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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Discovering and Designing a Chimeric Hyperthermophilic Chitinase for Crystalline Chitin Degradation

Chitin is one of the most abundant renewable biopolymers on earth. However, it is highly crystalline and recalcitrant to degrade. Here, we report a hyperthermophilic chitinase (ActChi) to directly hydrolyze crystalline chitin at its optimal temperature of 80 °C. It contains a malectin domain, a fibronectin type-III (Fn3) domain, and a catalytic domain (CD chi ). Both Fn3 and malectin have the function of chitin binding domain (ChBD) to increase the activity. Fn3 also significantly increases thermostability, but malectin decreases it. To enhance both activity and thermostability, here we introduced a heterogeneous and hyperthermophilic ChBD at the N-terminus of CD chi to obtain ChBD-CD chi . The activity of this hybrid enzyme is 201 U/μmol for crystalline chitin, which has increased 400% compared with that of ActChi. In addition, ChBD-CD chi can continuously degrade crystalline chitin for more than 4 days at 70 °C to increase the overall hydrolysis rate. The strategy is a good example of green sustainable degradation for crystalline biopolymer in nature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Discovering the Multisectoral Impacts of Global Energy Sector Outcomes Through Multiple Ensemble Aggregation Measures

Understanding complex human-Earth system interactions often involves analyzing large scenario ensembles that encompass a wide range of plausible futures. These ensembles often require aggregation to summarize information based on specific criteria or conditions. However, previous research using global change scenario ensembles has largely overlooked how the choice of aggregation method influences the interpretation of results. To address this gap, we leverage a large ensemble data set designed to capture broad energy system dynamics generated using the Global Change Analysis Model. We first explore how energy-related uncertainties are propagated to both global and regional water-energy-food sectors. We then conduct a rank correlation analysis across seven ensemble aggregation measures and demonstrate the need to consider multiple measures in global change scenarios. Our results suggest that global water and food sector outcomes in the 21st century vary widely depending on different scenario assumptions. The global energy productivity is projected to improve by the end of the century across all scenarios. Moreover, regions facing water scarcity challenges in 2100 do not always overlap with those facing extreme energy and food sector outcomes. Although rank correlations across seven aggregation measures are relatively stable across sectors, we identify cases where relying on a single measure leads to losing critical information in the full ensemble. Reliance on a single aggregation measure can distort the interpretation of global change scenario outcomes. Instead, adopting multiple ensemble aggregation measures provides a more holistic understanding of global change scenario ensembles.

Kim, Gijoo↗
DOE OSTI2026

Corundum Discovered by SuperCam and the Perseverance Rover at Jezero Crater, Mars

Minerals provide clues to the type of geologic environments in which they form. The primary types of minerals that have been identified on Mars indicate a history dominated by volcanism followed by interaction with water. However, other minerals are sometimes found. Here we present results from the SuperCam instrument on the Perseverance rover in which the mineral corundum (α-Al2O3) has been identified using a technique called time-resolved luminescence spectroscopy. Corundum has a unique light-emitting (luminescence) feature based on two well-known peaks as well as the time it takes for this light to fade after being excited by a laser, which is referred to as the lifetime. Corundum forms in specific environments that are enriched in aluminum and depleted in silicon and have been subjected to high temperature and pressure. Such places include deep subsurface magmas or shallower locations that have been exposed to high temperature through tectonic processes or meteorite impacts. Given their small size, association with a mineral called plagioclase, and location on the heavily impacted crater rim, we propose that these corundum minerals formed through impact processes.

58 GEOSCIENCES↗
DOE OSTI2022

Superconductivity above 200 K discovered in superhydrides of calcium

Searching for superconductivity with T c near room temperature is of great interest both for fundamental science & many potential applications. Here we report the experimental discovery of superconductivity with maximum critical temperature (T c ) above 210 K in calcium superhydrides, the new alkali earth hydrides experimentally showing superconductivity above 200 K in addition to sulfur hydride & rare-earth hydride system. The materials are synthesized at the synergetic conditions of 160~190 GPa and ~2000 K using diamond anvil cell combined with in-situ laser heating technique. The superconductivity was studied through in-situ high pressure electric conductance measurements in an applied magnetic field for the sample quenched from high temperature while maintained at high pressures. The upper critical field Hc(0) was estimated to be ~268 T while the GL coherent length is ~11 Å. The in-situ synchrotron X-ray diffraction measurements suggest that the synthesized calcium hydrides are primarily composed of CaH 6 while there may also exist other calcium hydrides with different hydrogen contents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A substitutional quantum defect in WS2 discovered by high-throughput computational screening and fabricated by site-selective STM manipulation

