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At least 1,513 records · Page 84

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

An electronic-structure-centered perspective is presented on permanent-magnet (PM) design, highlighting two key levers, that is, saturation magnetization (M s ), governed by 3d-band filling and exchange physics, and magnetocrystalline anisotropy energy (MAE), arising from spin-orbit coupling (SOC) on anisotropic orbital populations. Reviewing current practices, including DFT-based MAE/J ij extraction, atomistic-spin and micromagnetic modeling, and high-throughput machine learning (ML) pipelines, three bottlenecks limiting predictive discovery is identified that is i) electronic-structure accuracy for small MAE (sensitive to functional choice, Hubbard U, and many-body effects), ii) finite-temperature and kinetic realism (phonon/magnon renormalization, ordering kinetics), and iii) descriptor and multiscale decoupling (lack of SOC-weighted and orbital-resolved fingerprints). Deep dives into the electronic-structure of Nd─Fe─B and Fe─N show how these fingerprints govern magnetic performance, motivating DFT- and quantum-mechanics-based descriptors for discovery. Unbiased, structure-driven exploration, coupled with high-throughput simulations, ML, generative AI, and reasoning models, accelerates candidate identification and propagates insights across scales. Addressing supply-chain risks, on future needs of designing “critical-element-free” magnets with tailored microstructure and high energy products is emphasized. By integrating electronic fingerprints, AI reasoning, and multiscale modeling, a practical roadmap is provided for rare-earth-lean or rare-earth free, high-performance, sustainable PMs.

Singh, Prashant [Ames Laboratory, and Iowa State U↗

Unfolding of the Villin Headpiece Domain: Revealing Structural Heterogeneity with Time‐Resolved X‐Ray Solution Scattering and Markov State Modeling

Understanding protein folding pathways is crucial to deciphering the principles of protein structure and function. Here, the unfolding dynamics of the 35‐residue villin headpiece (HP35) and a norleucine‐substituted variant (2F4K) using a combination of experimental and computational techniques is investigated. Time‐resolved X‐ray solution scattering coupled with equilibrium molecular dynamics simulations and Markov state modeling reveals distinct unfolding mechanisms between the two variants: HP35 and 2F4K. Specifically, HP35 exhibits a two‐state unfolding process, whereas an intermediate state is identified for the 2F4K mutant. A Markov state model constructed from simulations is used to map atomic‐level transitions to experimental observations, providing insights into the role of sequence variations in modulating folding pathways. The findings underscore the importance of integrating experimental and computational approaches to unravel protein unfolding mechanisms between heterogenous structural ensembles.

Nijhawan, Adam K. [Department of Chemistry Northwe↗

Modeling, Validation, and Control of the IEA‐15 MW Reference Wind Turbine and VolturnUS‐S Platform

This paper presents the acausal modeling, validation, and control of floating offshore wind turbines (FOWTs). The model simulates the IEA‐15 MW reference turbine and the semi‐submersible VolturnUS‐S platform utilizing a Control‐oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS), which integrates the key coupled aero‐hydro‐elasto‐servo dynamics and is being developed by authors at the University of Central Florida. Verification and validation are conducted using numerical data from the industry‐standard simulation platform OpenFAST and experimental data from the Floating Offshore‐wind and Controls Advanced Laboratory (FOCAL) project, in which the authors were involved. Numerical results demonstrate the model's ability to qualitatively capture loads and responses across various load cases, highlighting the impact of the control system under different wind and wave conditions and opening new opportunities for optimizing FOWT designs. This paper provides wind turbine researchers with valuable insights into system characteristics, system frequencies, damping effects, and internal reaction forces, serving as a reference for future studies in FOWT modeling and control.

