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At least 937 records · Page 52

How Does HF-DFT Achieve Chemical Accuracy for Water Clusters?

Bolstered by recent calculations of exact functional-driven errors (FEs) and density-driven errors (DEs) of semilocal density functionals in the water dimer binding energy , we investigate approximate FEs and DEs in neutral water clusters containing up to 20 monomers, charged water clusters, and alkali- and halide-water clusters. Our proxy for the exact density is r 2 SCAN 50, a 50% global hybrid of exact exchange with r 2 SCAN, which may be less correct than r 2 SCAN for the compact water monomer but importantly more correct for long-range electron transfers in the noncompact water clusters. We show that SCAN makes substantially larger FEs for neutral water clusters than r 2 SCAN, while both make essentially the same DEs. Unlike the case for barrier heights, these FEs are small in a relative sense and become large in an absolute sense only due to an increase in cluster size. SCAN@HF, short for SCAN evaluated on the Hartree–Fock (HF) density, produces a cancellation of errors that makes it chemically accurate for predicting the absolute binding energies of water clusters. Likewise, adding a long-range dispersion correction to r 2 SCAN@HF, as in the composite method HF-r 2 SCAN-DC4, makes its FE more negative than in r 2 SCAN@HF, permitting a near-perfect cancellation of FE and DE. r 2 SCAN by itself (and even more so, r 2 SCAN evaluated on the r 2 SCAN 50 density), is almost perfect for the energy differences between water hexamers, and thus probably also for liquid water away from the boiling point. Thus, the accuracy of composite methods like SCAN@HF and HF-r 2 SCAN-DC4 is not due to the HF density being closer to the exact density, but to a compensation of errors from its greater degree of localization. We also give an argument for the approximate reliability of this unconventional error cancellation for diverse molecular properties. Lastly, we confirm this unconventional error cancellation for the SCAN description of the water trimer via Kohn–Sham inversion of the CCSD(T) density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A country-scale green energy-water-hydrogen nexus: Jordan as a case study

Many developing countries suffer from a shortage of clean energy-water production, causing significant dependency on imported fossil fuel to meet the local energy and freshwater demands. Furthermore, when planning a 100 % renewable energy system (RES) to match the energy demand on an hourly basis, the RES is usually oversized. Hence, unavoidable large amounts of excess energy would be generated during hours of high production, low demand, and fully charged energy storage systems (ESSs). Hence, using Jordan as a case study, this work proposes a novel integrated system of wind, solar photovoltaic (PV), and lithium-ion ESS to match 100 % of the country's energy demand while using the excess generated power to drive reverse osmosis water desalination plants to match the demand of freshwater as well. Furthermore, the remaining excess energy is used for producing green hydrogen. A techno-economic optimizer was developed to show that this concept is indeed feasible. Here, the model was used to scan Jordan for the fitting sites of the highest demand-supply matching and the lowest levelized cost of electricity (LCOE), simultaneously. Three different integration scenarios are presented, namely PV-ESS, wind-ESS, and hybrid PV-wind-ESS RESs. The hybrid system showed the best performance, especially compared to the wind-ESS RES, in terms of total installed capacity (33.37 GW), LCOE (0.0492 USD/kWh), specific water cost (0.3629 USD/m 3 ), and energy and water demand-supply fractions (99.47 and 96.16 %, respectively). Storing desalinated water in natural aquifers was found to be a favorable option to enhance the performance of the three systems, where stored water by the end of the year was sufficient to cover the freshwater requirements for several following years. Finally, the remaining excess energy is used to produce green hydrogen with an annual production of up to 1.37 million tons and a specific cost down to 1.08 USD/kg.

14 SOLAR ENERGY↗

Co‐Electrolysis of CO 2 and H 2 O to Syngas on Bimetallic Pd x Cu 1‐ x Catalysts for Tandem Thermochemical Conversion to Carbon Nanofibers

Electrification of chemical production using renewable energy and abundant feedstocks offers a promising pathway for decarbonizing the chemical industry. Current efforts on CO 2 valorization largely focus on making chemicals and fuels. Here, to help achieve net-negative emissions through long-term carbon storage, this study aims to develop efficient electrocatalysts for a tandem electrochemical-thermochemical process to convert CO 2 into carbon nanofibers (CNFs). CO 2 and water are first electrochemically reduced in a membrane electrode assembly (MEA) electrolyzer to produce syngas (CO + H 2 ), which is subsequently fed into a thermochemical packed bed reactor to facilitate CNF growth. This work systematically evaluated Pd x Cu 1-x bimetallic electrocatalysts to assess the effect of Pd–Cu alloying on enhancing syngas production while reducing Pd loading. Transmission electron microscopy and Raman spectroscopy confirmed the formation of high-purity, crystalline CNFs, regardless of the syngas composition from the MEA. In situ X-ray absorption spectroscopy and X-ray diffraction measurements revealed that increasing Cu content in the Pd x Cu 1-x alloy progressively inhibited palladium hydride formation, consistent with DFT calculations on the stability of Pd x Cu 1-x under reducing electrochemical potentials.

