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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Elements of Life, Photosynthesis and Genomics

I am a Professor of Biochemistry, Biophysics and Structural Biology and Plant and Microbial Biology at the University of California in Berkeley. I was born and raised in India, emigrated to the United States to attend university, earning a B.S. in Molecular Biology and a Ph.D. in Biochemistry at the University of Wisconsin in Madison. Following post-doctoral studies with Lawrence Bogorad at Harvard University where I became interested in genetic control of trace element quotas, I joined the department of Chemistry and Biochemistry at UCLA. One of the first to appreciate essential trace metals as potential regulators of gene expression, I articulated the details of the nutritional Cu regulon in Chlamydomonas. In parallel, I used genetic approaches to discover the genes governing missing steps in tetrapyrrole metabolism, including the attachment of heme to apocytochromes in the thylakoid lumen and the factors catalyzing the formation of ring V in chlorophyll. After biochemistry and classical genetics, I embraced genomics, taking a leadership role on the Joint Genome Institute’s efforts on the Chlamydomonas genome and more recently, contributing to high quality assemblies of several genomes in the green algal radiation, and large transcriptomic and proteomic datasets — focusing on the diel metabolic cycle in synchronized cultures and acclimation to key environmental and nutritional stressors — that are well-used and appreciated by the community. Finally, a new venture in Berkeley is the promotion of Auxenochlorella protothecoides as the true “green yeast” and as a platform for engineering algae to produce useful bioproducts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Systematic and statistical uncertainties of the hilbert-transform based high-precision FID frequency extraction method

Pulsed nuclear magnetic resonance (NMR) is widely used in high-precision magnetic field measurements. The absolute value of the magnetic field is determined from the precession frequency of nuclear magnetic moments. The Hilbert transform is widely used to extract the phase function from the observed free induction decay (FID) signal and then its frequency. In this paper, a detailed implementation of a Hilbert-transform based FID frequency extraction method is described. How artifacts and noise level in the FID signal affect the extracted phase function are derived analytically. A method of mitigating the artifacts in the extracted phase function of an FID is discussed. Correlations between noises of the phase function samples are studied for different noise spectra. We discovered that the error covariance matrix for the extracted phase function is nearly singular and improper for constructing the $\chi^2$ used in the fitting routine. A down-sampling method for fixing the singular covariance matrix has been developed, so that the minimum $\chi^2$-fit yields properly the statistical uncertainty of the extracted frequency. Other practical methods of obtaining the statistical uncertainty are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗
DOE OSTI2020

Experimental assessment of antimony (Sb) in pure uranium for immobilizing fission product lanthanides

The use of fuel additives is one of the concepts to mitigate fuel cladding chemical interaction (FCCI) for metallic fuel because fission product lanthanides are expected to be immobilized by the additive. Antimony (Sb) has been discovered to be a good candidate in UZr fuel. The present study focuses on its mechanism for immobilization in pure uranium, U–4Sb alloy was fabricated to understand the Sb behavior, while U–4Sb–4Ce was fabricated to simulate the case when lanthanides are generated. Both of the as-cast and annealed samples were characterized by scanning electron microscope (SEM) and energy dispersive spectrometer (EDS). U–Sb precipitates are formed in U–4Sb alloy, while U–Sb and Ce–Sb were found in U–4Sb–4Ce alloy, thermal exposure does not change the Sb-precipitation morphologies or chemical composition. Furthermore, diffusion couple tests between those alloys and cladding materials (Fe or HT9) under 650 °C for 500 h were performed and analyzed using SEM/EDS. Diffusion couple tests demonstrate the reaction between cladding and uranium, while no reaction between Sb-precipitations and cladding materials was found.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Unraveling the size fluctuation and shrinkage of nanovoids during in situ radiation of Cu by automatic pattern recognition and phase field simulation

Void formation is an important aspect of irradiation response of metals. In situ transmission electron microscopy observation for void evolution during irradiation is an effective technique for studying void evolution. However, the amount of data collected during in situ studies drastically overwhelm the current capability for manual data analyses. Here, we used a data-driven approach where a convolutional neural network combined with greedy matching to detect and track nanovoid evolutions and migrations. This approach was able to discover the surprising phenomena of void size fluctuation and shrinkage during irradiation of Cu with pre-existing nanovoids. Phase–field simulations revealed the fundamental mechanism behind this in situ observed phenomenon of void size fluctuation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tortuosity Effects in Lithium-Metal Host Anodes