17 WIND ENERGY↗

Atmospheric teleconnection associated with the Atlantic multidecadal variability in summer: assessment of the CESM1 model

Observational analysis shows that the Atlantic multidecadal variability (AMV) is associated with climate variability in the Northern Hemisphere through a zonal atmospheric teleconnection extending from the North Atlantic Ocean and propagating eastward around the Northern Hemisphere. Here, we studied the fidelity of model simulations in reproducing the observed summer AMV and the associated impacts on the mid-latitude climate by analysing simulations using the National Centre for Atmospheric Research Community Earth System Model Version 1 (CESM1), including CESM1 North Atlantic idealized and pacemaker simulations, CESM1 large ensemble twentieth century uninitialized simulations and large ensemble initialized CESM1 decadal predictions. To further compare the fidelity of CESM1, we also analysed large ensemble simulations from three other models. Our results suggest that the uninitialized large ensemble simulations from all models can produce an AMV time evolution and its regional climate impacts similar to the observations to certain degree. By initializing the observed oceanic condition in decadal prediction simulations, the simulated AMV and its regional impacts are closer to the observed ones than those in uninitialized ensemble simulations. In addition, the pacemaker simulations that nudged the time-evolving observed North Atlantic sea surface temperature anomalies produce spatiotemporal characteristics of the AMV and AMV climate impacts closer to the observed ones than the uninitialized simulations. We conclude that although coupled models can produce AMV and its regional impacts similar to observed, proper initialization and bias correction of the sea surface temperature spatial and temporal structure can improve this capability.

Initialization↗

The atmospheric effect of aerosols on future tropical cyclone frequency and precipitation in the Energy Exascale Earth System Model

This study uses experiments from the Energy Exascale Earth System Model (E3SM) to compare the influence on tropical cyclone (TC) activity of: (i) the atmospheric effect of aerosols under specified sea-surface temperatures (SSTs); and (ii) the net effect of greenhouse gases (GhGs) (including changes in SSTs). The experiments were performed using the CMIP6 Shared Socioeconomic Pathway SSP5-8.5 emissions scenario with GhG-induced SST warming specified and atmospheric aerosol effects simulated but without explicit ocean coupling. Insignificant changes in global TC frequency are found in response to the atmospheric effect of future aerosols and GhGs, as significant regional responses in TC frequency counteract each other. Future GhGs contribute to more frequent TCs in the North Atlantic, and reductions over the Northwestern Pacific and Southern Indian Ocean. The atmospheric effect of future aerosols drives more frequent TCs over the Northwestern Pacific and reductions over the Northeast Pacific and North Atlantic. Along with increases in TC intensity, global TC precipitation (TCP) is projected to increase by 52.8% (14.1%/K) due to the combined effect of future aerosols and GhGs. Although both forcings contribute to TCP increases (14.7–19.3% from reduced aerosols alone and 28.1–33.3% from increased GhGs alone), they lead to different responses in the spatial structure of TCP. TCP increases preferentially in the inner-core due to increased GhGs, whereas TCP decreases in the inner-core and increases in the outer-bands in response to the atmospheric effects of decreased aerosols. These changes are distinct from those caused by aerosol-induced SST changes, which have been considered in other studies.

54 ENVIRONMENTAL SCIENCES↗

Linking classical PRA models to a dynamic PRA

Here, this paper presents a series of methods designed to incorporate classical Probabilistic Risk Assessment (PRA) models such as Event Trees (ETs) and Fault Trees (FTs) into dynamic PRA. In contrast to classical PRA, dynamic PRA couples stochastic methods with system simulators to determine the risks associated with complex systems such as nuclear power plants. Compared with classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the progression of the accident. As part of a dynamic PRA analysis, it is not uncommon that parts of the system to be analyzed might not require a computationally expensive simulation model. These parts could be in fact modeled by employing classical PRA models (e.g., a FT). Here, we present a set of methods and tools that can be used to link the most common classical PRA models (ETs, FTs, reliability block diagrams and Markov models) to simulation codes such as RELAP5-3D: creating a “hybrid PRA.” In order to show the potential of such an hybrid PRA we employ this method to verify ET modeling assumptions (e.g., success criteria) using a large break loss of coolant accident initiating event as a test case. In this respect, we link a set of FTs from the original PRA to the RELAP5-3D code and perform a hybrid PRA. The FTs are employed to model the control logic of several safety systems and to propagate component failures throughout the system. Provided the generated dynamic PRA data, we show how conservative assumptions in the original PRA can be identified and how such original PRA can be modified by updating success criteria captured by the set of RELAP5-3D simulation runs.

