establishing a general set of design rules to control the dynamics of microbots using complex anisotropic fluids.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids

Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Neuromorphic computing has the potential to revolutionize future technologies and our understanding of intelligence, yet it remains challenging to realize in practice. The learning-from-mistakes algorithm, inspired by the brain's simple learning rules of inhibition and pruning, is one of the few brain-like training methods. This algorithm is implemented in neuromorphic memristive hardware through a codesign process that evaluates essential hardware trade-offs. While the algorithm effectively trains small networks as binary classifiers and perceptrons, performance declines significantly with increasing network size unless the hardware is tailored to the algorithm. This work investigates the trade-offs between depth, controllability, and capacity—the number of learnable patterns—in neuromorphic hardware. This highlights the importance of topology and governing equations, providing theoretical tools to evaluate a device's computational capacity based on its measurements and circuit structure. The findings show that breaking neural network symmetry enhances both controllability and capacity. Additionally, by pruning the circuit, neuromorphic algorithms in all-memristive circuits can utilize stochastic resources to create local contrasts in network weights. Through combined experimental and simulation efforts, the parameters are identified that enable networks to exhibit emergent intelligence from simple rules, advancing the potential of neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗
DOE OSTI2020

Strain‐Enhanced Metallic Intermixing in Shape‐Controlled Multilayered Core–Shell Nanostructures: Toward Shaped Intermetallics

Abstract Controlling the surface composition of shaped bimetallic nanoparticles could offer precise tunability of geometric and electronic surface structure for new nanocatalysts. To achieve this goal, a platform for studying the intermixing process in a shaped nanoparticle was designed, using multilayered Pd‐Ni‐Pt core–shell nanocubes as precursors. Under mild conditions, the intermixing between Ni and Pt could be tuned by changing layer thickness and number, triggering intermixing while preserving nanoparticle shape. Intermixing of the two metals is monitored using transmission electron microscopy. The surface structure evolution is characterized using electrochemical methanol oxidation. DFT calculations suggest that the low‐temperature mixing is enhanced by shorter diffusion lengths and strain introduced by the layered structure. The platform and insights presented are an advance toward the realization of shape‐controlled multimetallic nanoparticles tailored to each potential application.

Williams, Benjamin P.↗
DOE OSTI2020

Soft Polymer Janus Nanoparticles at Liquid–Liquid Interfaces

Abstract Soft polymeric Janus nanoparticles (JNPs), made from polystyrene‐ b ‐poly(butadiene)‐ b ‐poly(methylmethacrylate), PS‐PB‐PMMA, triblock terpolymers, assemble into a monolayer at the water–oil interface to reduce interfacial tension. The extent to which the polymer chains can deform influences the packing density of the JNPs at the interface. The longer the polymer chains are relative to the core, the softer are the JNPs, resulting in a JNPs assembly with a lower initial lateral packing density. The interfacial activity of JNPs can be further tuned by complexation of the PMMA chains with lithium ions that are introduced into the water phase. This work provides a fundamental understanding of soft JNPs packing at the water–oil interface and provides a strategy to tailor the areal density of soft JNPs at liquid–liquid interface, enabling the design of smart responsive structured‐liquid systems.

Jiang, Yufeng↗
DOE OSTI2020

Thermally Activated Adsorption in Metal–Organic Frameworks with a Temperature‐Tunable Diffusion Barrier Layer

Abstract Modification of the external surfaces of metal–organic frameworks offers a new level of control over their adsorption behavior. It was previously shown that capping of MOFs with ethylenediamine (EDA) can effectively retain small gaseous molecules at room temperature. Reported here is a temperature‐induced variation in the capping‐layer gate‐opening mechanism through a combination of in situ infared experiments and ab initio simulations of the capping layer. An atypical acceleration and increase in the loading of weakly adsorbed molecules upon raising the temperature above room temperature is observed. These findings show the discovery of novel temperature‐dependent kinetics that goes beyond standard kinetics and suggest a new avenue for tailoring selective adsorption by thermally tuning the surface barrier.

Tan, Kui↗