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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Measurements of He-Ar, He-N 2 , and He-air thermal creep slip and accommodation coefficients at high temperatures

Understanding gas flows in capillaries has many applications in modeling the transport of gases in nano-structured, porous, or fractured media. A network of capillaries can often approximate these media, and also information on gas-surface interactions obtained from capillary experiments can be used for modeling flows in these media. Experimental data on flows of different mixtures of He-Ar, He-N 2 , and He-air in the slip regime and in stainless steel capillaries at high temperatures were obtained by using a two-bulb apparatus. An accurate expression for the thermal creep slip coefficients with the Lennard-Jones potential parameters and diffuse-specular reflection gas-surface interaction conditions were then used to obtain the accommodation coefficients for the different gases. The experimental data are best described with values of accommodation coefficients in the range of 0.1–0.3 for He and 0.5–1.0 for Ar, N 2 , and air. Further, the use of values in this range is suggested for modeling gaseous flows in capillaries and nano-structured, porous, or fractured media if other direct measured values for a particular medium are unavailable.

42 ENGINEERING↗
DOE OSTI2022

A physics-based model of cladding wastage layer formation rate

In this report, lower length scale simulations to inform an engineering-scale model of fuel-cladding chemical interaction (FCCI) conducted under the auspices of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY22 are described. An overall strategy for the implementation of the BISON model is described, and the past and current lower length scale work on FCCI formation is put into the context of this overall strategy. Density functional theory and kinetic Monte Carlo simulations are used to determine the diffusion coefficient of neodymium in iron. Density functional theory calculations are also used to parameterize a parabolic approximation for the dependence of free energy on composition for the intermetallic compound Fe 17 Nd 2 . A phase-field model of the Fe-Nd system was developed that includes the random solid solution body-centered cubic phase and the intermetallic Fe 17 Nd 2 . The model was used to simulate growth of the intermetallic layer in a diffusion couple and the results were compared to experiment. The model’s prediction of the parabolic growth constant is within 40 % of the experimental value. The model is also used to simulate the formation of a grain boundary attack layer that is observed in experiment. The simulations show enhanced Nd concentration along the grain boundaries, but do not clearly show formation of a Fe 17 Nd 2 layer

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Crystallization of ApoA1 and ApoE4 Nanolipoprotein Particles and Initial XFEL-Based Structural Studies

Nanolipoprotein particles (NLPs), also called “nanodiscs”, are discoidal particles with a patch of lipid bilayer corralled by apolipoproteins. NLPs have long been of interest due to both their utility as membrane-model systems into which membrane proteins can be inserted and solubilized and their physiological role in lipid and cholesterol transport via high-density lipoprotein (HDL) and low-density lipoprotein (LDL) maturation, which are important for human health. Serial femtosecond crystallography (SFX) at X-ray free electron lasers (XFELs) is a powerful approach for structural biology of membrane proteins, which are traditionally difficult to crystallize as large single crystals capable of producing high-quality diffraction suitable for structure determination. To facilitate understanding of the specific role of two apolipoprotein/lipid complexes, ApoA1 and ApoE4, in lipid binding and HDL/LDL particle maturation dynamics, and to develop new SFX methods involving NLP membrane protein encapsulation, we have prepared and crystallized homogeneous populations of ApoA1 and ApoE4 NLPs. Crystallization of empty NLPs yields semi-ordered objects that appear crystalline and give highly anisotropic and diffuse X-ray diffraction, similar to fiber diffraction. Several unit cell parameters were approximately determined for both NLPs from these measurements. Thus, low-background, sample conservative methods of delivery are critical. Here we implemented a fixed target sample delivery scheme utilizing the Roadrunner fast-scanning system and ultra-thin polymer/graphene support films, providing a low-volume, low-background approach to membrane protein SFX. This study represents initial steps in obtaining structural information for ApoA1 and ApoE4 NLPs and developing this system as a supporting scaffold for future structural studies of membrane proteins crystalized in a native lipid environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Physics-based Induced Earthquake Forecasting: Process Understanding, and Hazards Mitigation