Abstract Point defects in two-dimensional materials are of key interest for quantum information science. However, the parameter space of possible defects is immense, making the identification of high-performance quantum defects very challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS 2 , which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur ( $${\rm{Co}}_{{{{{{{{\rm{S}}}}}}}}}^{0}$$ Co S 0 ) and fabricate it with scanning tunneling microscopy (STM). The $${\rm{Co}}_{{{{{{{{\rm{S}}}}}}}}}^{0}$$ Co S 0 electronic structure measured by STM agrees with first principles and showcases an attractive quantum defect. Our work shows how HT computational screening and nanoscale synthesis routes can be combined to design promising quantum defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Superlative mechanical energy absorbing efficiency discovered through self-driving lab-human partnership

Energy absorbing efficiency is a key determinant of a structure’s ability to provide mechanical protection and is defined by the amount of energy that can be absorbed prior to stresses increasing to a level that damages the system to be protected. Here, we explore the energy absorbing efficiency of additively manufactured polymer structures by using a self-driving lab (SDL) to perform >25,000 physical experiments on generalized cylindrical shells. We use a human-SDL collaborative approach where experiments are selected from over trillions of candidates in an 11-dimensional parameter space using Bayesian optimization and then automatically performed while the human team monitors progress to periodically modify aspects of the system. The result of this human-SDL campaign is the discovery of a structure with a 75.2% energy absorbing efficiency and a library of experimental data that reveals transferable principles for designing tough structures.

42 ENGINEERING↗
DOE OSTI2025

Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas

Understanding complex physical systems often requires integrating data from multiple diagnostics, each with limited resolution or coverage. We present a machine learning framework that reconstructs synthetic high-temporal-resolution data for a target diagnostic using information from other diagnostics, without direct target measurements during the inference. This multimodal super-resolution technique improves diagnostic robustness and enables monitoring even in case of measurement failures or degradation. Applied to fusion plasmas, our method targets edge-localized modes (ELMs), which can damage plasma-facing materials. By reconstructing super-resolution Thomson Scattering data from complementary diagnostics, we uncover fine-scale plasma dynamics and validate the role of resonant magnetic perturbations (RMPs) in ELM suppression through magnetic island formation. The approach provides new observation supporting the plasma profile flattening due to these islands. Our results demonstrate the framework’s ability to generate high-fidelity synthetic diagnostics, offering a powerful tool for ELM control development in future reactors like ITER. The approach is broadly transferable to other domains facing sparse, incomplete, or degraded diagnostic data, opening new avenues for discovery.

Jalalvand, Azarakhsh [Princeton Univ., NJ (United ↗
DOE OSTI2022

Discovering equations that govern experimental materials stability under environmental stress using scientific machine learning

Abstract While machine learning (ML) in experimental research has demonstrated impressive predictive capabilities, extracting fungible knowledge representations from experimental data remains an elusive task. In this manuscript, we use ML to infer the underlying differential equation (DE) from experimental data of degrading organic-inorganic methylammonium lead iodide (MAPI) perovskite thin films under environmental stressors (elevated temperature, humidity, and light). Using a sparse regression algorithm, we find that the underlying DE governing MAPI degradation across a broad temperature range of 35 to 85 °C is described minimally by a second-order polynomial. This DE corresponds to the Verhulst logistic function, which describes reaction kinetics analogous to self-propagating reactions. We examine the robustness of our conclusions to experimental variance and Gaussian noise and describe the experimental limits within which this methodology can be applied. Our study highlights the promise and challenges associated with ML-aided scientific discovery by demonstrating its application in experimental chemical and materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chemical screening by time-resolved X-ray scattering to discover allosteric probes

Abstract Drug discovery relies on efficient identification of small-molecule leads and their interactions with macromolecular targets. However, understanding how chemotypes impact mechanistically important conformational states often remains secondary among high-throughput discovery methods. Here, we present a conformational discovery pipeline integrating time-resolved, high-throughput small-angle X-ray scattering (TR-HT-SAXS) and classic fragment screening applied to allosteric states of the mitochondrial import oxidoreductase apoptosis-inducing factor (AIF). By monitoring oxidized and X-ray-reduced AIF states, TR-HT-SAXS leverages structure and kinetics to generate a multidimensional screening dataset that identifies fragment chemotypes allosterically stimulating AIF dimerization. Fragment-induced dimerization rates, quantified with time-resolved SAXS similarity analysis ( k VR ), capture structure–activity relationships (SAR) across the top-ranked 4-aminoquinoline chemotype. Crystallized AIF–aminoquinoline complexes validate TR-SAXS-guided SAR, supporting this conformational chemotype for optimization. AIF–aminoquinoline structures and mutational analysis reveal active site F482 as an underappreciated allosteric stabilizer of AIF dimerization. This conformational discovery pipeline illustrates TR-HT-SAXS as an effective technology for targeting chemical leads to important macromolecular states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Discovering tungsten-based composites as plasma facing materials for future high-duty cycle nuclear fusion reactors