97 - MATHEMATICS AND COMPUTING↗

Permeate fluxes from desalination of brines and produced waters: A reactive transport modeling study

The increasing interest in the use of membrane systems to desalinate inland brackish water, agricultural drainage, and industrially produced wastewater demands improved means of predicting desalination system performance under variable feedwater compositions. The interaction among water flow, solute transport, and chemical composition in these systems impacts permeate flux evolution. Here, an established multicomponent reactive transport simulator that accounts for these coupled processes is applied to compute osmotic pressure and permeate fluxes in reverse osmosis (RO) systems. The model is first validated by predicting permeate fluxes for a set of benchtop crossflow experiments subject to a range of feed flow rates and compositions, under fouling and non-fouling conditions. Results compare favorably with measured data that show that solutions with similar total dissolved solids concentrations but different compositions result in different permeate fluxes. The model is then applied to predict permeate fluxes from the desalination of produced waters using a commercial spiral wound RO module. For NaCl-dominant brines, at total dissolved salt concentrations (TDS) below about 70 g/L, permeate fluxes are inversely proportional to water mole fraction as the latter is a reasonable approximation of water activity (i.e. ideal mixing). In the case of Ca–Cl-, Na–CO3- and Na–SO4-dominant brines below about 70 g/L TDS, this relationship does not hold as well and tends to overpredict osmotic pressure and thus underpredict permeate fluxes. However, the opposite becomes true at higher TDS values for typical produced waters. The scaling potential of these waters is also computed by allowing the precipitation of minerals above their saturation limit on the RO membrane. This work demonstrates how reactive transport models developed for the analysis of waters from geological systems can be extended to improve process design, optimization, and control in desalination systems from produced waters and beyond.

Molins, Sergi↗

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗

Methodology to evaluate design modifications intended to eliminate frosting and high discharge temperatures in air-source heat pumps (ASHPs) in cold climates

Air-source heat pumps (ASHPs) operating in cold climates experience problems with frosting and high refrigerant temperatures. These problems increase energy consumption, and their severity depends on the climatic conditions. In the present paper, a methodology for identifying the prevailing problem between frosting and high discharge temperatures is presented. Three performance indices, the frosting index (FI), the discharge index (DI), and the total loss index (TLI), are proposed to quantify the impacts of frosting and high discharge temperatures on the annual performance of ASHPs in different climatic conditions. The FI and DI show which problem (frosting or high discharge temperature) dominates, and the TLI indicates the combined effect of frosting and high discharge temperatures on the performance of an ASHP. A thermodynamic model of an ASHP coupled with the TRNSYS building simulation tool is used to estimate the performance of an ASHP and the proposed loss indices to estimate the impact of both frosting and high discharge temperatures for 45 cities in Canada. The results can be extended to other parts of the world that experience similar climatic conditions The results reveal that in cities in ASHRAE climatic zones 5 and 6 (classified as cold regions) where the ambient air temperatures are predominantly between -15 °C to 6 °C, ASHPs are heavily impacted by frosting. The problem of high discharge temperatures in ASHPs is predominant in cities in climate zones 7 and 8 (classified as very cold and subarctic regions) where the temperatures are frequently below -20 °C in winter. Among the cities considered, St. John, NL has the highest fraction of heating hours experiencing frosting (90 %), where the annual increase in energy consumption due to frosting is 13.5 % of the annual heating energy consumption. The highest annual increase in energy consumption due to high discharge temperatures is in Isachsen, NU (zone 8), where the increase is 30 % of the annual heating energy consumption. Based on the proposed indices, another index called the performance gain index (PGI) is created, which can be used as a first step to assess the energy-saving potential of design modifications applied to ASHPs to solve the problems of frosting and high discharge temperatures. The PGI will aid in developing climate specific ASHPs. One possible design modification is the use of a two-stage ASHP with an economizer. It is observed that the two-stage ASHP with economizer can mitigate high discharge temperatures and improve performance in very cold and subarctic regions (zones 7 and 8). However, it is not as beneficial in zones 5 and 6, where the impact of high discharge temperatures on performance is minimal and frosting dominates. Finally, a case study, using the PGI to evaluate the economic and environmental effectiveness of a two-stage ASHP with economizer is presented for the city of Saskatoon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Aerodynamic effects on outer ash deposition rates in second generation atmospheric pressure oxy-coal combustion systems