Disposal of saltwater co-produced with oil and gas is linked to elevated seismicity in the Central and Midwest US. There is a concern that these events may lead to widespread damage and an overall increase in seismicity. Thus an improved understanding of the spatially and temporally variable deformation and stress field associated with fluid injection operation is critically necessary for evaluating time-varying seismic hazards. Despite the improvements in seismic monitoring capacity and the resulting decrease in the magnitude detection threshold, estimates of induced earthquake probability remain elusive due to insufficient models incapable of accounting for the complex physics governing the process of induced seismicity. The proposed research effort will comprehensively analyze, integrate, and interpret geodetic, injection, and seismic data in the vicinity of the injection sites in Oklahoma to resolve the 4-dimensional distribution of pore pressure and stress in the shallow crust. This project, in particular, is focused on exploring the statistical relation between injection operation and increased earthquake hazard. The amplitude of and the extent to which pore pressure changes are determined by some factors, in particular, the hydrogeological properties of the rocks, such as diffusivity. Thus the available deformation data will be used to constrain hydrogeological properties of the medium, to accurately resolve the evolution of crustal stresses due to fluid injection. Having the time-varying models of stress changes, a statistical framework will be implemented to estimate the time-dependent probability of large earthquakes on the nearby fault systems. These data and models help to improve seismic hazard estimates and aid in constructing operational-induced earthquake forecast models. This information can also be integrated into the updated U.S. National Seismic Hazard Map, which local communities and authorities use in their earthquake risk estimates and mitigation efforts.

58 GEOSCIENCES↗
DOE OSTI2022

Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning

Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Probing soft X-ray induced photoreduction of a model Mn-complex at cryogenic conditions

Soft X-ray absorption spectroscopy of first row transition elements at their respective L -edges provides important information about the oxidation and spin states of the metal centers. However, the associated sample damage in radiation-sensitive samples substantially alters the electronic and chemical structures of redox-active metal centers. Here, we measure the soft X-ray spectrum of the model Mn III (acac) 3 complex containing a redox-active Mn III metal center in an octahedral environment with a superconducting transition-edge sensor detector. To reduce the secondary damage resulting primarily from the diffusion of radicals and electrons, the spectra are collected at 30 K and 80 K on solid samples. Starting from the first scan, we detect the contribution of X-ray induced sample damage leading to a change in the Mn II intensity. However, at low temperatures, particularly at 30 K, we do not observe a gradual increase in the radiation damage with successive scans with the X-ray beam at the same spot. At our estimated dose of 90 kGy, we find 62% of Mn III (acac) 3 is still intact at 30 K. However, at room temperature, we see a gradual increase in radiation damage with increasing numbers of scans at the same spot, which is consistent with the possibility of increased diffusion rates of secondary radicals and electrons as noted in other studies.

L-edge spectroscopy↗
DOE OSTI2024

Spectroscopic Analysis of Pu-bearing Compounds in Double-Walled Cells

Spectroscopic analysis of radiological materials has been historically limited to radiological labs with 11 older or less advanced scientific instrumentation. The development of double-walled cells (DWCs) at 12 the Savannah River National Laboratory (SRNL) has enabled Pu-bearing compounds to be removed 13 from radiological laboratories and studied in our radiologically clean spectroscopy lab with state-of14 the-art instrumentation. In this manuscript, we discuss the contributions of DWCs that have allowed 15 the application of Raman spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy 16 (DRIFTS), diffuse reflectance spectroscopy (DRS) in the shortwave infrared, and gamma 17 spectroscopy at SRNL. Significant advances have been made in the understanding of thermal 18 decomposition of Pu(III) and Pu(IV) oxalates, the alpha-induced damage to the PuO2 crystal lattice, 19 and the effect of calcination temperatures to the quality of PuO2. These techniques have enabled 20 methods to conduct PuO2 age dating since last calcination and estimate the calcination temperature 21 with Raman and DRS. Additional spectroscopic information measured with DRIFTS has provided a 22 path to observe the evolution of carbon species with calcination temperature while gamma 23 spectroscopy provides information on age dating since last purification.

