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At least 613 records · Page 34

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DOE OSTI2026

Hypochlorite Redox Chemistry Enables High-Voltage and High-Power Saltwater Batteries

Saltwater batteries (SWBs) are promising alternatives to lithium-ion batteries for large-scale stationary energy storage. However, the performance of conventional oxygen redox-based saltwater battery systems is often constrained by sluggish oxygen evolution and reduction reactions (OER/ORR) at the cathode, leading to low voltage efficiency and limited power density. Here, OER and ORR are replaced by hypochlorite-based redox reactions through the introduction of sodium hypochlorite into saltwater. Operando pH and dissolved oxygen measurements confirm that OER and ORR are minimized and that hypochlorite redox reactions dominate the cathode behavior. Owing to the higher operating potential and faster reaction kinetics, the hypochlorite-redox-based SWBs delivers a higher discharge voltage of 3.3 V and reduced charge-discharge voltage polarization to 0.66 V. Further improvement is achieved by adjusting the saltwater pH to near-neutral conditions, increasing the discharge voltage to 3.5 V and more than doubling the peak power. The hypochlorite redox environment also exhibits chemical stability with key cell components, including the solid electrolyte and cathode current collectors. Operation of series-connected cells and cells employing hard carbon anodes demonstrates scalability and compatibility with alternative anode materials. These results provide a strong foundation for next-generation SWBs targeting large-scale stationary energy storage applications.

Go, Wooseok [ORNL]↗

DOE OSTI2024

Tight Bounds from Multiple‐Observable Entropic Uncertainty Relations

Abstract The additivity properties for both bipartite and multipartite systems are investigated by using entropic uncertainty relations (EUR) defined in terms of the joint Shannon entropy of probabilities of local measurement outcomes. In particular, state‐independent and state‐dependent entropic inequalities are introduced. Interestingly, the violation of these inequalities is strictly connected with the presence of quantum correlations. It is shown that the additivity of EUR holds only for EUR that involve two observables, while this is not the case for inequalities that consider more than two observables or the addition of the von Neumann entropy of a subsystem. They are applied to bipartite systems and to several classes of states of a three‐qubit system.

Riccardi, Alberto↗

DOE OSTI2025

Quantum‐Classical Simulation of Quantum Field Theory by Quantum Circuit Learning

Abstract Quantum circuit learning is employed to simulate quantum field theories (QFTs). Typically, when simulating QFTs with quantum computers, significant challenges are encountered due to the technical limitations of quantum devices when implementing the Hamiltonian using Pauli spin matrices. To address this challenge, quantum circuit learning is leveraged, employing a compact configuration of qubits and low‐depth quantum circuits to predict real‐time dynamics in quantum field theories. The key advantage of this approach is that a single‐qubit measurement can accurately forecast various physical parameters, including fully‐connected operators. To demonstrate the effectiveness of this method, it is used to predict quench dynamics, chiral dynamics and jet production in a 1+1‐dimensional model of quantum electrodynamics. It is found that our predictions closely align with the results of rigorous classical calculations, exhibiting a high degree of accuracy. This hybrid quantum‐classical approach illustrates the feasibility of efficiently simulating large‐scale QFTs on cutting‐edge quantum devices.

Ikeda, Kazuki [Department of Physics University of↗

DOE OSTI2025

Refining T c Prediction in Hydrides via Symbolic‐Regression‐Enhanced Electron‐Localization‐Function‐Based Descriptors