Lithium (Li) metal is the ultimate anode material for Li batteries because of its highest capacity among all candidates. Recent research has focused on stable interphase and host materials to address its low stability and reversibility. Here, we discover that tortuosity is a critical parameter affecting the morphology and electrochemical performances of hosted Li anodes. In three types of hosts—vertically aligned, horizontally aligned, and random reduced graphene oxide (rGO) electrodes with tortuosities of 1.25, 4.46, and 1.76, respectively—we show that high electrode tortuosity causes locally higher current density on the top surface of electrodes, resulting in thick Li deposition on the surface and degraded cycling performance. Low electrode tortuosity in the vertically aligned rGO host enables homogeneous Li transport and uniform Li deposition across the host, realizing greatly improved cycling stability. Furthermore, using this principle of low tortuosity, the designed electrode shows through-electrode uniform morphology with anodic Coulombic efficiency of ~99.1% under high current and capacity cycling conditions.

25 ENERGY STORAGE↗
DOE OSTI2020

Anode-free, Lean-Electrolyte Lithium-Sulfur Batteries Enabled by Tellurium-Stabilized Lithium Deposition

For realizing practically viable lithium-sulfur (Li-S) batteries, it is imperative to stabilize Li deposition and improve cyclability while reducing excess Li and electrolyte. We have discovered that introducing tellurium (Te) into the Li-S system as a cathode additive significantly improves the reversibility of Li plating and stripping by forming a tellurized and sulfide-rich solid-electrolyte interphase (SEI) layer on the Li surface. A remarkable improvement in cyclability is demonstrated in anode-free full cells with limited Li inventory and large-area Li-S pouch cells under lean electrolyte conditions. Tellurium reacts with polysulfides to generate soluble polytellurosulfides that migrate to the anode side and form stabilizing lithium thiotellurate and lithium telluride in situ as SEI components. A significant reduction in electrolyte decomposition on the Li surface is also engendered. This work demonstrates Te inclusion as a viable strategy for stabilizing Li deposition and establishes a robust evaluation framework for preserving electrochemical performance under limited Li and limited electrolyte conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Overcoming Shockley-Queisser limit using halide perovskite platform?

The Intergovernmental Panel on Climate Change (IPCC) reveals that the global temperature has reached its highest level in the last 2,000 years. Development of emissions-free electrification technologies such as photovoltaics (PV) can be a great paramountcy to balance the climate pressure and the growing demand on energy. Although many PV technologies have been demonstrated so far, all the single-junction PVs are still subjected to the well-known efficiency cap of the Shockley-Queisser limit (33.7%), with most of the absorbed solar energy lost into heat. In parallel to delicate system-level designs, such as tandem, multi-junction, photothermal, or up-/down-conversion, we ask the question about the feasibility of overcoming the SQ limit at material level. In this study, we first dissect the origin of the limit, and then, by using the emerging perovskite as the platform, we list several potential pathways (i.e., hot carrier, multi-exciton generation, intermediate band gap, and ferroelectricity that have been newly discovered or can be introduced in the perovskite) to the roadmap of exceeding the SQ limit.

14 SOLAR ENERGY↗
DOE OSTI2022

Thermoelectrics: From longitudinal to transverse

Thermoelectric power generation is a promising technology to realize a sustainable society because it directly converts thermal energy into electricity in a solid. Conventional thermoelectric generation is driven by the Seebeck effect, discovered by T.J. Seebeck in 1821, in which a charge current J c is generated in the direction parallel to a temperature gradient ∇T, the longitudinal geometry. Here, the ratio between the generated longitudinal electromotive force and applied ∇T is defined as the Seebeck coefficient. As shown in Figure 1A, a thermoelectric module based on the Seebeck effect typically consists of many pairs (128 for a 12V unit) of p-type and n-type conductors alternately arranged and connected in series. Since the Seebeck coefficient of a p-type (n-type) conductor is positive (negative), the thermopower in each element adds to the total output in the Seebeck module. This configuration is needed to achieve a practical voltage because each element only supplies millivolts but limits the use of thermoelectric generators. The efficiency of thermoelectric generators is characterized by the thermoelectric figure of merit, zT. Despite a 3-fold improvement in zT resulting from materials research over the last two decades, little progress has been made in their practical use; this is ascribed to the technological challenges in contact technology. The contacts on the hot side are subject to thermal degradation. All contacts (512 for a 12V unit) add electrical and thermal contact resistances that reduce the device efficiency to a fraction of that promised by the materials.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Deep learning of experimental electrochemistry for battery cathodes across diverse compositions

Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple performance properties and the scarcity of high-fidelity data. Here, we present a machine learning model (DRXNet) for battery informatics and demonstrate the application in the discovery and optimization of disordered rocksalt (DRX) cathode materials. We have compiled the electrochemistry data of DRX cathodes over the past 5 years, resulting in a dataset of more than 19,000 discharge voltage profiles on diverse chemistries spanning 14 different metal species. Learning from this extensive dataset, our DRXNet model can capture critical features in the cycling curves of DRX cathodes under various conditions. Our approach offers a data-driven solution to facilitate the rapid identification of novel cathode materials, accelerating the development of next-generation batteries for carbon neutralization.

25 ENERGY STORAGE↗
DOE OSTI2020

Internal short circuit and failure mechanisms of lithium-ion pouch cells under mechanical indentation abuse conditions: An experimental study

Electromechanical structural integrity and thermal stability dictate the safety performance of lithium-ion batteries. Progressive deformation and failure across microscopic and macroscopic lengths scales that are responsible for internal short circuit (ISC) in lithium-ion cells under mechanical abuse conditions remains elusive. In this study, a series of indentation tests were conducted on lithium-ion cells with different capacities up to the occurrence of ISC. The external response and internal configuration of these cells were investigated. It is discovered that cells with different capacities and state of charges exhibited different behaviors. Maximum temperature, which is often regarded as the most important parameter related to thermal runaway (TR), varied considerably due to the complicated contact configurations. X-ray computed tomography (XCT) showed that ISC was a collective result of shear band or other strain-localization modes in the electrode assembly, shear offsets in the granular coatings of electrodes, and the accompanying ductile fracture in the metal foils. We believe that the irregular strain-localization modes (kinks, cusps, and buckles), radical mismatches in mechanical properties of different layers, and geometric features of the indenter eventually lead to the tearing/puncture of cell separator at various locations. Furthermore, the results could provide useful guidance for the micromechanical modeling of lithium-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2021

Layer-structured triple-conducting electrocatalyst for water-splitting in protonic ceramic electrolysis cells: Conductivities vs. activity

Electron, proton and oxygen-triple-conducting materials are becoming the dominant steam electrode candidate to break the rate limit on the water-splitting reaction that throttles the performance of protonic ceramic electrolysis cells (PCECs). In this study, based on Pr 2 NiO 4+δ Ruddlesden-Popper phase, we manipulate these conductivities by Pr-site Ba substitution to probe the correlation of each conductivity with the kinetics of the elementary reaction steps. It is found that the proton conductivity is vital to sustain an extended active surface area for faster adsorption of reactants and desorption of products. The effect of oxygen conductivity is surprisingly found insignificant in the water-splitting reaction. On the contrary, surface oxygen removal is discovered as the most rate-limiting process. The electronic conductivity is not a direct limiting factor. However, an electron transfer process between the current collector and the electrode junction could introduce extra resistance that is perceptible at a high operating temperature range. The best water-splitting activity is obtained on a proton conductivity/oxygen surface desorption capability well-balanced sample after Ba substitution. As a result, a water-splitting reaction resistance of 0.022 Ωcm 2 , a current density of 1.96 A/cm 2 at 700 °C is achieved on Pr 1.7 Ba 0.3 NiO 4+δ , one of the best performances for PCECs.