Recent measurements in scenarios representative of second generation atmospheric pressure oxy-coal combustion systems have shown a significant increase in ash deposition rates in comparison to combustion in air. However, the causative mechanisms behind this increase have not been well understood. To fill this void, well-characterized experiments including fuel and deposit particle size distributions (PSDs) were coupled with highly resolved numerical simulations to isolate the aerodynamic effects impacting the deposition process such that mechanisms could be hypothesized. Three combustion scenarios (AIR, OXY27, OXY70) spanning a factor of three variation in flue gas volumetric flow rates were simulated and the deposition characteristics (impaction rates, deposit PSD, temperature, residence times, capture rates) tracked/predicted using a customized deposition module. The measured deposit PSD was significantly different from the PSD of the parent fuel indicating significant physio-chemical transformations (coalescence and particle growth in particular) at play. The use of simplistic modeling approaches (swelling parameter variations) to model particle growth led to inaccurate deposit ash PSD and rate predictions. A more satisfactory agreement between the measurements and simulations was obtained when the functional form of the parent fuel PSD (spread parameter) was modified to conform closely to the deposit PSD while still ensuring the fidelity of temperature and velocity predictions. Based on the measured ash compositions, identical capture criteria were employed across all three scenarios. Here this study further supports the theory that the ash deposition rates in these systems are dominated by aerodynamic effects with the ash PSD playing a dominant role.

42 ENGINEERING↗

Multiphysics simulation of TRISO fuel compacts and the effects of homogenization on silver release predictions

This work studies the impact of explicit and homogenized modeling approaches on the multiphysics simulation of TRistructural ISOtropic (TRISO) fuel compacts in prismatic High Temperature Gas Reactors (HTGRs) and the silver release predictions. TRISO fuel compacts exhibit complex double heterogeneity that significantly affects heat conduction, neutron transport, and fission products release. In this work, we use Cardinal, a multiphysics tool based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to couple neutron transport and heat conduction. OpenMC is used for neutron transport and the MOOSE heat transfer module is used for the heat conduction. Then, we use BISON for the silver release predictions. Two different modeling approaches—explicit modeling of individual TRISO particles and homogenized representation using effective thermal properties—are compared at high TRISO packing fractions (20% and 40%) across varying power densities. Results demonstrate that homogenization significantly under-predicts peak temperatures, for the case of high power/TRISO, there is a difference of 83.73 K in the maximum temperature. Additionally, homogenization underestimates the silver release predictions compared to explicit modeling. Specifically, the temperature and power density differences lead to significant differences in silver release predictions. This work demonstrates the importance of accurately modeling heterogeneity of the TRISO particles to reliably predict fission product release and assess reactor safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydroxyl radical yields in the heavy ion radiolysis of water

The yields of hydroxyl radicals in the radiolysis of water with protons and carbon ions have been examined using experimental scavenging techniques coupled with Monte Carlo track simulations. Combined with previous results using helium ions, this set of data gives valuable information on the potential for radiation induced damage to biological systems for light ions with very different track structures. Carbon dioxide production from aerated formic acid solutions in concentrations ranging from 10 -3 to 1 M was used as a probe of hydroxyl radical yields from about 8 ns to 8 µs. Numerical interpolation of the results at slightly different ion energies in combination with data from gamma radiolysis allows for a systematic analysis of both track average and track segment yields. As expected, considerable track chemistry is found to occur on the nanosecond to microsecond time scales. Monte Carlo track simulations employing stochastic diffusion-kinetic calculations of product yields are found to reproduce experimental observations satisfactorily. The track simulations are used to extract hydroxyl radical kinetics in pure water at neutral conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Discovery of Stacking Heterogeneity, Layer Buckling, and Residual Water in COF-999-NH 2 and Implications on CO 2 Capture