Hydrogen‐based materials are able to possess extremely high superconducting critical temperatures, T c s , due to hydrogen's low atomic mass and strong electron–phonon interaction. Recently, a descriptor based on the Electron Localization Function (ELF) has enabled the rapid estimation of the T c of hydrogen‐containing compounds from electronic networking properties, but its applicability has been limited by the small size and homogeneity of the training dataset used. Herein, the model is re‐examined, compiling a publicly available combined dataset of 244 binary and ternary hydride superconductors. The analysis shows that though ELF‐based networking remains a valuable descriptor, its predictive power declines with increasing compositional complexity. However, by introducing the molecularity index, defined as the highest value of the ELF at which two hydrogen atoms connect, and applying symbolic regression, the accuracy of the predictions can be substantially enhanced. These results establish a more robust framework for assessing superconductivity in hydride materials, facilitating accelerated screening of novel candidates through integration with crystal structure prediction methods or high‐throughput searches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Tubular Nanostructures from Large‐Pore 2D Covalent Organic Frameworks

Abstract The synthesis of a wavy mesoporous 2D covalent organic framework (COF) with a 6‐nm hexagonal pore lattice ( Joa‐COF‐1 ) is reported. This has been achieved by the synthesis of a terpyrenyl linker of approximately 2.7 nm in length and its subsequent condensation with a 3‐connected non‐planar cata‐hexabenzocoronene. Joa‐COF‐1 exists as non‐covalent tubular domains composed of π‐stacked 4 to 5 pores in 2D COF sections that can be separated by mild sonication, resulting in a family of tubular COF nanostructures that combine a 1D morphology with accessible mesopores.

Almarza, Joaquín [POLYMAT University of the Basque↗

DOE OSTI2024

Reductive Elimination From Tetra‐Alkyl Cuprates [Me n Cu(CF 3 ) 4− n ] − ( n =0–4): Beyond Simple Oxidation States

Abstract In recent years, the electronic structures of organocuprates in general and the complex [Cu(CF 3 ) 4 ] − in particular have attracted significant interest. A possible key indicator in this context is the reactivity of these species. Nonetheless, this aspect has received only limited attention. Here, we systematically study the series of tetra‐alkyl cuprates [Me n Cu(CF 3 ) 4− n ] − and their unimolecular reactivity in the gas phase, which includes concerted formal reductive eliminations as well as radical losses. Through computational studies, we characterize the electronic structures of the complexes and show how these are connected to their reactivity. We find that all [Me n Cu(CF 3 ) 4− n ] − ions feature inverted ligand fields and that the distinct reactivity patterns of the individual complexes arise from the interplay of different effects.

Zimmer, Bastian↗

DOE OSTI2025

Tubular Nanostructures from Large‐Pore 2D Covalent Organic Frameworks

Almarza, Joaquín [POLYMAT University of the Basque↗

DOE OSTI2025

Magnetic Solitons and Thickness‐Dependent Magnetization Reversal in Interconnected Helical Nanowire Arrays

By expanding magnetic nanostructures into the third dimension, it is possible to introduce new interactions and realize new forms of magnetic textures and emergent phenomena. Consequently, this unlocks new opportunities for applications in data storage, unconventional computing and sensing by utilizing 3D devices with enhanced functionalities. Connected magnetic nanowires offer a unique platform for applications such as neuromorphic computing due to their tunability and the presence of multiple transport pathways. However to realize this promise, it is necessary to further our understanding of how to locally control the magnetization in 3D, nanowire-based geometries. In this work we show the formation of magnetic domain walls, vortices, anti-vortices, and linked vortex-anti-vortex pairs in interconnected helical nanowire arrays. We show how wire diameter and 3D geometric design can control the states that form and reveal the magnetization reversal mechanism. Hence, we demonstrate this to be a highly tunable system, where the magnetization can be readily reconfigured by an external magnetic field.

3D Nanomagnetism↗

DOE OSTI2025

Structure–Activity Relationships of Inactive‐Conformation Binding EGFR Inhibitors: Linking the ATP and Allosteric Pockets

ABSTRACT The epidermal growth factor receptor (EGFR) tyrosine kinase is an important therapeutic target in non‐small cell lung cancer (NSCLC). However, the continual emergence of resistance mutations in the treatment of EGFR mutation‐positive NSCLC with currently approved tyrosine kinase inhibitors warrants the development of next‐generation inhibitors. Since research for ATP‐competitive EGFR tyrosine kinase inhibitors (TKIs) that extend into the back pocket has been neglected in the recent past, we survey the extent to which such binding functional groups can be incorporated into an ATP‐site imidazole scaffold. We find thatmeta‐substituted amide linkers derivatized with fluorine in 2,6‐positions and/or a hydroxy group in 3‐position of the back pocket phenyl exhibit the highest potency. Structural insights into how the back pocket groups are bound through points of connection provide new directions for the discovery and optimization of inactive conformation targeting agents in EGFR and other kinases.