25 ENERGY STORAGE↗
DOE OSTI2021

Unraveling the formation mechanism of NaCoPO 4 polymorphs

Phosphate compounds are one of the attractive classes of cathodes for their potential application in rechargeable Na-ion batteries (NIBs) due to their high insertion voltages and stabilities. Unlike olivine-LiMPO 4 (M = Fe, Mn, Co, Ni) cathodes, maricite-NaMPO 4 phases are electrochemically inactive due to lack of sodium diffusion channels. Interestingly, cobalt bearing compounds exhibit rich polymorphism (α-, β-, ABW- and Red-NaCoPO 4 ). However, the preparation of NaCoPO 4 single phases is challenging due to their closer enthalpies of formation. In this study, we have attempted to understand the formation mechanism of NaCoPO 4 polymorphs during solid state reaction using two different cobalt precursors (Co(OH) 2 and CoCO 3 ). The temperature dependent in-situ powder X-ray Diffraction (PXRD) studies showed the formation of β-NaCoPO 4 at a much lower temperature compared to the one reported in the literature, whilst we have discovered a new high temperature polymorph gamma-NaCoPO 4 . The choice of precursors was also found to be important for the preparation of ABW-NaCoPO 4 , i.e., the rapid decomposition of Co(OH) 2 has resulted in its formation whilst the high stability of CoCO 3 prohibited the same. The order of the formation of the NaCoPO 4 polymorphs during heating was found to be ABW→β→α →$\gamma$. During normal cooling, gamma-NaCoPO 4 transformed primarily into alpha-polymorph whilst quenching in liquid N-2 resulted in the formation of β-NaCoPO 4 The as-synthesized beta- and ABW-NaCoPO 4 phases exhibited high sodium (de)-intercalation voltages (similar to 4.2 and 4.5 V vs. Na + /Na 0 , respectively), albeit with limited reversible capacities. This study is expected to open new avenues to harvest metastable polymorphs based on other transition metals (Fe, Mn and Ni).

25 ENERGY STORAGE↗
DOE OSTI2024

Underlying mechanism of structural transformation between GaSb and GaAs response to intense electronic excitation

Ion irradiation of semiconductors has emerged as a promising approach for fabricating self-organized nanosystems with high atomic precision, despite often being accompanied by undesirable phenomena. Exploring the mechanisms underlying structural transformations is crucial for assessing nanostructure array types under complex irradiation environments. By quantitatively calculating the thermodynamically driven processes and analyzing the impact of intrinsic structural parameters, distinct structural transformations in response to intense electronic excitation are systematically investigated in gallium antimonide (GaSb) and gallium arsenide (GaAs) systems. In high-energy regimes, the nanofibers layer of GaSb exhibits intriguing structural discrepancy, characterized by partial nanofibers with coherent boundaries, interspersed nanopores accompanied by antisite defects and Ga precipitates, distinguishing to a series of discontinuous latent tracks that emerged within cylindrical trajectories in GaAs. Furthermore, significant diffusion behaviors of the nanohillocks are discovered in GaAs, with higher average roughness than GaSb, driven by the gradient stress distribution influenced by the free-surface effects. The deposition energy for melting phase formation, Gibbs free energy, and Ga diffusion coefficients contribute to the distinctive structural features, evidencing relatively stable morphological configurations and higher irradiation resistance in GaAs. Consequently, special optoelectronic properties associated with structural discrepancies facilitate the design and optimization of material functionalities by irradiation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design of an alumina forming coating for Nb-base refractory alloys

Refractory multi-principal element alloys (RMPEAs) promise to significantly enhance gas turbine engine efficiency, but their poor oxidation performance inhibits their implementation. Alumina-forming bond coat alloys can provide oxidation protection, but discovering suitable chemistries remains a challenge. We employed a design methodology that screens for alumina-formation capability using Al activity and phase constitution predictions from CalPhaD (Thermo-Calc). Alloy down-selection from approximately 7,800 alloys in the Nb-Si-Ti-Al-Hf system was conducted via analysis of calculated thermodynamic properties with number-density topology style maps. This approach is validated by creating and testing the composition Nb 12 Si 23 Ti 24 Al 36 Hf 5 , which forms protective alumina scales up to 1400 °C and resists pesting at 800 °C. Further, the alloy has an average coefficient of thermal expansion of ~10.1 ppm/K, making it well matched to Nb-based refractory alloys. The methodology will be useful for the design of coatings for RMPEAs, enabling their implementation and significant efficiency benefits sooner.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Heterogeneous catalysis: Optimal performance at a phase boundary?

Most of the industrially used heterogeneous catalysts have been discovered by trial and error, and despite decades of experience, the discovery of new catalysts continues to be extremely challenging. The drive to uncover guiding principles in catalyst design is more present than ever. We share a series of observations indicating that optimal catalysts typically function at characteristic phase boundaries (e.g., abrupt changes in adsorbate coverage, catalyst structure, etc.) accessed in the reaction conditions. The catalyst exploits the associated instability—the desire to exist in multiple states simultaneously—as a driving force for chemical transformations. In other words, phase boundaries are good places to start the catalyst search, and indeed, we should focus on at least two phases at once rather than just one. Here, we substantiate this claim with several studies that combine statistical operando modeling and experiments. Transpiring from these observations is a hitherto unrecognized vector in catalyst discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