Abstract Despite of excellent thermal properties and high sputtering resistance, pure tungsten cannot fully satisfy the requirements for plasma facing materials in future high-duty cycle nuclear fusion reactions due to the coupled extreme environments, including the high thermal loads, plasma exposure, and radiation damage. Here, we demonstrated that tungsten-based composite materials fabricated using spark-plasma sintering (SPS) present promising solutions to these challenges. Through the examination of two model systems, i.e., tungsten-zirconium composite for producing porous tungsten near the surface and dispersoid-strengthened tungsten, we discussed both the strengths and limitations of the SPS-fabricated materials. Our findings point towards the need for future studies aimed at optimizing the SPS process to achieve desired microstructures and effective control of oxygen impurities in the tungsten-based composite materials.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Using genetic algorithms to discover novel ground-state triplet conjugated polymers

Stable ground-state triplet π-conjugated copolymers have many interesting electronic and optoelectronic properties. However, the large number of potential monomer combinations makes it impractical to synthesize or even just use density functional theory (DFT) to calculate their triplet ground-state stability. Furthermore, we present a genetic algorithm implementation that uses the semi-empirical GFN2-xTB to find ground-state triplet polymer candidates. We find more than 1400 polymer candidates with a triplet ground-state stability of up to 4 eV versus the singlet. Additionally, we explore the properties of the monomers of those candidates in order to understand the design rules which promote the formation of a stable ground-state triplet in π-conjugated polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Application of machine learning to discover new intermetallic catalysts for the hydrogen evolution and the oxygen reduction reactions

The adsorption energies for hydrogen, oxygen, and hydroxyl were calculated by means of density functional theory on the lowest energy surface of 24 pure metals and 332 binary intermetallic compounds with stoichiometries AB, A 2 B, and A 3 B taking into account the effect of biaxial elastic strains. This information was used to train two random forest regression models, one for the hydrogen adsorption and another for the oxygen and hydroxyl adsorption, based on 9 descriptors that characterized the geometrical and chemical features of the adsorption site as well as the applied strain. All the descriptors for each compound in the models could be obtained from physico-chemical databases. The random forest models were used to predict the adsorption energy for hydrogen, oxygen, and hydroxyl of ≈2700 binary intermetallic compounds with stoichiometries AB, A 2 B, and A 3 B made of metallic elements, excluding those that were environmentally hazardous, radioactive, or toxic. This information was used to search for potential good catalysts for the HER and ORR from the criteria that their adsorption energy for H and O/OH, respectively, should be close to that of Pt. Further, this investigation shows that the suitably trained machine learning models can predict adsorption energies with an accuracy not far away from density functional theory calculations with minimum computational cost from descriptors that are readily available in physico-chemical databases for any compound. Moreover, the strategy presented in this paper can be easily extended to other compounds and catalytic reactions, and is expected to foster the use of ML methods in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Leveraging the redox activities of cerium and dibenzotetrathiafulvalene to discover a photo-responsive magnetic material

Stimuli-responsive changes in lanthanide-based materials are a promising research direction. In this study, [DBTTF] 4 [Ce 2 Cl 10 ] DBTTF = dibenzotetrathiafulvalene (1) was synthesized by a light-induced crystallization, where photo-oxidation of DBTTF enables formation of the cerium dimer [Ce 2 Cl 10 ] 4− . Intermolecular interactions between the stacked organic units of the crystal result in charge transfer bands in the visible-NIR (near-infrared) region, evident in the solid-state absorption spectrum upon comparison with the solution spectrum. The assignments of the sublattice oxidation states were made with single-crystal X-ray diffraction (SC-XRD) structural characterization, Raman spectroscopy, X-ray absorption spectroscopy, and magnetometry. Continuous 532 nm laser irradiation of the microcrystalline solid modulates the redox states in 1, leading to ∼40% reduction in the observed magnetization at 2 K. Density functional theory PBE+U/HSE06 band structure calculations predict Mott insulating behavior in 1, with a bandgap of 0.54/0.81 eV, and further support the conjecture that the observed photo-induced change in magnetization results from electron transfer from the [Ce 2 Cl 10 ] 4− anions to the π-stacked [DBTTF] 2 2+ organic dimer subunits. An enhancement in conductivity is similarly observed upon 532 nm irradiation, determined by single-crystal transport measurements. The findings reveal that photo-responsive lanthanide-based materials can be achieved by integration of redox-active organic moieties with redox-active lanthanide cations for the realization of switchable, photo-magnetic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