Chemistry↗

DOE OSTI2024

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

ABSTRACT Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica , Debaryomyces hansenii , and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Weintraub, Sarah J. [Department of Bioinformatics ↗

DOE OSTI2024

Mechanisms in the Synthesis of S -Alcohols with 1,4-NADH Biomimetic Co-factor N-Benzyl-1,4-dihydronicotinamide using Horse Liver Alcohol Dehydrogenase: A Hybrid Computational Study

The enantioselective reduction of prochiral ketones catalyzed by horse liver alcohol dehydrogenase (HLADH), was investigated via a hybrid computational approach, for molecular reactions involved in chiral synthesis of S-alcohols, when the natural co-factor, 1,4-dihyronicotinamide adenine dinucleotide, 1,4-NADH, was replaced with biomimetic co-factor, N-benzyl-1,4-dihydronicotinamide, 1. We surmised that different hydride and proton transfer mechanisms were involved using co-factor, 1. An alternative mechanism, where the hydride transfer step occurred, via an η 1 -keto-S-η 2 -5,6-1,4-dihydronicotinamide-Zn(II) complex, was previously investigated with a model of the HLADH-Zn(II) catalytic site (J. Organometal. Chem. 2021, 943, 121810). Presently, we studied canonical and alternative mechanisms compared to models of the entire enzyme structure. We disproved the η 2 -Zn(II) complex, and discovered a canonical hydride transfer from biomimetic 1,4-NADH, 1, to the Zn(II) bound prochiral ketone substrate, followed by a new proton relay, consisting of a water chain connecting His51 to Ser48 that accomplished the S-alkoxy anion's protonation to yield the final S-alcohol product. The HLADH catalysis, with biomimetic co-factor, 1, that replaced the ribose group, the 5'-diphosphate groups, and the adenine nucleotide with a N-benzyl group, has provided a new paradigm for the design of other structures of 1,4-NADH biomimetic co-factors, including their economic value in biocatalysis reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Evaluation of Iron‐Phosphate Glass–Ceramic Waste Form for Electrorefiner Salt Waste Simulant Dechlorinated With Phosphoric Acid

The importance of glass and glass–ceramic nuclear waste forms has been reaffirmed in recent years by the growing interest in nuclear power as a reliable energy source. Determination of processing methods for the disposal of halide-containing wastes will be essential for the advancement of nuclear technologies such as non-aqueous fuel reprocessing. Phosphate-based dechlorination and subsequent vitrification of radioactive salt waste into an iron-phosphate waste form have been identified as a potential processing scheme for electrochemical processing waste. The impact of H 3 PO 4 -based dechlorination of complex salt mixtures on the vitrification process and structure of the final iron-phosphate waste form has not yet been investigated. In this work, iron-phosphate glass–ceramics were made from simulant salt waste (48LiCl–33KCl–19NaCl mol%) dechlorinated with the H3PO4-based method. The glass-forming region was compared to that of traditionally prepared Na 2 O–Fe 2 O 3 –P 2 O 5 systems. For a candidate glass-forming composition, the processing scheme presented here was determined to favor Fe 3+ species. The O/P molar ratio was consistent for the candidate composition when dechlorinated at 400°C and 600°C in air and argon environments, indicating glass network connectivity was maintained despite variations in processing parameters. The results presented here validate processing schemes requiring iron-phosphate waste form synthesis following H 3 PO 4 -based dechlorination.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Carbon‐13 Hyperpolarization of α‐Ketocarboxylates with Parahydrogen in Reversible Exchange

