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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Integrated halide perovskite photoelectrochemical cells with solar-driven water-splitting efficiency of 20.8%

Abstract Achieving high solar-to-hydrogen (STH) efficiency concomitant with long-term durability using low-cost, scalable photo-absorbers is a long-standing challenge. Here we report the design and fabrication of a conductive adhesive-barrier (CAB) that translates >99% of photoelectric power to chemical reactions. The CAB enables halide perovskite-based photoelectrochemical cells with two different architectures that exhibit record STH efficiencies. The first, a co-planar photocathode-photoanode architecture, achieved an STH efficiency of 13.4% and 16.3 h to t 60 , solely limited by the hygroscopic hole transport layer in the n-i-p device. The second was formed using a monolithic stacked silicon-perovskite tandem, with a peak STH efficiency of 20.8% and 102 h of continuous operation before t 60 under AM 1.5G illumination. These advances will lead to efficient, durable, and low-cost solar-driven water-splitting technology with multifunctional barriers.

08 HYDROGEN↗
DOE OSTI2022

Waste to worth: A high-temperature water-gas shift magnetite catalyst with encapsulated core-shell structure from coal fly ash

In this paper, we demonstrate the synthesis of magnetite-based, encapsulated catalyst with a core-shell structure from coal fly ash, an industrial solid waste, and its application to industrially important high temperature water-gas shift reaction (HT-WGSR). The catalyst precursor was first synthesized through a leaching-precipitation-hydrothermal process, leading to the formation of a nanosheet-like hematite precursor consisting of Fe 3+ as primary element and minor cations including Al 3+ , Mg 2+ and other cations (e.g. Ca 2+ and Ti 4+ ). During the WGSR, the nanosheets broke into smaller particles with a core of magnetite with a diameter of ~20 nm, whereas the inherent impurity elements were activated and migrated to the outer surface forming a shell with a thickness of ~4 nm. Due to the protection of shell, the as-synthesized catalyst exhibited improved activity, thermal stability and long-term durability for HT-WGSR at 400 °C and 450 °C. Compared to the pure hematite, this catalyst exhibited much higher activity and stability, i.e., increased CO conversion and decreased deactivation rate constant, by a factor of four and three, respectively. Additionally, through a bottom-up reverse synthesis, we have confirmed that Al 3+ functioned as a textual promoter enhancing the interfacial area of the catalyst. On the other hand, the presence of minor impurity elements, in particular 2.58 wt% Mg 2+ and 0.18 wt% Ti 4+ , were found to increase the basicity, and promote the adsorption rate of CO, the redox of catalysts, and the alteration of the reaction mechanism from regenerative to associative with the formation of a strong intermediate formate. Finally, this study not only opens a new direction on the valorization of solid waste into high-value catalysts, promoting the sustainability of solid waste management, but also provides an alternative, cost-effective and scalable approach for the design and fine-tuning of encapsulated catalysts.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale

Abstract High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe. From the 63 solution-sets, our omics guided process identifies one experimentally feasible solution requiring 14 simultaneous reaction interventions. We implement a total of 14 genes knockdowns using multiplex-CRISPRi. MCS-based solution shifts production from stationary to exponential phase. We achieve 25.6 g/L, 0.22 g/l/h, and ~50% maximum theoretical yield (0.33 g indigoidine/g glucose). These phenotypes are maintained from batch to fed-batch mode, and across scales (100-ml shake flasks, 250-ml ambr®, and 2-L bioreactors).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Random heteropolymers as enzyme mimics

Despite successes in replicating the primary–secondary–tertiary structure hierarchy of protein, it remains elusive to synthetically materialize protein functions that are deeply rooted in their chemical, structural and dynamic heterogeneities. We propose that for polymers with backbone chemistries different from that of proteins, programming spatial and temporal projections of sidechains at the segmental level can be effective in replicating protein behaviours; and leveraging the rotational freedom of polymer can mitigate deficiencies in monomeric sequence specificity and achieve behaviour uniformity at the ensemble level. Here, guided by the active site analysis of about 1,300 metalloproteins, we design random heteropolymers (RHPs) as enzyme mimics based on one-pot synthesis. We introduce key monomers as the equivalents of the functional residues of protein and statistically modulate the chemical characteristics of key monomer-containing segments, such as segmental hydrophobicity. The resultant RHPs form pseudo-active sites that provide key monomers with protein-like microenvironments, co-localize substrates with catalytic or cofactor-binding sidechains and catalyse reactions such as oxidation and cyclization of citronellal with isopulegol/menthoglycol selectivity. This RHP design led to enzyme-like materials that can retain catalytic activity under non-biological conditions, are compatible with scalable processing and have expanded substrate scope, including environmentally long-lasting antibiotic tetracycline.