58 GEOSCIENCES↗

Bioinspired Activation of N 2 on Asymmetrical Coordinated Fe Grafted 1T MoS 2 at Room Temperature

Inspired by the nitrogen fixation process on MoFe nitrogenase, asymmetrical coordinated Fe grafted onto 1T MoS 2 were successfully synthesized. The unique electron -rich structure with asymmetrical coordination made the 1T Fe 0.1 Mo 0.9 S 2 layered material actively react with water and dinitrogen at room temperature and atmosphere pressure. Subsequently, ammonia can be produced with a yield of 800 pmol (NH 4 + ) g -1 (12.5% yield in mole). The activation, fixation and reduction of dinitrogen were confirmed by isotopically labeled experiments. The location and the specific coordination environment of grafted Fe in Fe-Mo-S were further determined by X-ray absorption spectroscopy analysis. Our work demonstrates that the nitrogen fixation and reduction for ammonia at room temperature without any chemical and electrochemical assistance is distinctly different from traditional bionic -inspired nitrogen fixation process. The mechanism of the activation and reduction of N 2 was further investigated by density functional theory calculation and Raman spectra. Compared with 1T MoS 2 , the enriched electron nature and asymmetrical coordination of Fe in Fe-Mo-S materials play a critical role in the bioinspired activation of N 2 at ambient condition.

1T MoS2↗

Plasma‐driven biocatalysis: In situ hydrogen peroxide production with an atmospheric pressure plasma jet increases the performance of OleT JE when compared to adding the same molar amount of hydrogen peroxide in bolus

Abstract Enzymes like fatty acid peroxygenase OleT JE are desirable enzymes for the industry. While they require inexpensive hydrogen peroxide for activity, the same hydrogen peroxide also causes overoxidation of their reactive heme center. Here, we generate hydrogen peroxide slowly in situ using the Cooperation in Science and Technology (COST)‐Jet, an atmospheric pressure plasma jet, to avoid overoxidizing OleT JE . The COST‐Jet was operated in helium with a water admixture to provide hydrogen peroxide for OleT JE activity. This helium/water admixture produced the highest enzyme turnover numbers after 2 min of treatment. These turnover numbers were even superior to using an equimolar amount of hydrogen peroxide to treat the enzymes exogenously, showing that this plasma source can provide a reliable amount of reaction mediator to support OleT JE activity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Long-term cement hydration studies with isothermal calorimetry

The purpose of this study was to investigate for how long the thermal power of hydration can be measured with isothermal calorimetry, which is a general measurement technique with stable properties that, in many cases, can detect low rates of processes. Measurements were conducted for 365 days on cement paste with Portland cement, fly ash blended Portland cement and different water-to-binder ratios. The results showed that all the tested systems still produced a measureable signal after one year. The samples with Portland cement were also analyzed by XRD after 365 days, and phase composition calculations were made with GEMS. Together with the calorimetric results, these results were used to determine the degree of hydration by five methods, the results of which showed good agreement.

36 MATERIALS SCIENCE↗

Atomic autoionization in the photo-dissociation of super-excited deuterated water molecules fragmenting into D + + O + + D

We present the relaxation dynamics of deuterated water molecules via autoionization, initiated by the absorption of a 61 eV photon, producing the very rare D + + O + + D breakup channel. We employ the COLd target recoil ion momentum spectroscopy method to measure the 3D momenta of the ionic fragments and emitted electrons from the dissociating molecule in coincidence. We interpret the results using the potential energy surfaces extracted from multi-reference configuration interaction calculations. The measured particle energy distributions can be related to a super-excited monocationic state located above the double ionization threshold of D 2 O. The autoionized electron energy shows a sharp distribution centered around 0.5 eV, which is a signature of the atomic oxygen autoionization occurring in the direct and sequential dissociation processes of D 2 O + * at a large internuclear distance. In this way, an O + radical fragment and a low-energy electron are created, both of which can trigger secondary reactions in their environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Material Plasma Exposure eXperiment High Heat Flux Microwave Absorber Design, Manufacture, and Articles Test

