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At least 631 records · Page 35

Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Here, our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proteogenomic insights suggest druggable pathways in endometrial carcinoma

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

60 APPLIED LIFE SCIENCES↗

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗

Selective CO 2 Reduction by Bis(bipyridine)cobalt(II) Catalysts: The Role of Pendant Pyridine as a Proton Acceptor

Electrochemical CO 2 reduction reaction (CO 2 RR) catalyzed by molecular earth-abundant metal catalysts is a promising strategy to convert CO 2 into value-added products. One recent trend in this field has been focusing on the rational design of catalysts by incorporating redox-active ligands and modifying the secondary coordination sphere (SCS) to achieve efficient and selective CO 2 RR. Herein, we report a series of Co bis­(bipyridine) catalysts featuring various dangling groups, such as pyridine, tertiary amine, or butyl, in the secondary coordination sphere (Co-PyMe, Co-Py, Co-PrN, and Co-Bu). Efficient, selective electrocatalytic CO 2 RR was achieved by the complexes after the generation of triply reduced intermediate consisting of a Co I center and a dianionic ligand, producing CO as the major product and trace amount of H 2 . Strong correlations with the identity of dangling groups and turnover frequency (TOF) have been observed, in which Co-PyMe displayed the highest TOF (1086 s –1 in MeCN/H 2 O). Mechanistic studies indicated that the acceleration of CO 2 RR with pyridine-functionalized catalysts were derived from the protonation of pyridine dangling groups which participated as weak acids in the H-bonding network with exogenous proton sources, stabilizing CO 2 -bound intermediates and facilitating proton transfer. In addition, precatalytic CO 2 binding and activation at the third reduction (−2.1 V) was revealed by CV and SEC-IR studies. The resultant doubly reduced CO-bound species acted as a trapping state which inhibited CO 2 RR electrocatalysis. Regeneration of active species was accessed via reductive dissociation of CO at a more negative potential. In conclusion, this study highlights the combined effects of redox-active ligands and pyridine/pyridinium as SCS groups on CO 2 RR catalysis and provides design principles for future development of CO 2 RR catalysts utilizing pyridine/pyridiniums as SCS functional groups to fine-tune the catalytic activity.

CO2 reduction↗

Assessing Microbial Communities Related to Mercury Transformations in Contaminated Streambank Soils

In nature, the bioaccumulative potent neurotoxin methylmercury (MeHg) is produced from inorganic mercury (Hg) predominantly by anaerobic microorganisms. Hg-contaminated soils are a potential source of MeHg due to microbial activity. We examine streambank soils collected from the contaminated East Fork Poplar Creek (EFPC) in Tennessee, USA, where seasonal variations in MeHg levels have been observed throughout the year, suggesting active microbial Hg methylation. In this study, we characterized the microbial community in contaminated bank soil samples collected from two locations over a period of one year and compared the results to soil samples from an uncontaminated reference site with similar geochemistry (n = 12). Microbial community composition and diversity were assessed by 16S rRNA gene amplicon sequencing. Furthermore, to isolate potential methylators from soils, enrichment cultures were prepared using selective media. A set of three clade-specific primers targeting the gene hgcA were used to detect Hg methylators among the δ-Proteobacteria in EFPC bank soils across all seasons. Two families among the δ-Proteobacteria that have been previously associated with Hg methylation, Geobacteraceae and Syntrophobacteraceae, were found to be predominant with relative abundances of 0.13% and 4.0%, respectively. However, in soil enrichment cultures, Firmicutes were predominant among families associated with Hg methylation. Specifically, Clostridiaceae and Peptococcaceae and their genera Clostridium and Desulfosporosinus were among the ten most abundant genera with relative abundances of 2.6% and 1.7%, respectively. These results offer insights into the role of microbial communities on Hg transformation processes in contaminated bank soils in EFPC. Identifying the biogeochemical drivers of MeHg production is critical for future remediation efforts.