Villa-Aleman, Eliel↗
DOE OSTI2024

Tractometry of the Human Connectome Project: resources and insights

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines. We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry—“Tractoscope” (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations

Gross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS- and GPP-related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP-only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates

ABSTRACT: Variation in the genome of Pseudomonas aeruginosa , an important pathogen, can have dramatic impacts on the bacterium’s ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based on their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical P. aeruginosa isolates using genomic information and corresponding virulence phenotypes in a mouse model of bacteremia. We defined the accessory genome of these isolates through the presence or absence of accessory genomic elements (AGEs), sequences present in some strains but not others. Machine learning models trained using AGEs were predictive of virulence, with a mean nested cross-validation accuracy of 75% using the random forest algorithm. However, individual AGEs did not have a large influence on the algorithm’s performance, suggesting instead that virulence predictions are derived from a diffuse genomic signature. These results were validated with an independent test set of 25 P. aeruginosa isolates whose virulence was predicted with 72% accuracy. Machine learning models trained using core genome single-nucleotide variants and whole-genome k-mers also predicted virulence. Our findings are a proof of concept for the use of bacterial genomes to predict pathogenicity in P. aeruginosa and highlight the potential of this approach for predicting patient outcomes. IMPORTANCE Pseudomonas aeruginosa is a clinically important Gram-negative opportunistic pathogen. P. aeruginosa shows a large degree of genomic heterogeneity both through variation in sequences found throughout the species (core genome) and through the presence or absence of sequences in different isolates (accessory genome). P. aeruginosa isolates also differ markedly in their ability to cause disease. In this study, we used machine learning to predict the virulence level of P. aeruginosa isolates in a mouse bacteremia model based on genomic content. We show that both the accessory and core genomes are predictive of virulence. This study provides a machine learning framework to investigate relationships between bacterial genomes and complex phenotypes such as virulence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Chemical structure and curing dynamics of bisphenol S, PEEK™-like, and resveratrol phthalonitrile thermoset resins

This effort provides a multifaceted analysis of the structural changes and material dynamics of thermally driven softening and curing of three distinct phthalonitrile (PN) resins that cross-link into thermally stable and oxidation-resistant thermosets. Although this material system has yielded a large subset of fire-retardant composites that require facile processing and low-temperature curing, to date, insufficient information had been available on the fundamental processes that drive their softening and curing stages. Our approach conducted a complementary analysis the chemistry, monomer mobility, and rheology of three PN polymers in order to correlate the curing processes with corresponding structural and behavioral transformations of thermosets. Here, we focused on PNs with a bisphenol S backbone, a bisphenol A (PEEK™-like) backbone, and a resveratrol backbone. We relied on quasi-elastic neutron scattering (QENS) in order to analyze the in situ dynamics and self-diffusion properties of PN monomers, and to track changes in their mobilities during cross-linking and staging. Our analysis facilitates proper control over the staging and final curing of these resins and enables more efficient processing of these thermosets.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quality Ranking of Unary Fluoride Salt Property Data in MSTDB-TP

Molten salt reactor developers rely on thermal property data to design, license and operate the reactors they are developing. The Molten Salt Thermal Database-Thermophysical Properties (MSTDB-TP) is being developed under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program and managed by Oak Ridge National Laboratory. The MSTDB-TP is intended to serve as a single source of measured thermophysical property values for a wide variety of molten salt systems available to researchers, molten salt reactor developers, and regulators. These properties include melting and boiling points, heat capacity, density, viscosity and thermal diffusivity and conductivity. Published measurements of molten salt properties are lacking for many salts and the data that are available are often inconsistent. This creates a challenge for MSR developers in determining which property values to select when designing their reactors. The MSDTDB-TP collects all available property data and down-selects to preferred data sets or correlations. It is the purpose of this work to apply a recently developed ranking system that indicates the quality of property values listed in the database to inform decisions about how to use the available data. Quality assessments and rankings are being applied to data in MSTDB-TP to provide an indication of the quality of the data available. A previous report detailed the ranking system that was followed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Sn-InAs Nanowire Shadow-Defined Josephson Junctions

Hybrid superconductor–semiconductor platforms are foundational to advancing quantum information technologies, motivating the integration of materials with clean interfaces, robust superconductivity, and scalable architectures. Here, in this work, we report the synthesis and analysis of inclined InAs nanowires, conformally coated with β-Sn shells. These nanowires extend in opposite in-plane directions, forming a self-aligned, criss-cross network. This enables the deterministic formation of nanowire-shadow Josephson junctions through angle-controlled, low-temperature Sn deposition. Structural characterization shows uniform polycrystalline β-Sn shells forming a sharp, diffusion-free interface with InAs. Low-temperature transport measurements reveal a hard induced superconducting gap ≈ 600 μeV, switching currents up to ≈ 500 nA, and parallel magnetic field resilience beyond 1T. These results establish β-Sn/InAs nanowire networks as a promising platform for superconducting qubits, low-noise microwave devices, and the exploration of exotic superconducting phases including triplet pairing and topological superconductivity.