36 MATERIALS SCIENCE↗
DOE OSTI2024

[2 + 2] Cycloaddition Produces Divalent Organic Color-Centers with Reduced Heterogeneity in Single-Walled Carbon Nanotubes

Organic color centers (OCCs), generated by the covalent functionalization of single-walled carbon nanotubes, have been exploited for chemical sensing, bioimaging, and quantum technologies. However, monovalent OCCs can assume at least 6 different bonding configurations on the sp 2 carbon lattice of a chiral nanotube, resulting in heterogeneous OCC photoluminescence emissions. Herein, we show that a heat-activated [2 + 2] cycloaddition reaction enables the synthesis of divalent OCCs with a reduced number of atomic bonding configurations. The chemistry occurs by simply mixing enophile molecules (e.g., methylmaleimide, maleic anhydride, and 4-cyclopentene-1,3-dione) with an ethylene glycol suspension of SWCNTs at elevated temperature (70–140 °C). Unlike monovalent OCC chemistries, we observe just three OCC emission peaks that can be assigned to the three possible bonding configurations of the divalent OCCs based on density functional theory calculations. Notably, these OCC photoluminescence peaks can be controlled by temperature to decrease the emission heterogeneity even further. Furthermore, this divalent chemistry provides a scalable way to synthesize OCCs with tightly controlled emissions for emerging applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning

Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2020

A scalable crosslinked fiberglass-aerogel thermal insulation composite

Ceramic aerogels are attractive for thermal insulation due to its lightweight and low thermal conductivity, while it is indispensable to address the obstacle of its brittleness nature and large-scale manufacturing for building efficiency applications. The economical manufacturing of large-scale elastic thermal insulation aerogels has remained challenging. Herein, we report a universal manufacturing of the fiberglass reinforced aerogel composites where the architectured three-dimensional fiber networks with the cross-linked silica aerogel exhibit superinsulation and mechanical elasticity. These remarkable performances are obtained through in-situ cross-linking reaction between molecular assembly induced aerogel and fiberglass under ambient pressure drying environment, in which the interfacial interactions are verified from its infrared spectra. The resulting ultralight aerogel composite sheet exhibits a density of 0.1 g cm -3 , large strain recovery (>50%), and low thermal conductivity (0.0253 W m –1 K –1 ). Here, the thermal insulation aerogel composites shed light on the super-elastic aerogel manufacturing with scalability for energy saving building applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Reaction Optimization for Enzymatic Deconstruction of Industrially Relevant Nylon Composites

Plastics such as polyamides (PAs) possess unique physicochemical properties that make them indispensable in modern society. However, their energy‐intensive production and challenging end‐of‐life management highlight the urgent need for efficient recycling or remanufacturing solutions. Enzymatic depolymerization offers a promising route toward circular recycling, yet remains constrained by limited enzyme characterization, lack of validation under industrially relevant conditions and substrates, and overall performance. Here, we optimized the reaction conditions for three recently discovered nylon‐degrading enzymes. One of them, Nyl12, achieved product titers with PA6 and PA66 that exceed previously reported values, without enzyme engineering or substrate pretreatment. We further demonstrated the scalability of the process and its application to complex PA‐based materials used in microelectronic components. Analysis of substrate features, including surface area and particle size, revealed key parameters governing enzymatic activity and provided a framework for future pretreatment and process optimization efforts. In combination, these efforts provide a new benchmark for enzymatic nylon recycling.

nylon↗
DOE OSTI2023

Enhanced microbial production of protocatechuate from engineered sorghum using an integrated feedstock-to-product conversion technology

Building a stronger bioeconomy requires production capabilities that are largely generated through microbial genetic engineering. Plant feedstocks can additionally be genetically engineered to generate desirable feedstock traits and provide precursors for direct microbial conversion into desired products. The oleaginous yeast Rhodosporidium toruloides is a promising organism for this type of conversion as it can grow on a wide range of deconstructed biomass and consume a variety of carbon sources. Here, we leveraged R. toruloides native p-coumaric acid consumption pathway to accumulate protocatechuate (PCA) from 4-hydroxybenzoate (4HBA) released from a sorghum feedstock line genetically engineered to overproduce 4HBA. We did so by generating and evaluating an R. toruloides strain that accumulates PCA, RSΔ12623. We then show that at two scales a cholinium lysinate pretreatment with enzymatic saccharification successfully extracts 95% of the 4HBA from the engineered sorghum biomass while producing deconstructed lignin that can be more efficiently depolymerized in a subsequent thermochemical reaction. We also demonstrate that strain RSΔ12623 can convert more than 95% of 4HBA to PCA while consuming >95% of the glucose and >80% of the xylose present in sorghum hydrolysates. Finally, to evaluate the scalability of such fermentations, we conducted the conversion of 4HBA to PCA in a 2 L bioreactor under controlled conditions. Importantly, this work demonstrates the potential of purposefully producing aromatic precursors in planta that can be liberated during biomass deconstruction for direct microbial conversion to desirable bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Fission with Exotic Nuclei (Full Technical Report)