54 ENVIRONMENTAL SCIENCES↗

Towards the usage of quarry blasts as an active seismic source for subsurface characterization and imaging

SUMMARY Active or man-made seismic sources are often used to delineate subsurface geological structures via seismic imaging techniques. Although conventional controlled seismic sources have provided high-resolution subsurface images, the high cost of data acquisition necessitates improved use of cheaper alternative seismic sources for subsurface imaging, such as traffic noise, quarry blasts and earthquakes. Here, we explore the potential use of quarry blasts as an active seismic source for subsurface imaging. The goal of our study is to demonstrate the utility of quarry blasts as seismic sources for investigating subsurface structure with a field experiment in Mill Creek, southern Oklahoma. We deployed a 7455-m-long receiver line of 72 receivers (105 m spacing) extending away from a quarry, with a recording time of 28 d. We analyse similarities between blasts, wave types, origin time and excitation location of quarry blasts, which is important information for using such signal as an active source. Given a relative homogeneous geological condition in the study area, we could not observe clear reflected waves. However, the use of P- and S-wave velocities led to the delineation of a major basement damage zone in the study area, which further demonstrates the viability of quarry blasts as a useful seismic source for subsurface geological imaging.

58 GEOSCIENCES↗

Government sector activities to reduce thermal-spectrum molten salt breeder reactor investment risk

Thermal-Spectrum Molten Salt Breeder Reactors (TS-MSBRs) have long been recognized as having high potential for clean, safe, large-scale, cost-effective energy production for the foreseeable future. U.S. government support for TS-MSBR development was stopped half a century ago in the belief that they were too technically difficult. Technology progression over the past several decades as well as the pressing need for clean power on-demand provides incentives to reconsider the development program cancellation. Limited, early-stage, government sector activities have the potential to sufficiently reduce investor risk to trigger the private sector investment necessary to commercialize the reactor class. In conclusion, these activities are summarized in this article.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Advancements in active filler-contained polymer solid-state electrolytes for lithium-metal batteries: A concise review

Lithium-metal batteries (LMBs) usually are regarded as the pinnacle of next-generation energy storage due to the high specific capacity and low redox potential of the Li-metal anode. However, their development is hindered by safety hazards related to flammable electrolytes and uncontrolled side reactions within the battery. Both polymer and solid-state inorganic electrolytes, despite their potential, exhibit shortcomings that limit their practical applications. Active filler-containing polymer electrolytes (AFPEs) offer a promising solution by combining the benefits of both types. Enhanced by supramolecular interactions between the polymer matrix and active fillers, AFPEs demonstrate superior electrochemical performance over traditional polymer electrolytes. This review discusses the progress in active fillers and various polymer matrices, examining the factors that enhance performance, particularly ionic conductivity. It also outlines the future research directions of AFPEs, aiming to broaden the application of solid electrolytes in high-performance LMBs.

All solid-state batteries↗

Chemical Imaging for In Situ Detection and Discrimination of Aquatic Toxins Targeting Voltage Gated Sodium Channels

Biologically derived neurotoxins from cyanobacteria and algae impact environmental resources in addition to being considered a potential biological threat to human and animal health. Activity based assays are essential to detecting and responding to toxic neurotoxin events either naturally occurring or deliberate. Two toxins of interest include saxitoxin and brevetoxin. These toxins bind to and alter the function of voltage-gated sodium channels (NaV channels) which are essential for generating cell membrane action potential. We report the development and refinement of a System for Analysis at Liquid Vacuum Interface (SALVI) to assess the functional activity of saxitoxin and brevetoxin. This approach utilizes a vacuum-compatible microfluidic reactor that permits analysis at the liquid vacuum interface of human derived cells with a neurotoxin of interest in a biologically relevant environment.

54 ENVIRONMENTAL SCIENCES↗

A lipase from Lacticaseibacillus rhamnosus IDCC 3201 with thermostability and pH resistance for use as a detergent additive

Lipases are important biocatalysts and ubiquitous in plants, animals, and microorganisms. The high growth rates of microorganisms with low production costs have enabled the wide application of microbial lipases in detergent, food, and cosmetic industries. Herein, a novel lipase from Lacticaseibacillus rhamnosus IDCC 3201 (Lac-Rh) was isolated and its activity analyzed under a range of reaction conditions to evaluate its potential industrial application. The isolated Lac-Rh showed a molecular weight of 24 kDa and a maximum activity of 3438.5 ± 1.8 U/mg protein at 60 °C and pH 8. Additionally, Lac-Rh retained activity in alkaline conditions and in 10% v/v concentrations of organic solvents, including glycerol and acetone. Interestingly, after pre-incubation in the presence of multiple commercial detergents, Lac-Rh maintained over 80% of its activity and the stains from cotton were successfully removed under a simulated laundry setting. Overall, the purified lipase from L. rhamnosus IDCC 3201 has potential for use as a detergent in industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing Structural Evolution of Nickel Phosphide-Iron Oxide Core–Shell Nanocatalysts in Alkaline Medium for the Oxygen Evolution Reaction

