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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CO 2 Hydrogenation to Methanol over Inverse ZrO 2 /Cu(111) Catalysts: The Fate of Methoxy under Dry and Wet Conditions

Understanding the surface chemistry of CH 3 O species is essential for the production of methanol by CO 2 hydrogenation over Cu-based heterogeneous catalysts, as it facilitates the rational design of more efficient conversion processes. Recent research has identified inverse ZrO 2 /Cu catalysts as highly active and selective systems for the transformation of CO 2 to methanol with a performance that can be better than that of commercial Cu/ZnO catalysts. Here, we employed synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS) and calculations based on density functional theory (DFT) to understand the fate of CH 3 O groups under dry and wet environments. AP-XPS spectra revealed that under CO 2 hydrogenation conditions, formate and methoxy are two key intermediates to produce methanol. Furthermore, there are three different types of reactive sites on the surface: One is active for methoxy adsorption, which is stable and responsible for the methanol synthesis; Another one transforms CO 2 into CO; and a third one is active for CO 2 and methoxy dissociation, leading to C and methane formation. The theoretical calculations indicate that CH 3 OH readily dissociates to CH 3 O species following a highly exothermic (ΔE = -20.99 kcal/mol) and barrierless process. The water produced by the reverse water-gas shift reaction (CO 2 + H 2 → H 2 O + CO) can prevent the decomposition of CH 3 O species. We discovered that by introducing a tiny amount of water vapor (2 × 10 -6 Torr) into the reaction chamber, the energy barrier for the reaction CH 3 O(ads) + H(ads) → CH 3 OH(gas) is dramatically reduced. AP-XPS and computational modelling showed that water is quite capable of extracting adsorbed methoxy to form gaseous methanol. With this in mind, one could boost the methanol selectivity by adding appropriate amounts of water or steam, which is an inexpensive and feasible solution for industrial operations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Dynamic Evolution of 2D Layers within Perovskite Nanocrystals via Salt Pair Extraction and Reinsertion

Metal halide perovskite (MHP) semiconductors exhibit unprecedented optoelectronic properties coupled with low formation energies that enable scalable, cost-efficient solution processing. The low formation energies additionally facilitate dynamic transformation of the chemical composition and crystal structure of the MHP material. In this work, we show that CsBr salt is selectively extracted from CsPbBr 3 nanocrystals (NCs) to yield PbBr 2 NCs. The PbBr 2 NCs are then exposed to different glacial acetic acid ABr salt solutions to generate a variety of emissive compounds with the generic structure A' 2 A n-1 Pb n Br 3 n-1 X' 2 , where A = cesium (Cs + ), methylammonium (MA + ), formamidinium (FA+); A' = A or H+; X' = Br- or acetate (CH3COO-); and n is the number of lead halide layers, where n = 1, 2, 3, ...8. We systematically vary the ratios of PbBr 2 /ABr/CH 3 COOH and show that certain ratios result in isolable single-phase APbBr3 NCs - an effective A-site cation exchange from the parent CsPbBr 3 NCs. Importantly, time-resolved photoluminescence (PL) spectroscopy shows the dynamic evolution of many additional species as evidenced by blue-shifted emission peaks from 2.85-2.49 eV for MA + -based structures. We assign these species to n = 1, 2, 3, 4, and 5 quasi-two-dimensional network (2DN) sheets, in which CH 3 COO- anions and Br- anions compete for the c-axis X' sites separating haloplumbate(II) layers within the A' 2 A n-1 Pb n Br 3n-1 X' 2 NCs. Finally, we demonstrate the degree of CH 3 COO- incorporation, and thus the 2DN layer thickness and PL energy, is controlled in the early reaction times by kinetic factors. After a longer time (3 h), thermodynamic forces dictated by Le Chatelier's principle tune the structure in A' 2 A n-1 Pb n Br 3n-1 X' 2 NCs from exclusively n = 1 to n = 8 depending on the PbBr 2 /ABr/CH 3 COOH ratio.

14 SOLAR ENERGY↗
DOE OSTI2021

A Preprocessing Tool for Enhanced Ion Mobility–Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility–mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Further, other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Scalable Frontal Oligomerization: Insights from Advanced Mass Analysis