Covalent organic frameworks (COFs), with their modular architectures and tunable functionalities, provide a versatile platform to design sorbents for the direct capture of CO 2 from air. Here, for this work, we combined density functional theory, molecular dynamics, and grand canonical Monte Carlo simulations with experiment to understand structural factors for furthering COF-999-NH 2 ’s performance as the precursor to COF-999 for direct air CO 2 capture. Small energy differences among laterally shifted stackings suggest intrinsic stacking heterogeneity. The simulations show pronounced layer buckling coupled to extensive amine–nitrile hydrogen bonding and persistent pore water, which initiates undesired polymerization and undermines uptake. The predicted presence of water is confirmed by subsequent experiments. These insights point to a single, actionable design rule: exclude retained water by introducing hydrophobic pore environments to maximize the CO 2 capture efficiency.

adsorption↗

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗

Grain boundary effects in high-temperature liquid-metal dealloying: a multi-phase field study

Abstract A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying, specifically considering the role of grain boundaries. A semi-implicit time-stepping algorithm using spectral methods is implemented, which enables simulating large 2D and 3D domains over long time scales while still maintaining a realistic interfacial thickness. Simulations reveal a mechanism of coupled grain–boundary migration to maintain equilibrium contact angles with the topologically complex solid–liquid interface, which locally accelerates diffusion-coupled growth of a liquid channel into the precursor. This mechanism asymmetrically disrupts the ligament connectivity of the dealloyed structure in qualitative agreement with published experimental observations. The grain boundary migration-assisted corrosion channels form even for precursors with small amounts of the dissolving alloy species, below the parting limit . The activation of this grain boundary dealloying mechanism depends strongly on grain boundary mobility.

36 MATERIALS SCIENCE↗

Global peak water limit of future groundwater withdrawals

Over the past 50 years, humans have extracted the Earth’s groundwater stocks at a steep rate, largely to fuel global agro-economic development. Given society’s growing reliance on groundwater, we explore ‘peak water limits’ to investigate whether, when and where humanity might reach peak groundwater extraction. Using an integrated global model of the coupled human–Earth system, we simulate groundwater withdrawals across 235 water basins under 900 future scenarios of global change over the twenty-first century. Here we find that global non-renewable groundwater withdrawals exhibit a distinct peak-and-decline signature, comparable to historical observations of other depletable resources (for example, minerals), in nearly all (98%) scenarios, peaking on average at 625 km 3 yr -1 around mid-century, followed by a decline through 2100. The peak and decline occur in about one-third (82) of basins, including 21 that may have already peaked, exposing about half (44%) of the global population to groundwater stress. Most of these basins are in countries with the highest current extraction rates, including the United States, Mexico, Pakistan, India, China, Saudi Arabia and Iran. Furthermore, these groundwater-dependent basins will probably face increasing costs of groundwater and food production, suggesting important implications for global agricultural trade and a diminished role for groundwater in meeting global water demands during the twenty-first century.

58 GEOSCIENCES↗

Robust and tunable oxide nanoscrolls for solar-driven H 2 generation and storage

Hydrogen gas is a promising alternative to fossil fuels due to its high energy output and environmentally safe byproducts. Various morphologies of photocatalytic materials have been explored for high-efficiency H 2 production, for instance, quasi-1D nanoscroll structures that provide a larger surface-to-volume ratio. Recently, we predicted layer-by-layer formation of stable oxide nanoscrolls directly from dichalcogenide precursors, eliminating the need for costly formation of two-dimensional oxides for a roll-up synthesis of nanoscrolls. Here, in this study, we evaluate the suitability of those oxide nanoscroll materials—MoO 3 , WO 3 , PdO 2 , HfO 2 , and GeO 2 —for solar-driven photocatalytic H 2 production and storage. Using excited state theory coupled with Bethe–Salpeter equation simulations, we discern their electronic and optical properties as a function of interlayer scroll spacing and find them to be highly conducive for solar-driven photocatalysis. Additionally, using ab initio molecular dynamics simulations, we show that they are also suitable for H 2 storage as the nanoscrolls exhibit an effective trapping of hydrogen, even in the presence of defects and vacancies in the oxides. This work thus demonstrates the discovery of robust and tunable oxide nanoscrolls as materials for advancing solar-driven hydrogen technologies.

Chemical compounds↗