Abstract Signal Amplification by Reversible Exchange (SABRE) is a relatively simple and fast hyperpolarization technique that has been used to hyperpolarize the α‐ketocarboxylate pyruvate, a central metabolite and the leading hyperpolarized MRI contrast agent. In this work, we show that SABRE can readily be extended to hyperpolarize 13 C nuclei at natural abundance on many other α‐ketocarboxylates. Hyperpolarization is observed and optimized on pyruvate (P 13C =17 %) and 2‐oxobutyrate (P 13C =25 %) with alkyl chains in the R‐group, oxaloacetate (P 13C =11 %) and alpha‐ketoglutarate (P 13C =13 %) with carboxylate moieties in the R group, and phenylpyruvate (P 13C =2 %) and phenylglyoxylate (P 13C =2 %) with phenyl rings in the R‐group. New catalytically active SABRE binding motifs of the substrates to the hyperpolarization transfer catalyst – particularly for oxaloacetate – are observed. We experimentally explore the connection between temperature and exchange rates for all of these SABRE systems and develop a theoretical kinetic model, which is used to fit the hyperpolarization build‐up and decay during SABRE activity.

McBride, Stephen J. [Department of Chemistry North↗

DOE OSTI2024

Converting Second‐Order Saddle Points to Transition States: New Principles for the Design of 4π Photoswitches

Abstract Molecular photoswitches have demonstrated potential for storing solar energy at the molecular level, with power densities comparable to commercial batteries and hydroelectric energy storage. However, development of efficient photoswitches is hindered by limitations in cyclability and optical properties of existing materials. We here demonstrate that certain limitations in photoswitches based on electrocyclizations stem from the issue of controlling competition between Woodward‐Hoffmann allowed and forbidden pathways. Our approach moves beyond the traditional view of activation barriers and reveals that second‐order saddle points are crucial in dictating the competition between disrotatory and conrotatory pathways. These insights suggest new opportunities to manipulate the competition between these pathways through geometric constraints, fundamentally altering the connectivity of the potential energy surface. Our study also emphasizes the necessity of multi‐reference methods and the need to conduct higher‐dimensional explorations for competing pathways beyond photoswitch design.

Chemistry↗

DOE OSTI2025

Deciphering the Evolution of Current Distribution in Hybrid Silver Vanadium Oxide / Carbon Monofluoride Cathodes within Lithium Primary Batteries

For batteries to function effectively all active material must be accessible requiring both electron and ion transport to each particle. A common approach to generating the needed conductive network is the addition of carbon to create a composite electrode. An alternative approach is the electrochemically induced formation of conductive reaction products where the electrochemically generated materials are in intimate contact with the active material contributing to effective connection of each active particle. Furthermore, this study probes silver vanadium oxide (Ag 2 V 4 O 11 , SVO), carbon monofluoride (CF x ), and hybrid SVO/CF x electrodes in lithium batteries. Ex situ XRD identifies Ag 0 as a reduction product from SVO and LiF from CF x that can be followed as a function of depth-of-discharge (DOD). Spatially-resolved operando energy dispersive x-ray diffraction reveals that the presence of SVO alleviates reaction heterogeneity in the electrodes which are electron transfer limited in the absence of sufficient Ag 0 . Synchrotron X-ray tomography on discharged cathodes reveals the distribution of silver particles where the particles are more closely spaced near the current collector indicating multiple nucleation sites for their formation. Finally, operando isothermal microcalorimetry is used to determine the heat dissipation of the parent and hybrid battery types. Using material enthalpy potentials, we determine the current distribution between the two active materials for the discharging hybrid cathode adding further insight to the diffraction analysis. Taken together, these results provide a comprehensive understanding of hybrid SVO/CF x cathodes and give guidance on optimal compositions that balance power and energy density considerations.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Accessing Transient Isomers in the Photoreaction of Metastable‐State Photoacid