Metal phosphide-containing materials have emerged as a potential candidate of non-precious metal-based catalysts for alkaline oxygen evolution reaction (OER). While it is known that metal phosphide undergoes structural evolution, considerable debate persists regarding the effects of dynamics on the surface activation and morphological stability of the catalysts. In this study, we synthesize NiP x -FeO x core-shell nanocatalysts with an amorphous NiP x core designed for enhanced OER activity. Using ex-situ X-ray absorption spectroscopy, we elucidate the local structural changes as a function of cyclic voltammetry cycles. Our studies suggest that the presence of corner-sharing octahedra in the FeO x shell improves structural rigidity through interlayer cross-linking, thereby inhibiting the diffusion of OH - /H 2 O. Thus, the FeO x shell preserves the amorphous NiP x core from rapid oxidation to Ni 3 (PO 4 ) 2 and Ni(OH) 2 . On the other hand, the incorporation of Ni from the core into the FeO x shell facilitates absorption of hydroxide ions for OER. As a result, the Ni/Fe(OH) x at the surface oxidizes to the active γ-(oxy)hydroxide phase under the applied potentials, promoting OER. This intriguing synergistic behavior holds significance as such synthetic route involving the FeO x shell can be extended to other systems, enabling manipulation of surface adsorption and diffusion of hydroxide ions. These findings also demonstrate that nanomaterials with core-shell morphology can be tuned to leverage the strength of each metallic component for improved electrochemical activities.

25 ENERGY STORAGE↗

Potential defect structure effects in the volatility separation of sub-picogram quantities of fission and activation products from an irradiated UO2 matrix

Here, the use of fluorination as a rapid separation technique for quantification of trace-mass, short-lived isotopes is illustrated. Single crystal 238 UO 2 was exposed to a 14 MeV neutron source to produce mixed fission and activation products. Selective removal of trace volatile fluorides from non-volatile ones produced two results of interest. A decrease in background produced better detection and quantification of select analytes across the gamma spectrum. Second, at the very low burnup condition described, the volatility behaviors of common isotopes were altered relative to their well-established behaviors in higher burnup metal and metal oxide fuels.

Fission and activation product separations↗

Two-dimensional ring polymer molecular dynamics determination of the MnO + + H 2 /D 2 reaction rates on a Δ-machine learned potential energy surface

In this work, we investigate the impact of nuclear quantum effects in the kinetics of the MnO + + H 2 reaction, a prototypical system for gas-phase H 2 activation by transition metal oxide ions. The DFT based potential energy surfaces (PESs) for the lowest-lying quintet and septet spin states reported in our previous work are improved by 2953 newly calculated CCSD(T)/AVDZ points using a delta-machine learning (Δ-ML) method. To examine nuclear quantum effects, the rate coefficients are computed using ring-polymer molecular dynamics (RPMD). Due to the mechanistic complexity of the reaction, two reaction coordinates are necessary to map out the free-energy surface and an extended RPMD rate theory is developed. The calculated RPMD rate coefficients on the new PES are in better agreement with experimental data. The calculated kinetic isotope effects (KIEs) range from 1.6 to 1.8, also in good agreement with the experimental values. Additionally, the converged RPMD rate coefficients are 2.3 to 3.1 times higher than their classical counterparts across the studied temperature range, suggesting the presence of moderate nuclear quantum effects in this reaction.

Liu, Yang [University of New Mexico, Albuquerque, ↗

Increasing the Hot‐Electron Driven Hydrogen Evolution Reaction Rate on a Metal‐Free Graphene Electrode

Abstract Recently, it has been shown that a semiconductor–insulator–graphene device can drive the hydrogen evolution reaction (HER) at the graphene surface with a reduced onset potential by injecting hot electrons into graphene. However, the catalytic properties of graphene are limited by the large hydrogen adsorption energy and lack of electrochemically active sites. To address these limitations, a n ‐silicon/insulator/plasma etched graphene device is investigated, where a dry etch process is used to increase the number of active sites on the graphene by creating a greater number of active edge sites, increasing hydrogen adsorption at a given potential. This has been shown to improve the properties of devices with cold electrons. However, here it is shown that this approach can improve the HER rate with hot electrons. The electrons injected into the graphene from the silicon shift the onset potential of HER by as high as ≈0.8 V reaching a current density of 90 mA cm −2 at an overpotential of ‐0.5 V versus RHE. Furthermore, the comparison between device with pristine graphene shows a ≈2X improvement in current density at high overpotentials. This result shows that hot‐electron devices can be improved by modifying the catalytically active sites without metal catalysts.