Linear oligomers of dicyclopentadiene (DCPD) are reactive precursors for thermoplastic and thermoset materials. Unlike the foul-smelling parent monomer, oligomers composed of DCPD are odorless. With appropriate modification of the end-group or backbone chemistry, telechelic DCPD oligomers have potential utility as cross-linkers and as macromonomer precursors for block and graft copolymers. Most existing methods to produce oligo-DCPD, however, require solvent, are relatively slow, and necessitate air-free techniques. Here we show that frontal ring-opening metathesis oligomerization (FROMO) of neat DCPD and other norbornene derivatives rapidly generates hundreds of grams of material in minutes with catalyst loadings of 0.5 mM. This energy-efficient catalytic process utilizes the heat generated by the reaction to self-propagate oligomerization throughout the liquid monomer. FROMO employs a terminal olefin (e.g., styrene) in which a cross-metathesis reaction (i.e., chain transfer) competes with ring-opening metathesis (i.e., propagation). Kendrick mass analysis enables rapid identification and assignment of all the chain-end types present and quantifies the degree of branching resulting from the infrequent cyclopentene ring-opening reaction. This analytical technique also detects oligomer species derived from trace impurities in the monomer or chain-transfer agent that are otherwise difficult to observe with other characterization methods. Here, the obtained oligomers possess well-defined chain-ends and molecular weight distributions.

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

A Perspective on Multiscale Modeling of Explicit Solvation-Enabled Simulations of Catalysis at Liquid–Solid Interfaces

Catalysis at liquid-solid interfaces is profoundly influenced by the interfacial solvent structure, which affects catalytic activity, selectivity, and reaction pathways. This perspective discusses state-of-the-art multiscale modeling methods that integrate quantum mechanics and molecular mechanics approaches to apply explicit solvent molecules to capture these interfacial phenomena. Specifically, the construction of multiscale models, the importance of capturing the interfacial solvent structure, and the computational strategies used to achieve this are explored, and the challenges in balancing chemical accuracy with computational expense are highlighted. Additionally, this perspective addresses the limitations of current methods. Opportunities for integrating machine learning are proposed. Here, by advancing the efficiency and user friendliness of multiscale modeling, it is argued that deeper insights into heterogeneous catalysis in liquid phases can be provided, which will ultimately contribute to the development of more efficient catalytic processes.

Ab initio molecular dynamics↗
DOE OSTI2025

Machine Learning-Guided Identification of PET Hydrolases from Natural Diversity

The enzymatic depolymerization of poly(ethylene terephthalate) (PET) is emerging as a leading chemical recycling technology for waste polyester. As part of this endeavor, new candidate enzymes identified from natural diversity can serve as useful starting points for enzyme evolution and engineering. In this study, we improved upon HMM searches by applying an iterative machine learning strategy to identify 400 putative PET-degrading enzymes (PET hydrolases) from naturally occurring homologs. Using high-throughput (HTP) experimental techniques, we successfully expressed and purified >200 enzyme candidates and assayed them for PET hydrolysis activity as a function of pH, temperature, and substrate crystallinity. From this library, we discovered 91 previously unknown PET hydrolases, 35 of which retain activity at pH 4.5 on crystalline material, which are conditions relevant to developing more efficient commercial processes. Notably, four enzymes showed equal to or higher activity than LCC-ICCG, a benchmark PET hydrolase, at this challenging condition in our screening assay, and 11 of which have pH optima <7. Using these data, we identified regions of PETases statistically correlated to activity at lower pH. We additionally investigated the effect of condition-specific activity data on trained machine learning predictors and found a precision (putative hit rate) improvement of up to 30% compared to a Hidden Markov Model alone. Our findings show that by pointing enzyme discovery toward conditions of interest with multiple rounds of experimental and machine learning, we can discover large sets of active enzymes and explore factors associated with activity at those conditions.

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

Impact of Surface Enhanced Raman Spectroscopy in Catalysis

Catalysis stands as an indispensable cornerstone of modern society, underpinning the production of over 80% of manufactured goods and driving over 90% of industrial chemical processes. As the demand for more efficient and sustainable processes grows, better catalysts are needed. Understanding the working principles of catalysts is key, and over the last 50 years, surface-enhanced Raman Spectroscopy (SERS) has become essential. Discovered in 1974, SERS has evolved into a mature and powerful analytical tool, transforming the way in which we detect molecules across disciplines. In catalysis, SERS has enabled insights into dynamic surface phenomena, facilitating the monitoring of the catalyst structure, adsorbate interactions, and reaction kinetics at very high spatial and temporal resolutions. This review explores the achievements as well as the future potential of SERS in the field of catalysis and energy conversion, thereby highlighting its role in advancing these critical areas of research.

