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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,441 records · Page 80

The correlation of local deformation and stress-assisted local phase transformations in MMC foams

Cellular structures are of growing interest for industry, and are of particular importance for lightweight applications. In this paper, a special case of metal matrix composite foams (MMCs) is investigated. The investigated foams are composed of austenitic steel exhibiting transformation induced plasticity (TRIP) and magnesia partially stabilized zirconia (Mg-PSZ). Both components exhibit martensitic phase transformation during deformation, thus generating the potential for improved mechanical properties such as strength, ductility, and energy absorption capability. The aim of these investigations was to show that stress-assisted phase transformations within the ceramic reinforcement correspond to strong local deformation, and to determine whether they can trigger martensitic phase transformations in the steel matrix. To this end, in situ interrupted compression experiments were performed in an X-ray computed tomography device (XCT). By using a recently developed registration algorithm, local deformation could be calculated and regions of interest could be defined. Corresponding cross sections were prepared and used to analyze the local phase composition by electron backscatter diffraction (EBSD). The results show a strong correlation between local deformation and phase transformation. - Graphical abstract: Display Omitted - Highlights: • In situ compressive deformation on MMC foams was performed in an XCT. • Local deformation fields and their gradient amplitudes were estimated. • Cross sections were manufactured containing defined regions of interest. • Local EBSD phase analysis was performed. • Local deformation and local phase transformation are correlated.

36 MATERIALS SCIENCE↗

Phenomena Identification and Ranking Table (PIRT) for heat pipes

Heat pipes are advanced passive thermal management devices that utilize phase change and capillary action to achieve efficient heat transfer. However, due to the complexity of the phenomena coupled in heat pipes, including capillary, phase change, turbulence, and compressibility effects, there are high uncertainties in the predictability of their operational regimes and performance. This PIRT exercise, conducted as a collaborative effort involving the Department of Energy (DOE) Microreactor Program (MRP), the Nuclear Regulatory Commission (NRC), and university partners systematically identifies, reviews, and prioritizes critical phenomena affecting the operation of heat pipes based on their importance and knowledge levels. Additional analyses and discussion are provided for phenomena with high importance and low knowledge, such as wick de-wetting, critical heat flux, contact angles, and pressure dynamics. The discussions included the recognizing challenges and proposing future research directions for both modeling and simulation and experimental efforts. Additionally, the report addresses phenomena with medium importance and low knowledge that could impact heat pipe operation during non-normal or transient operation, including frozen startup, laminar to turbulent transition, geyser boiling, wick priming, underfilling conditions, surface roughness of the wick, NCGs trapped in the wick, and the timescales of startup and shutdown. In conclusion, this comprehensive evaluation serves as a valuable resource for guiding future research and development efforts, supporting the successful integration of heat pipes into critical applications such as nuclear reactors, and contributing to the advancement of heat pipe technologies in safety-critical industries.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Unsteady aerodynamic loads on pitching aerofoils represented by Gaussian body force distributions

The actuator line model (ALM) is an approach commonly used to represent lifting and dragging devices like wings and blades in large-eddy simulations (LES). The crux of the ALM is the projection of the actuator point forces onto the LES grid by means of a Gaussian regularisation kernel. The minimum width of the kernel is constrained by the grid size; however, for most practical applications like LES of wind turbines, this value is an order of magnitude larger than the optimal value that maximises accuracy. This discrepancy motivated the development of corrections for the actuator line, which, however, neglect the effect of unsteady spanwise shed vorticity. In this work we develop a model for the impact of spanwise shed vorticity on the unsteady loading of an aerofoil modelled as a Gaussian body force distribution, where the model is applicable within the regime of unsteady attached flow. The model solution is derived both in the time and frequency domain and features an explicit dependence on the Gaussian kernel width. We verify the model with ALM-LES for both pitch steps and periodic pitching. The model solution is compared with Theodorsen theory and validated with both computational fluid dynamics using body fitted grids and experiment. It is concluded that the optimal kernel width for unsteady aerodynamics is approximately 40 % of the chord. The ALM is able to predict the magnitude of the unsteady loading up to a reduced frequency of 𝑘 ≈ 0.2.