Despite its importance for stockpile stewardship or nuclear forensics, data on fission is fragmentary: most experiments have only been performed on stable actinide nuclei and are often incomplete, and theoretical simulations often contain many parameters hard to constrain, which results in large uncertainties. Consequently, nuclear libraries have large gaps for important isotopes. The goal of this project was to prepare to take advantage of the unprecedented yields of radioactive isotopes at the upcoming DOE Facility for Rare Ion Beams and to leverage recent progress in the field of machine learning to develop a comprehensive program of fission studies that could address some of the most pressing problems in nuclear fission over the next several decades. Our project leveraged synergies between experimental nuclear physics, nuclear theory, and data science expertise at LLNL. On the experimental front, our main objective was to develop in-house expertise for inverse kinematics reactions with relativistic beams as well as to field and test new detectors to perform correlated measurements of fission properties. On the theoretical side, the objective was to develop a novel, high-fidelity and scalable approach of fissionfragment calculations based on emulating computationally expensive, quantum-mechanical calculations of nuclear properties with deep neural networks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Development of Scalable Reactive Transport Framework for PFAS

Research on PFAS chemicals is extensive and covers all aspects, including analytical quantification, determination of properties, toxicology, ex situ treatment, and in situ remediation. PFAS chemicals are very stable and thus persistent/recalcitrant in the environment. Although there are many unknowns about PFAS chemicals, degradation pathways, reaction rates, etc., many different sorption, oxidation, reduction, biological, and innovative treatment approaches are being developed. Sorption with activated carbon is currently the only fully available in situ treatment technology for PFAS-impacted groundwater. Given the wide array of PFAS chemicals and transformation products, remediation may need multi-step treatment trains to fully address the PFAS contamination. The work here provides kinetic reaction modules that represent an initial cut at functionality representing PFAS migration and reaction in groundwater aquifer flow and transport models. One reaction kinetics module provides a method to model kinetically limited adsorption using a mass transfer model. The second reaction module represents biological transformation of 8:2 FTOH and daughter species, illustrating how a complex reaction pathway network can be represented. Both reaction modules allow for spatially variable parameter values so that a variety of remediation approaches (e.g., a PRB or volumetric treatment or variations in geochemical conditions) can be simulated. The intent with these PFAS reaction modules is to provide tools for practitioners to aid in the selection, design, and assessment of potential in situ PFAS remediation strategies. It is anticipated that, as PFAS remediation technologies and scientific understanding advances, these modules would be refined or replaced to match new knowledge.

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

Robust Oxygen‐Vacancy‐Engineered Co(OH) 2 /Cu Heterostructures Boost Nitrate Electroreduction to Ammonia beyond 2 A cm −2

Electrocatalytic nitrate reduction reaction (NO 3 RR) presents a sustainable paradigm for green NH 3 synthesis and NO 3 − wastewater valorization. However, overcoming sluggish NO 3 RR kinetics under industrial-current operation persists as a critical challenge. Herein, robust oxygen vacancy-enriched heterostructures (O v -Co(OH) 2 /Cu) are engineered through in situ electrochemical reconstruction. By coupling Cu-mediated NO 3 − -to-NO 2 − conversion with O v -Co(OH) 2 -accelerated NO 2 − -to-NH 3 transformation, this heterostructured system delivers an unprecedented NH 3 yield rate of 167.8 mg h −1 cm −2 and 97.7% Faradaic efficiency at >2 A cm −2 , while maintaining exceptional current tolerance over 25 h. Operando spectroscopic characterizations and theoretical calculations reveal that the introduction of O v in Co(OH) 2 synergistically accelerates water dissociation to ensure continuous hydrogen supply and optimizes *NOOH adsorption, reducing the energy barrier for the rate-limiting step (*NO 2 to *NOOH). To demonstrate practical viability, a membrane-electrode-assembly electrolyzer integrating NO 3 RR with glycerol oxidation reaction achieves highly effective co-production of NH 3 and formate alongside wastewater treatment. In conclusion, this work offers new insights into the rational design of electrocatalysts through in situ reconstruction-induced vacancy engineering for scalable and practical NO 3 RR applications.