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

Thermoplastic Polymer from Lignin: Creating an Extended Polyamide Network through Reactive Kraft Lignin Derivatives

Thermoplastic polymers have many desirable properties for consumer applications and are complemented by efficient thermal processing techniques, reducing the cost of manufacturing. Lignin exists as an immense biobased carbon source but has largely been researched for its use in thermoset materials due to its own cross-linked, polyfunctional nature. In this study, a new reaction design is employed to create a thermoplastic polyamide network incorporating lignin that is tested to be 99% biobased carbon by radiocarbon analysis. Chemical analysis reveals the nature of lignin incorporation based on chain extension and cross-linking models. The thermal and rheological properties of the new polymers are thoroughly investigated to demonstrate the higher melt-strength capability of the lignin-based polymers facilitating their use in modern processing equipment. This analysis results in finding an optimal lignin loading ratio in the polymer composition reflected by improved tensile strength and stiffness. The results point to a promising polymer design for applying industrial kraft lignin in high-value thermoplastic polymer applications.

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

Mine Tailings Valorization by Electrochemically Stimulated Mineralization from Mildly Acidic Conditions

This study presents a high-efficiency electrochemical process for the mineralization of calcium carbonate (CaCO 3 ) from mildly acidic mine tailing supernatant water. Electrochemical pH control was used to promote carbonate speciation and precipitation from CO 2 -saturated solutions, achieving >1 mol CaCO 3 precipitated per mol e - at applied potentials between -1.4 and -1.6 V vs Ag/AgCl. Product morphology and polymorph selectivity were tunable via applied potential, yielding calcite and vaterite phases. Experiments using real mine tailings water confirmed selective calcite precipitation, despite the presence of sulfate and other trace elements. These results highlight a viable route for coupling CO 2 utilization with mine tailings valorization.

36 MATERIALS SCIENCE↗
DOE OSTI2012

HIV-1 Protease with 20 Mutations Exhibits Extreme Resistance to Clinical Inhibitors through Coordinated Structural Rearrangements

The escape mutant of HIV-1 protease (PR) containing 20 mutations (PR20) undergoes efficient polyprotein processing even in the presence of clinical protease inhibitors (PIs). PR20 shows >3 orders of magnitude decreased affinity for PIs darunavir (DRV) and saquinavir (SQV) relative to PR. Crystal structures of PR20 crystallized with yttrium, substrate analogue p2-NC, DRV, and SQV reveal three distinct conformations of the flexible flaps and diminished interactions with inhibitors through the combination of multiple mutations. PR20 with yttrium at the active site exhibits widely separated flaps lacking the usual intersubunit contacts seen in other inhibitor-free dimers. Mutations of residues 35-37 in the hinge loop eliminate interactions and perturb the flap conformation. Crystals of PR20/p2-NC contain one uninhibited dimer with one very open flap and one closed flap and a second inhibitor-bound dimer in the closed form showing six fewer hydrogen bonds with the substrate analogue relative to wild-type PR. PR20 complexes with PIs exhibit expanded S2/S2' pockets and fewer PI interactions arising from coordinated effects of mutations throughout the structure, in agreement with the strikingly reduced affinity. In particular, insertion of the large aromatic side chains of L10F and L33F alters intersubunit interactions and widens the PI binding site through a network of hydrophobic contacts. The two very open conformations of PR20 as well as the expanded binding site of the inhibitor-bound closed form suggest possible approaches for modifying inhibitors to target extreme drug-resistant HIV.

08 HYDROGEN↗
DOE OSTI2023

Unraveling two distinct polymorph transition mechanisms in one n-type single crystal for dynamic electronics

Cooperativity is used by living systems to circumvent energetic and entropic barriers to yield highly efficient molecular processes. Cooperative structural transitions involve the concerted displacement of molecules in a crystalline material, as opposed to typical molecule-by-molecule nucleation and growth mechanisms which often break single crystallinity. Cooperative transitions have acquired much attention for low transition barriers, ultrafast kinetics, and structural reversibility. However, cooperative transitions are rare in molecular crystals and their origin is poorly understood. Crystals of 2-dimensional quinoidal terthiophene (2DQTT-o-B), a high-performance n-type organic semiconductor, demonstrate two distinct thermally activated phase transitions following these mechanisms. Here we show reorientation of the alkyl side chains triggers cooperative behavior, tilting the molecules like dominos. Whereas, nucleation and growth transition is coincident with increasing alkyl chain disorder and driven by forming a biradical state. We establish alkyl chain engineering as integral to rationally controlling these polymorphic behaviors for novel electronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pathways to a net-zero-carbon water sector through energy-extracting wastewater technologies

The energy-consuming and carbon-intensive wastewater treatment plants could become significant energy producers and recycled organic and metallic material generators, thereby contributing to broad sustainable development goals, the circular economy, and the water-energy-sanitation-food-carbon nexus. This review provides an overview of the waste(water)-based energy-extracting technologies, their engineering performance, techno-economic feasibility, and environmental benefits. Here, we propose four crucial strategies to achieve net-zero carbon along with energy sufficiency in the water sector, including (1) improvement in process energy efficiency; (2) maximizing on-site renewable capacities and biogas upgrading; (3) harvesting energy from treated effluent; (4) a new paradigm for decentralized water-energy supply units.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Interactive cryptographic proofs of quantumness using mid-circuit measurements