17 WIND ENERGY↗

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗

Photoexcited Phenyl Ring Twisting in Quinodimethane Dyes Enhances Photovoltaic Performance in Dye-Sensitized Solar Cells

Four metal-free organic quinodimethane-based dyes, which represent molecular building blocks for a new class of DSSC dyes, were studied here with the objective to improve their photovoltaic performance via molecular engineering strategies. Such strategies can only be systematic and successful if they are derived from knowledge-based paradigms that relate individual aspects of the molecular structure for a given class of dyes to their photovoltaic properties. The optical and electrochemical properties of these dyes were investigated experimentally by UV–vis absorption and emission spectroscopy, as well as cyclic voltammetry and electrochemical impedance spectroscopy. Density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations on these dyes complement these experiments. Among other results, this concerted experimental and computational study revealed that the dialkylaminophenyl moiety in these dyes exhibits a large twist as a result of its ground-to-excited-state optical transition. In particular, a near-perpendicular (88.98°) twist of the dimethylaminophenyl moiety relative to the π-bridging unit that connects the three aryl rings in 2 was observed upon formation of its photo-excited-state structure. Moreover, it was discovered that 2 affords the highest V OC and power-conversion efficiency (PCE) values among these dyes. The particularly high PCE for 2 was found to be due to this twisting of the phenyl ring, which blocks the pathway of electrons from TiO 2 to the donor, and hence suppresses undesirable electron recombination at the dye···TiO 2 interface. This diode-like effect minimizes undesirable electron-recombination effects and represents an unprecedented structure–property relationship that should be useful for the molecular engineering of larger chromophores in this class of dyes for DSSC applications.

14 SOLAR ENERGY↗

Rapid Mineral Precipitation During Shear Fracturing of Carbonate-Rich Shales

Target subsurface reservoirs for emerging low-carbon energy technologies and geologic carbon sequestration typically have low permeability and thus rely heavily on fluid transport through natural and induced fracture networks. Sustainable development of these systems requires deeper understanding of how geochemically mediated deformation impacts fracture microstructure and permeability evolution, particularly with respect to geochemical reactions between pore fluids and the host rock. Here, a series of triaxial direct shear experiments was designed to evaluate how fractures generated at subsurface conditions respond to penetration of reactive fluids with a focus on the role of mineral precipitation. Calcite-rich shale cores were directly sheared under 3.5 MPa confining pressure using BaCl 2 -rich solutions as a working fluid. Experiments were conducted within an X-ray computed tomography (xCT) scanner to capture 4-D evolution of fracture geometry and precipitate growth. Three shear tests evidenced nonuniform precipitation of barium carbonates (BaCO 3 ) along through-going fractures, where the extent of precipitation increased with increasing calcite content. Precipitates were strongly localized within fracture networks due to mineral, geochemical, and structural heterogeneities and generally concentrated in smaller apertures where rock:water ratios were highest. The combination of elevated fluid saturation and reactive surface area created in freshly activated fractures drove near-immediate mineral precipitation that led to an 80% permeability reduction and significant flow obstruction in the most reactive core. While most previous studies have focused on mixing-induced precipitation, this work demonstrates that fluid–rock interactions can trigger precipitation-induced permeability alterations that can initiate or mitigate risks associated with subsurface energy systems.

58 GEOSCIENCES↗

Coupled Climate Simulations With E3SM‐MMF

Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO 2 experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections.

E3SM↗

Autonomous and dynamic precursor selection for solid-state materials synthesis

Abstract Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and conditions to be tested. Here we introduce an algorithm (ARROWS 3 ) designed to automate the selection of optimal precursors for solid-state materials synthesis. This algorithm actively learns from experimental outcomes to determine which precursors lead to unfavorable reactions that form highly stable intermediates, preventing the target material’s formation. Based on this information, ARROWS 3 proposes new experiments using precursors it predicts to avoid such intermediates, thereby retaining a larger thermodynamic driving force to form the target. We validate this approach on three experimental datasets, containing results from over 200 synthesis procedures. In comparison to black-box optimization, ARROWS 3 identifies effective precursor sets for each target while requiring substantially fewer experimental iterations. These findings highlight the importance of domain knowledge in optimization algorithms for materials synthesis, which are critical for the development of fully autonomous research platforms.