The Material Plasma Exposure eXperiment (MPEX) at Oak Ridge National Laboratory is in the final design phase. MPEX will be capable of exposing neutron-irradiated materials to plasmas for the study of plasma-material interaction. This facility will provide information about the complex effects of plasmas on materials and contribute to examining new materials that can withstand high heat fluxes and high ion fluences for future fusion devices. MPEX plasma is heated by 70-GHz or 105-GHz electron Bernstein wave/electron cyclotron heating (ECH), and the high-frequency microwaves are prone to scattering microwave power, which can have detrimental effects, especially on diagnostic components. A large portion of the injected ECH power is expected to be absorbed by plasma, but the remainder requires that microwave absorbers be placed immediately upstream and downstream of the ECH launcher to minimize stray microwaves leaving the ECH region. These microwaves can inadvertently heat components that cannot be shielded or otherwise protected. The microwave absorber design is based on an array of pyramid-shaped ceramic tiles brazed to a water-cooled explosion-bonded heat sink and a stainless steel plate to produce one tile module. Computational fluid dynamics and structural analyses were performed to optimize and validate the design. Multiple test coupons were produced to validate the process for brazing the two different tile materials to the Glidcop AL-15 baseplate. The articles were tested to evaluate the reliability and thermal performance through exposure to an electron beam with a heat flux of up to 1.5 MW/m2. Nondestructive testing was performed before and after testing to identify voids or separations that may have been introduced by the high heat flux. This paper discusses the details of high heat flux microwave absorber design, manufacturing details and associated challenges, and test results, demonstrating the effectiveness of the proposed design.

Hussain, Aftab↗

Data for The Leaf Economics Spectrum of Triploid and Tetraploid C4 Grass Miscanthus x giganteus

The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C3 species grown under natural ecosystems. However, the specific contribution of C4 species to the global LES is studied less widely. C4 species have a CO2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M. × giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M. × giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C3 species to include C4 crops, these findings highlight that M. × giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

Biomass Analytics↗

Tritium Pressure Enhancement on the TPBAR Cladding by Physical Processes at the Getter

Tritium for the U.S. nuclear weapon stockpile is produced in tritium producing burnable absorber rods (TPBARs) inserted into Tennessee Valley Authoritys (TVA) light-water nuclear reactors. The rods are stainless steel tubes with a permeation barrier coating and internal components that generate and contain the tritium. The TPBAR incorporates a Ni-plated Zircoloy getter tube to capture tritium and prevent it from reaching the rod cladding and permeating into the environment. Under the conventional view of getter behavior, the tritium pressure outside the getter tube is expected to be limited to the equilibrium vapor pressure of Zr hydride at the temperature of the rod as long as the total hydrogen concentration remains below the capacity of the hydride. Since the tritium pressure is higher within the rod core, this behavior relies on the thin getters ability to hold off a differential tritium pressure. The effective tritium pressure on the cladding can also be enhanced by isotope exchange. Hydrogen ingress through the cladding from the reactor coolant creates a hydrogen pressure on the outer surface of the getter that can exchange with tritium, allowing the tritium partial pressure to increase toward this hydrogen gettering pressure. The goal of this work was to use laboratory-scale experiments to examine these mechanisms and create a model of getter behavior that describes tritium transport within the TPBAR. A third mechanism wherein the concentration at the outer surface of the getter is increased by the temperature gradient within the getter tube wall (the Soret effect) is not experimentally tested but is captured in the model. While not conclusively demonstrated by the experiments due to low pressure, high temperature, and small gap volume conditions, the model shows that when combined, the three mechanisms can explain both the magnitude and time dependence of the tritium release observed for reactor fuel assemblies with TPBARs. The model also shows how various modifications of the TPBAR design can reduce this tritium release into the environment.

07 ISOTOPE AND RADIATION SOURCES↗

Catalytic Membrane Reactors Based on Carbon Molecular Sieve Hollow Fiber Membranes for Sustainable and Modular H 2 Production

We aimed to develop a catalytic membrane reactor (CMR) that couples water–gas shift (WGS) reaction with in-situ H 2 separation to produce blue H 2 and a CO 2 -rich stream from coal- and biomass-derived syngas. Our core approach employs high-permeance carbon molecular sieve (CMS) hollow-fiber membranes (HFMs) with strong gas separation ability, which we further integrate into catalytic membrane reactors to intensify H 2 production and CO 2 capture in a single unit. Three organizations with complementary skills collaborated to achieve the goal, including the University at Buffalo (UB), Los Alamos National Laboratory (LANL), and Trimeric Corporation (Trimeric).