The ability to perform measurements in the middle of a quantum circuit is a powerful resource. It underlies a wide range of applications, from remote state preparation to quantum error correction. Here we apply mid-circuit measurements for a particular task: demonstrating quantum computational advantage. The goal of such a demonstration is for a quantum device to perform a computational task that is infeasible for a classical device with comparable resources. In contrast to existing demonstrations, the distinguishing feature of our approach is that the classical verification process is efficient, both in asymptotic complexity and in practice. Furthermore, the classical hardness of performing the task is based upon well-established cryptographic assumptions. Protocols with these features are known as cryptographic proofs of quantumness. Using a trapped-ion quantum computer, we perform mid-circuit measurements by spatially isolating portions of the ion chain via shuttling. This enables us to implement two interactive cryptographic proofs of quantumness, which when suitably scaled to larger systems, promise the efficient verification of quantum computational advantage. In conclusion, our methods can be applied to a range of interactive quantum protocols.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Structure, function, and inhibition of drug reactivating human gut microbial β-glucuronidases

Bacterial β-glucuronidase (GUS) enzymes cause drug toxicity by reversing Phase II glucuronidation in the gastrointestinal tract. While many human gut microbial GUS enzymes have been examined with model glucuronide substrates like p-nitrophenol-β-D-glucuronide (pNPG), the GUS orthologs that are most efficient at processing drug-glucuronides remain unclear. Here we present the crystal structures of GUS enzymes from human gut commensals Lactobacillus rhamnosus, Ruminococcus gnavus , and Faecalibacterium prausnitzii that possess an active site loop (Loop 1; L1) analogous to that found in E. coli GUS, which processes drug substrates. We also resolve the structure of the No Loop GUS from Bacteroides dorei. We then compare the pNPG and diclofenac glucuronide processing abilities of a panel of twelve structurally diverse GUS proteins, and find that the new L1 GUS enzymes presented here process small glucuronide substrates inefficiently compared to previously characterized L1 GUS enzymes like E. coli GUS. We further demonstrate that our GUS inhibitors, which are effective against some L1 enzymes, are not potent towards all. Our findings pinpoint active site structural features necessary for the processing of drug-glucuronide substrates and the inhibition of such processing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Improving deep learning model performance under parametric constraints for materials informatics applications

Abstract Modern machine learning (ML) and deep learning (DL) techniques using high-dimensional data representations have helped accelerate the materials discovery process by efficiently detecting hidden patterns in existing datasets and linking input representations to output properties for a better understanding of the scientific phenomenon. While a deep neural network comprised of fully connected layers has been widely used for materials property prediction, simply creating a deeper model with a large number of layers often faces with vanishing gradient problem, causing a degradation in the performance, thereby limiting usage. In this paper, we study and propose architectural principles to address the question of improving the performance of model training and inference under fixed parametric constraints. Here, we present a general deep-learning framework based on branched residual learning (BRNet) with fully connected layers that can work with any numerical vector-based representation as input to build accurate models to predict materials properties. We perform model training for materials properties using numerical vectors representing different composition-based attributes of the respective materials and compare the performance of the proposed models against traditional ML and existing DL architectures. We find that the proposed models are significantly more accurate than the ML/DL models for all data sizes by using different composition-based attributes as input. Further, branched learning requires fewer parameters and results in faster model training due to better convergence during the training phase than existing neural networks, thereby efficiently building accurate models for predicting materials properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exploration of the bio-analogous asymmetric C–C coupling mechanism in tandem CO 2 electroreduction

C–C coupling is a critical step of CO 2 fixation in constructing the carbon skeleton of value-added multicarbon products. The Wood–Ljungdahl pathway is an efficient natural process through which microbes transform CO 2 into methyl and carbonyl groups and subsequently couple them together. This asymmetric coupling mechanism remains largely unexplored in inorganic CO 2 electroreduction. Here we experimentally validate the asymmetric coupling pathway through isotope-labelled co-reduction experiments on a Cu surface where 13 CH 3 I and 12 CO are co-fed externally as the methyl and the carbonyl source, respectively. Isotope-labelled multicarbon oxygenates were detected, which confirms an electrocatalytic asymmetric coupling on the Cu surface. We further employed tandem Cu–Ag nanoparticle systems in which *CH x and *CO intermediates can be generated to achieve asymmetric C–C coupling for a practical CO 2 electroreduction. We found that the production of multicarbon oxygenates is correlated with the generation rate of two intermediate indicators, CH 4 and CO. By aligning their rates, the oxygenates generation rate can be maximized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