36 MATERIALS SCIENCE↗

Atomic-scale understanding of oxide growth and dissolution kinetics of Ni-Cr alloys

Aqueous corrosion of metals is governed by formation and dissolution of a passivating, multi-component surface oxide. Unfortunately, a detailed atomistic description is challenging due to the compositional complexity and the need to consider multiple kinetic factors simultaneously. To this end, we combine experiments with a first-principles-derived, multiscale computational framework that transcends thermodynamic descriptions to explicitly simulate the kinetic evolution of surface oxides of Ni-Cr alloys as a function of composition, temperature, pH, and applied voltage. In the absence of pitting, we identify three distinct voltage regimes, which are kinetically dominated by oxide growth, dissolution, and competitive dissolution and reprecipitation. Evolving compositional gradients and oxide thickness are revealed, including a transition between a metastable Ni-Cr mixed oxide and a thick, porous Ni-dominated oxide. Beyond elucidating the underlying physics, we highlight the need for competing kinetics in models to properly predict the transition from passivation to corrosion. Our results provide a key step towards co-design of alloy composition alongside environmental conditions for sustainable use across a variety of critical energy and infrastructure applications.

36 MATERIALS SCIENCE↗

Targeted materials discovery using Bayesian algorithm execution

Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces. A popular strategy is Bayesian optimization, which aims to find candidates that maximize material properties; however, materials design often requires finding specific subsets of the design space which meet more complex or specialized goals. We present a framework that captures experimental goals through straightforward user-defined filtering algorithms. These algorithms are automatically translated into one of three intelligent, parameter-free, sequential data collection strategies (SwitchBAX, InfoBAX, and MeanBAX), bypassing the time-consuming and difficult process of task-specific acquisition function design. Our framework is tailored for typical discrete search spaces involving multiple measured physical properties and short time-horizon decision making. We demonstrate this approach on datasets for TiO 2 nanoparticle synthesis and magnetic materials characterization, and show that our methods are significantly more efficient than state-of-the-art approaches. Overall, our framework provides a practical solution for navigating the complexities of materials design, and helps lay groundwork for the accelerated development of advanced materials.

42 ENGINEERING↗

Understanding the performance of a bisphosphonate Ru water oxidation catalyst

Water oxidation catalysts (WOCs) create electrons that allow generating H 2 from water and sunlight, a promising process for the production of clean energy. Here, the mechanism of water oxidation mediated by Ru(2,2'-bipyridine-6,6'-diphosphonato)(4-picoline) 2 has been studied computationally to comprehend the results obtained in the experiments performed by the Concepcion and Grotjahn groups. Our study was performed at pH = 8 and 1. At pH = 8, the phosphonates are fully deprotonated and the catalysis, which is shown to be more energetically costly than that of the dicarboxylato Ru catalyst counterpart, takes place through a mechanism that involves a bimolecular interaction between two metal-oxo units (I2M). At pH = 1, only one of the phosphonates of the catalyst can deprotonate. After testing all possible pathways and comparing with experimental data, we conclude that the catalysis proceeds neither through a water nucleophilic attack nor via I2M, but rather we hypothesize that the rate-determining step involves both the catalyst and the ceric ammonium nitrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AI Driven Experiment Calibration and Control

One critical step on the path from data taking to physics analysis is calibration. For many experiments this step is both time consuming and computationally expensive. The AI Experimental Calibration and Control project seeks to address these issues, starting first with the GlueX Central Drift Chamber (CDC). We demonstrate the ability of a Gaussian Process to estimate the gain correction factor (GCF) of the GlueX CDC accurately, and also the uncertainty of this estimate. Using the estimated GCF, the developed system infers a new high voltage (HV) setting that stabilizes the GCF in the face of changing environmental conditions. This happens in near real time during data taking and produces data which are already approximately gain-calibrated, eliminating the cost of performing those calibrations which vary ±15% with fixed HV. We also demonstrate an implementation of an uncertainty aware system which exploits a key feature of a Gaussian process.