ammonia synthesis↗
DOE OSTI2025

Large area transparent refractory aerogels with high solar thermal performance

Application of transparent silica aerogels in low-temperature solar thermal systems has led to major improvements in performance. In high temperature concentrating solar thermal (CST) systems, aerogels have yet to demonstrate the necessary scalability, durability, and performance to support their widespread deployment. Here, large-area transparent refractory aerogel tiles are synthesized and shown to achieve a record-high receiver figure-of-merit (FOM) at high temperatures. The work leverages a scaled-up process for sol–gel synthesis to control the density of the aerogels for improved solar transmittance and adapts a previous atomic layer deposition (ALD) technique with the aid of predictive reaction-transport modeling. After aging for 10 days at 700 °C, the large-area tiles exhibit a solar-weighted transmittance of 95.6 % and a thermal emittance of 0.31, corresponding to a FOM of 80 % at 100 suns and 700 °C. The observed sintering rates at 700 °C are comparably low to earlier one-inch aerogels, suggesting long-term stability under relevant operating conditions. Furthermore, the study indicates that refractory aerogels are scalable materials for efficient photothermal conversion at high temperatures.

Aerogels↗
DOE OSTI2026

Translating Fundamental Insights into Ag-Based Bimetallic Electrocatalysts to Anion-Exchange Membrane Fuel Cells

To address challenges of high costs and scalability for fuel cells, it is essential to develop af-fordable and earth-abundant materials that are Pt-group-metal (PGM)-free. Recent advance-ments in PGM-free electrocatalysis for the oxygen reduction reaction (ORR) in alkaline media show that high catalyst loadings are needed to achieve high reaction rates; however, there are associated mass transport limitations. To address this issue, we develop low-loading ionomer-less Ag-bimetallic thin films by alloying with 3d block elements or Sn. We bridge knowledge from fundamental rotating disk electrode (RDE) studies to gas-diffusion cathodes in high-temperature anion-exchange membrane fuel cells (HT-AEMFCs), resulting in high-activity ORR catalysis and peak power densities up to 1.2 W cm-² geo for the Ag-Sn and Ag-Co alloys. Here, experimental post-characterization and theoretical calculations reveal small Co or Sn oxide nano-islands on Ag as likely active sites enhancing ORR activity, ultimately offering these low-loading PGM-free ORR materials as a viable path towards sustainable energy conversion.

Catalysts↗
DOE OSTI2025

Operando Neutron Imaging of Lithium Flux and Gradient Cathode Design for Enhanced Kinetics in High‐Loading All‐Solid‐State Li─S Batteries

All-solid-state Li–sulfur batteries (ASSLSBs) are considered promising candidates for next-generation energy storage owing to their inherent safety, high energy density, and abundant sulfur resources. However, slow redox kinetics greatly limit sulfur utilization during solid-solid sulfur reactions, leading to significant challenges to achieve efficient performance in high-mass-loading ASSLSBs. Here, operando neutron image is employed to directly visualize, for the first time, that sluggish Li + transport kinetics and the uneven distribution of Li + during cathodic reactions are critical factors limiting sulfur conversion. To address this issue, gradient cathode architectures comprising three and five layers are designed, in which catholyte concentrations are strategically varied to optimize Li-ion flux and enhance ionic conductivity of the whole composite cathode electrode. Operando neutron imaging distinctly visualizes and confirms that three-layer gradient approach significantly enhances Li-ion mobility, resulting in more uniform redox reactions and greatly improved sulfur utilization compared to traditional non-gradient structures. Consequently, the three-layer gradient cathode achieves superior rate performance and reduced electrode polarization at high sulfur mass loadings of 4.5 and 6.0 mg cm −2 . Furthermore, the applicability and scalability of this design are demonstrated in a five-layer gradient cathode architecture, achieving an impressive discharge specific capacity increase from 656 mAh g −1 (three-layer gradient) to 1232 mAh g −1 at 1/20 C for ultra-high sulfur loading of 7.5 mg cm −2 . In conclusion, this innovative gradient cathode design offers substantial advancements in understanding and overcoming Li-ion transport limitations, paving the way toward practical, high-energy-density ASSLSBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Standardized excitable elements for scalable engineering of far-from-equilibrium chemical networks

Engineered far-from-equilibrium synthetic chemical networks that pulse or switch states in response to environmental signals could precisely regulate the kinetics of chemical synthesis or self-assembly. Currently, such networks must be extensively tuned to compensate for the different activities of and unintended reactions between a network’s various chemical components. Modular elements with standardized performance could be used to rapidly construct networks with designed functions. Here we develop standardized excitable chemical regulatory elements, termed genelets, and use them to construct complex in vitro transcriptional networks. We develop a protocol for identifying >15 interchangeable genelet elements with uniform performance and minimal crosstalk. Furthermore, these elements can be combined to engineer feedforward and feedback modules whose dynamics match those predicted by a simple kinetic model. Modules can then be rationally integrated and organized into networks that produce tunable temporal pulses and act as multistate switchable memories. Standardized genelet elements, and the workflow to identify more, should make engineering complex far-from-equilibrium chemical dynamics routine.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