B-Sn↗
DOE OSTI2023

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies

This report represents the milestone deliverable M2SF-23SN010301072 “Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies” The report provides a status update of FY23 activities for the work package Argillite Disposal work packages for the DOE-NE Spent Fuel Waste Form Science and Technology (SFWST) Program. Clay-rich geological media (often referred as shale or argillite) are among the most abundant type of sedimentary rock near the Earth’s surface. Argillaceous rock formations have the following advantageous attributes for deep geological nuclear waste disposal: widespread geologic occurrence, found in stable geologic settings, low permeability, self-sealing properties, low effective diffusion coefficient, high sorption capacity, and have the appropriate depth and thickness to host nuclear waste repository concepts. The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress (through experiment, modeling, and testing) in the study of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in clay/shale/argillaceous rock. International collaboration activities comprising field-scale heater tests, field data monitoring, and laboratory-scale experiments provide key information on changes to the engineered barrier system (EBS) material exposed high thermal loads. Moreover, consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the engineered barrier system (EBS) design concepts. Chemical and structural analyses of sampled bentonite material from laboratory tests at elevated temperatures are key to the characterization of thermal effects affecting bentonite clay barrier performance. The knowledge provided by these experiments is crucial to constrain the extent of sacrificial zones in the EBS design during the thermal period. Thermal, hydrologic, mechanical, and chemical (THMC) data collected from heater tests and laboratory experiments have been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches to assess issues on coupled processes involving porous media flow, transport, geomechanical phenomena, chemical interactions with barrier/geologic materials, and the development of EBS concepts. These lines of knowledge are central to the design of deep geological backfilled repository concepts where temperature plays a key role in the EBS behavior, potential interactions with host rock, and long-term performance in the safety assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Overview of Base Model in Parametric Studies Specific to Performance of U-Mo Plates

This paper provides an overview of the base model specifically developed to perform parametric sensitivity studies on the U-10Mo monolithic fuel system. U-Mo monolithic fuels are being considered for the conversion of test reactors into high-performance research reactors that operate using proliferation-resistant, low-enriched uranium (LEU) fuels. These plate-type fuels contain a high-density, low-enrichment fuel sandwiched between zirconium diffusion barriers and encapsulated in aluminum claddings. All U.S. high-performance research reactors have released the designs of their LEU monolithic fuel reactor cores. These designs include nearly 50 distinct fuel plate geometries with different operational parameters. Consequently, a single generic plate geometry representing all the extreme points in this design matrix is unrealistic. To evaluate the performance for various parameters, a set of sensitivity studies was performed. These studies considered various input parameters (i.e., geometric, operational, and material property-related). The results revealed valuable information about plate performance and the sensitivity of this performance to various modeling inputs. To establish a reference state for comparing these result, base model featuring representative irradiation conditions was developed. To capture in-reactor behavior accurately, incorporation of representative constitutive models capable of evolving properties with respect to temperature, irradiation time, and burnup was needed. The behavioral models considered burnup-dependent properties, swelling, creep, and degradation. This paper introduces the base model created for the parametric sensitivity studies. The detailed description of the procedure includes the model geometry, model discretization, thermo-mechanical coupling, material properties and behavioral models. This paper also provides selected results and assesses the performance of the base model.