Britton, Thomas↗

Design studies and commissioning plans for plasma acceleration research station experimental program

Plasma acceleration research station is an electron beam driven plasma wakefield acceleration test stand proposed for CLARA facility in Daresbury Laboratory. In this paper, the interaction between the electron beam and the plasma is numerically characterised via 2D numerical studies by using VSIM code. The wakefields induced by a single bunch travelling through the plasma were found to vary from 200 MV/m to 3 GV/m for a range of bunch length, bunch radius, and plasma densities. Energy gain for the particles populating the bunch tail through the wakefields driven by the head of the bunch was demonstrated. After determining the achievable field for various beams and plasma configurations, a reference setting was determined for further studies. Considering this reference setting, the beam quality studies were performed for a two-bunch acceleration case. The maximum energy gain as well as the energy spread mitigation by benefiting from the beam loading was investigated by positioning the witness and driver bunches with respect to each other. Emittance growth mechanisms were studied considering the beam-plasma and beam-wakefield interactions. Eventually, regarding the findings, the initial commissioning plans and the aims for the later stages were summarised.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Two-state thermodynamics and the possibility of a liquid-liquid phase transition in supercooled TIP4P/2005 water

Water shows intriguing thermodynamic and dynamic anomalies in the supercooled liquid state. One possible explanation of the origin of these anomalies lies in the existence of a metastable liquid-liquid phase transition (LLPT) between two (high and low density) forms of water. While the anomalies are observed in experiments on bulk and confined water and by computer simulation studies of different water-like models, the existence of a LLPT in water is still debated. Unambiguous experimental proof of the existence of a LLPT in bulk supercooled water is hampered by fast ice nucleation which is a precursor of the hypothesized LLPT. Moreover, the hypothesized LLPT, being metastable, in principle cannot exist in the thermodynamic limit (infinite size, infinite time). Therefore, computer simulations of water models are crucial for exploring the possibility of the metastable LLPT and the nature of the anomalies. In this work, we present new simulation results in the NVT ensemble for one of the most accurate classical molecular models of water, TIP4P/2005. To describe the computed properties and explore the possibility of a LLPT, we have applied two-structure thermodynamics, viewing water as a non-ideal mixture of two interconvertible local structures (“states”). The results suggest the presence of a liquid-liquid critical point and are consistent with the existence of a LLPT in this model for the simulated length and time scales. We have compared the behavior of TIP4P/2005 with other popular water-like models, namely, mW and ST2, and with real water, all of which are well described by two-state thermodynamics. In view of the current debate involving different studies of TIP4P/2005, we discuss consequences of metastability and finite size in observing the liquid-liquid separation. We also address the relationship between the phenomenological order parameter of two-structure thermodynamics and the microscopic nature of the low-density structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quasioptical modeling of wave beams with and without mode conversion. IV. Numerical simulations of waves in dissipative media

We report the first quasi-optical simulations of wave beams in a hot plasma using the quasi-optical code PARADE (PAraxial RAy DEscription) [K. Yanagihara, I. Y. Dodin, and S. Kubo, Phys. Plasmas 26, 072112 (2019)]. This code is unique in that it accounts for inhomogeneity of the dissipation-rate across the beam and mode conversion simultaneously. We show that the dissipation-rate inhomogeneity shifts beams relative to their trajectories in cold plasma and that the two electromagnetic modes are coupled via this process, an effect that was ignored in the past. Additionally, we propose a simplified approach to account for the dissipation-rate inhomogeneity. This approach is computationally inexpensive and simplifies the analysis of actual experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Berni Julian Alder, theoretical physicist and inventor of molecular dynamics, 1925–2020

Berni Julian Alder, one of the leading figures in the invention of molecular dynamics simulations used for a wide array of problems in physics and chemistry, died on September 7th, 2020. His career, spanning more than 65 years, transformed statistical mechanics, many body physics, the study of chemistry and the microscopic dynamics of fluids, by making atomistic computational simulation (in parallel with traditional theory and experiment) a new pathway to unexpected discoveries. Among his many honors, the CECAM prize, recognizing exceptional contributions to the simulation of the microscopic properties of matter is named for him. He was awarded the National Medal of Science by President Obama in 2008.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