Chae, Hyun Uk↗

Hybrid Metal Halides: Advancing Optoelectronic Materials (Final Technical Report)

Hybrid metal halides, particularly main group halide perovskites, are a unique class of materials that offer exceptional optoelectronic properties along with a remarkable materials design space. Initial research on this class of materials was driven by the ability of the prototype hybrid 3D perovskite-structured compound methylammonium lead iodide to function as the active layer in thin film solar cells. It is now known that this class of materials comprise a large family with tunable band gaps, relatively high charge carrier mobilities in both single crystal and polycrystalline forms, and relatively low concentrations of (deleterious) electrically active states within the band gap. Beyond applications in solar cells, the potential of these materials has been extended to emitters in light emitting diodes, and active components of radiation detectors. Complementing new functionality, the design space for hybrid metal halides continues to increase with discovery of new structural motifs. In this project, the combination of organic and inorganic functionalities has been employed to open pathways to the design and synthesis new, functional hybrid metal halides. Beyond the simple perovskites, Ruddlesden-Popper and Dion-Jacobsen compounds, and other variants, such as the newly advanced “hollow” perovskites have been studied. The materials have provided routes to understanding the unique electronic properties of hybrid metal halides because of their natural quantum well structures as well as other means of controlling band gaps and band dispersions. Understanding these materials, including the design rules for their formation, their structures and compositions in bulk and in thin films form, and the role of local (non-crystallographic) structure has an important aspect of this endeavor. The goal of advancing new materials and new fundamental understanding within this deceptively simple, yet fascinating class of compounds, so richly endowed with interesting and useful functionality, has been fulfilled.

36 MATERIALS SCIENCE↗

Composite Analysis Solid Waste Release Data Reduction of Activity Flux from Waste Sites to the Vadose Zone for Baseline Assessment

This environmental calculation file (ECF) describes the data reduction methodology for the solid waste release datasets generated by the Composite Analysis Solid Waste Release (CASWR) model (CP-62766, Model Package Report: Composite Analysis Solid Waste Release Model [CASWR Model]) and documents the resulting reduced datasets for the updated Composite Analysis (CA) baseline assessment. This ECF is in support of the updated Hanford Site CA. The purpose of the updated Hanford Site CA is to provide an estimate of the cumulative radiological impacts from active and planned low-level radioactive waste disposals and other potentially interacting radioactive waste disposal sources that will remain following Hanford Site closure. The vadose zone modeling activities associated with the CA includes solid waste forms as contaminant sources. To support the modeling of solid waste transport from the vadose zone to the groundwater at the Hanford Site, the CASWR model was designed to generate deterministic radionuclide release rates for the Hanford Site Central Plateau solid waste disposal sites. The complete CASWR model-generated dataset for the CA Baseline Assessment consists of 2,378,831 sets of time and release rates (1,073,869 sets for the 200 East Area and 1,304,962 sets for the 200 West Area), representing a course of the simulation from year 1953 to year 12,069, 16 radiological contaminants of potential concern (COPCs), and 237 solid waste sources as documented in ECFHANFORD- 19-0112, Solid Waste Release Calculations for the Composite Analysis Baseline Assessment. For several of the STOMP vadose zone models, the number of release rate data pairs required for release at all waste sites would exceed the limitations imposed by the STOMP modelling software package used to simulate contaminant transport through the vadose zone. As a result, a data reduction of the CASWR dataset is required prior to its use as a source input for the CA vadose zone modeling activities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Dataset, Code, and Models for Training Deep Learning Potentials for Low Temperature Plasma-Surface Interactions

This repository contains datasets, training scripts, and finished models, and test simulations used in the development of DeepREBO— a machine-learned interatomic potential trained to emulate the REBO2 empirical potential. The data was generated to study deep potential development for simulations of plasma-surface interactions. It uses an active learning framework, starting from a minimal dataset and iteratively expanding it. Included are those generated datasets, the trained models, and simulations used to evaluate the performance of the training process. This resource supports reproducibility and provides a reference framework for training deep potentials in plasma-surface interaction studies.

active learning↗