42 ENGINEERING↗
DOE OSTI2021

Modeling of High-Temperature Corrosion of Zirconium Alloys Using the eXtended Finite Element Method (X-FEM)

Oxidation modeling in modern nuclear fuel performance codes is currently limited by the lack of coupling with mechanics, thus preventing proper description of how high-temperature oxidation impacts mechanical properties. This is mostly due to the fact that the finite difference formalism adopted in corrosion models is incompatible with the direct coupling with mechanics in the finite element modeling employed in modern nuclear fuel performance codes. In this study, a physically based zirconium alloy corrosion model called the Coupled-Current Charge Compensation (C4) model, which was initially developed for operating temperature conditions, has been updated to include high-temperature corrosion in order to provide additional critical information (e.g., oxygen concentration profile) under loss-of-coolant accident (LOCA) conditions—information lacking in existing empirical models. The C4 model was implemented in the MOOSE finite-element framework developed at Idaho National Laboratory, enabling it to be used in the BISON nuclear fuel performance code based on the MOOSE framework. To precisely track the different interfaces at a relatively low computational cost, the eXtended Finite Element Method (X-FEM) was applied in MOOSE. The model’s results were compared to those of existing empirical models as well as metallographic analysis of high-temperature oxidized Zircaloy-4 coupons. Oxygen diffusivities in the a and ß phases resulting from this comparison closely agree with those found in the literature. The C4 model implemented with X-FEM in MOOSE now has the capability to accurately predict oxide, oxygen-stabilized a, and prior ß phase layer growth kinetics under isothermal exposure at high temperature (1000–1500°C). Furthermore, in contrast with the empirical models, the C4 model accounts for the finite thickness of the fuel cladding. It can predict the oxygen concentration profile evolution through the whole cladding, enabling evaluation of the remaining ductile thickness—a crucial variable for modeling the mechanical behavior of the fuel cladding under LOCA. Furthermore, this implementation allows direct coupling with mechanics, at a low computing cost, using finite-element-based nuclear fuel performance codes such as BISON.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A fresh perspective on the role of band bending, and related contributors, in light-driven production of electricity and chemicals

It is widely known that semiconductor-based solar energy conversion could power our planet. This is in part because high-quality semiconductor structures are unrivalled in their ability to separate photogenerated electrons and holes. One effective approach to achieving this photoinduced charge separation relies on a phenomenon known as “band bending”. But details to justify why band bending results in photoinduced charge separation are more complex than often appreciated. This underappreciation is an impediment to the rational, hypothesis-driven design of next-generation approaches to solar energy conversion. Herein we show, by means of derivations rooted in physical chemistry, that several phenomena – not just band bending – can facilitate photoinduced charge separation, and that each is influenced by nonequilibrium species concentration and a parameter, such as diffusion coefficient or rate coefficient, that introduces dynamics. To help visualize the impact of each phenomenon, we introduce plots that depict their contributions as free energy, force, flux, force constant, and rate. We reveal that spatial dopant distributions that define band bending are predictors of initial photogenerated species transport rates. But charge separation alone does not guarantee high-efficiency operation. A photogenerated change in energy that is freely available to do useful work is also essential, and is strongly dependent on semiconductor optical properties and reaction kinetics. Notably, this information reveals that specificity of interfacial chemical reactions – even when they are not preceded by charge separation elsewhere – can result in efficient solar energy conversion. We expect that this tutorial will guide researchers in their pursuit to uncover new mechanisms for light to perform useful work.

14 SOLAR ENERGY↗
DOE OSTI2026

Monitored Fluctuating Hydrodynamics

We introduce a hydrodynamic framework for describing monitored classical stochastic processes. We study the conditional ensembles for these monitored processes—i.e., we compute spacetime correlation functions conditioned on a fixed, typical measurement record. In the presence of global symmetries we show that these conditional ensembles can undergo measurement-induced “sharpening” phase transitions as a function of the monitoring rate; moreover, even weak monitoring can give rise to novel critical phases, derived entirely from a classical perspective. We give a simple hydrodynamic derivation of the known “charge-fuzzy phase” for weakly monitored diffusive many-body quantum systems. We show that although the unmonitored symmetric and asymmetric exclusion processes are in different universality classes of transport, the fluctuations in their conditional ensembles flow to the same fixed point with emergent relativistic invariance under monitoring. On the other hand, weakly monitored systems with non-Abelian symmetries enter a novel strongly coupled fixed point with nontrivial dynamical exponent, which we characterize. Our formalism naturally accounts for monitoring general observables, such as currents or density gradients, and allows for a direct calculation of information-theoretic diagnostics of sharpening transitions, including the Shannon entropy of the measurement record.

classical statistical mechanics↗