The photoreaction of a metastable‐state photoacid (mPAH) generally involves multiple isomers with various connected pathways of photoinduced structural changes during a single reaction cycle. However, only a limited number of isomers have been identified experimentally so far owing to the inherent complexity in combination with the presence of various competing electronic and vibrational processes, as well as the constantly varying interactions between mPAH isomers and solvent molecules. Here, in this work, an optical spectroscopic study on a benzimidazole‐based mPAH, a novel photoacid using benzimidazole as the structural moiety with the active proton, is reported. Through measurements of linear absorption and steady‐state fluorescence in neat solvents and binary mixtures, a pronounced effect of neat water and its binary mixture with glycerol is discovered on the photoreaction of this benzimidazole‐mPAH, manifested by the remarkably distinct spectral responses to irradiation from that observed for an organic solution under identical conditions. Measurements of time‐ and frequency‐resolved fluorescence emission further enable to access transient isomers and the associated spectral characteristics from other competing electronic excited‐state relaxation processes. Spectral deconvolution analysis and time‐dependent density functional theory calculations are applied to separate distinct spectral components and access their potential origin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Mo 3 S 13 Chalcogel: A High-Capacity Electrode for Conversion-Based Li-Ion Batteries

Despite large theoretical energy densities, metal-sulfide electrodes for energy storage systems face several limitations that impact the practical realization. Here, we present the solution-processable, room temperature (RT) synthesis, local structures, and application of a sulfur-rich Mo 3 S 13 chalcogel as a conversion-based electrode for lithium-sulfide batteries (LiSBs). The structure of the amorphous Mo 3 S 13 chalcogel is derived through operando Raman spectroscopy, synchrotron X-ray pair distribution function (PDF), X-ray absorption near edge structure (XANES), and extended X-ray absorption fine structure (EXAFS) analysis, along with ab initio molecular dynamics (AIMD) simulations. A key feature of the three-dimensional (3D) network is the connection of Mo 3 S 13 units through S–S bonds. Li/Mo 3 S 13 half-cells deliver initial capacity of 1013 mAh g –1 during the first discharge. After the activation cycles, the capacity stabilizes and maintains 312 mAh g –1 at a C/3 rate after 140 cycles, demonstrating sustained performance over subsequent cycling. Such high-capacity and stability are attributed to the high density of (poly)sulfide bonds and the stable Mo–S coordination in Mo 3 S 13 chalcogel. Importantly, these findings showcase the potential of Mo 3 S 13 chalcogels as metal-sulfide electrode materials for LiSBs.

25 ENERGY STORAGE↗

DOE OSTI2024

Identifying microbial drivers in biological phenotypes with a Bayesian network regression model

Abstract In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify regions in the brain that are associated with specific human traits, yet their potential to elucidate microbial drivers in biological phenotypes for microbiome research remains unknown. In particular, microbial networks are challenging due to their high dimension and high sparsity compared to brain networks. Furthermore, unlike in brain connectome research, in microbiome research, it is usually expected that the presence of microbes has an effect on the response (main effects), not just the interactions. Here, we develop the first thorough investigation of whether Bayesian Network Regression models are suitable for microbial datasets on a variety of synthetic and real data under diverse biological scenarios. We test whether the Bayesian Network Regression model that accounts only for interaction effects (edges in the network) is able to identify key drivers (microbes) in phenotypic variability. We show that this model is indeed able to identify influential nodes and edges in the microbial networks that drive changes in the phenotype for most biological settings, but we also identify scenarios where this method performs poorly which allows us to provide practical advice for domain scientists aiming to apply these tools to their datasets. BNR models provide a framework for microbiome researchers to identify connections between microbes and measured phenotypes. We allow the use of this statistical model by providing an easy‐to‐use implementation which is publicly available Julia package at https://github.com/solislemuslab/BayesianNetworkRegression.jl .

59 BASIC BIOLOGICAL SCIENCES↗