08 HYDROGEN↗

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗

Hybrid Cooling and Water Treatment for Resilient, Water-Self-Sufficient Data Centers

The continued growth of data center infrastructure is intensifying demand for freshwater resources, particularly in water-stressed regions, and is increasingly limiting sustainable capacity expansion. This work investigates a conceptual hybrid system that integrates freeze desalination with ultrasonic-assisted ice separation to enable on-site production of pure water from diverse sources, including seawater, brackish groundwater, and reclaimed industrial or agricultural wastewater. Simultaneously, the system produces low-temperature cooling streams that enhance heat removal in high power density computing environments. A process-level thermodynamic analysis is performed across a range of boundary and operating conditions, including variations in feed concentration, freezing temperature, and mass flow rate. The results are presented as performance curves relating feedwater concentration and target purified water output to the corresponding intake flow requirements, enabling estimation of source water demand per unit of Information Technology Equipment (ITE) energy consumption (kWh) across varying data center scales and operational scenarios. The corresponding electrical energy consumption for integrated cooling and water treatment is also evaluated as a function of system operating parameters and target water production levels. These results provide a basis for evaluating system feasibility across different conditions and for identifying parameter ranges in which integrated water treatment and cooling improve resource efficiency, thermal performance, and operational flexibility in data centers.

Elhefny, Aly [ORNL] (ORCID:0000000284907923)↗

Investigation of enhanced CO 2 storage in deep saline aquifers by WAG and brine extraction in the Minnelusa sandstone, Wyoming

Geological CO 2 sequestration in deep saline aquifers has been extendedly investigated to reach the goal of carbon neutral as large amount of CO 2 can be reduced in a short time. Here, this study investigates the feasibility of water-alternating-gas (WAG) injection and brine extraction on enhancing CO 2 storage in a target deep saline aquifer, Minnelusa Sandstone in the Powder River Basin (PRB) of Wyoming. An integrated numerical model is developed to account for four scenarios: (1) CO 2 continuous injection (CI) through one injection well, (2) WAG injection through one injection well, (3) CO 2 CI through one injection well and brine extraction through one producer, (4) WAG injection through one injection well and brine extraction through one producer. Simulation results suggest that WAG injection and brine extraction corporately make it possible to enhance CO 2 injectivity while securing CO 2 storage safety. For instance, WAG injection considerably reduces structural trapping contribution while enhances dissolved and residual trapping contributions. As for brine extraction, it can decrease the maximum averaged reservoir pressure by 37% and 22% for CI and WAG injection, respectively. Besides, sensitive analyses of the operational parameters for the fourth scenarios are performed. Results reveal that, when the amount of total CO 2 injection has been predetermined, CO 2 injection time and rate within each period of WAG should be small whereas it is preferable to have large water injection time and rate. This is to secure desirable dissolved and residual trapping contributions (store CO 2 with safety). Sensitive degree results confirm that CO 2 injection rate, water injection time, and CO 2 injection time of WAG injection exhibit significant effects on CO 2 storage whereas the impacts of producer bottom-hole pressure (BHP), water injection rate, and CO 2 -water injection time are relatively weaker. This study not only sheds light on achieving double-win goal: enhance CO 2 injectivity and store CO 2 with safety, but also can be a critical reference for other CO 2 storage in deep saline aquifers.

58 GEOSCIENCES↗

Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data

Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Morphology–Diffusivity Relationships in Fluorine-Free Random Terpolymers for Proton-Exchange Membranes

Here, using atomistic molecular dynamics simulations, we investigate the morphology and transport properties of a new family of fluorine-free terpolymers designed as proton-exchange membranes. Simulated random terpolymers consist of three monomers with a 5-carbon backbone with a phenylsulfonate, phenyl, or no pendant group and have ion exchange capacities (IECs) ranging from 1.06–4.14 mmol/g. At a hydration level of 9, cluster analysis reveals macrophase separation between water and terpolymers with IEC < 2.1 mmol/g and continuous, percolated hydrophilic and hydrophobic nanoscale domains at higher IECs. Channel width distribution analysis of the percolated morphologies revealed that more hydrophobic units produce less uniform channels. Decreasing the surface area per sulfonate group and increasing the fractal dimension of the hydrophilic domains correlate with increased water diffusivity, due to a more acidic interface and more isotropic water channels. Relative to the previously studied phenylsulfonate homopolymer, these terpolymers with lower IECs have only modestly lower water diffusion, and we anticipate other advantages related to processability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