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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantifying Charge Carrier Localization in PBTTT Using Thermoelectric and Spectroscopic Techniques

Chemically doped poly[2,5-bis(3-alkylthiophen-2-yl)thieno[3,2- b ]thiophene] (PBTTT) shows promise for many organic electronic applications, but rationalizing its charge transport properties is challenging because conjugated polymers are inhomogeneous, with convoluted optical and solid-state transport properties. Herein, we use the semilocalized transport (SLoT) model to quantify how the charge transport properties of PBTTT change as a function of iron(III) chloride (FeCl 3 ) doping level. We use the SLoT model to calculate fundamental transport parameters, including the carrier density needed for metal-like electrical conductivities and the position of the Fermi energy level with respect to the transport edge. We then contextualize these parameters with other polymer-dopant systems and previous PBTTT reports. Additionally, we use grazing incidence wide-angle X-ray scattering and spectroscopic ellipsometry techniques to better characterize inhomogeneity in PBTTT. Our analyses indicate that PBTTT obtains high electrical conductivities due to its quickly rising reduced Fermi energy level, and this rise is afforded by its locally high carrier densities in highly ordered microdomains. Ultimately, this report sets a benchmark for comparing transport properties across polymer-dopant-processing systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Spatially Offset Femtosecond Stimulated Raman Spectroscopy: Observing Exciton Transport through a Vibrational Lens

To design better molecular electronic devices, we need a strong understanding of how charges or excitons propagate, as many efficiency losses arise during transport. Exciton transport has been difficult to study because excitons tend to be short-lived, have short diffusion lengths, and can easily recombine. Here, we debut spatially offset femtosecond stimulated Raman spectroscopy (SO-FSRS), a three-pulse ultrafast microscopy technique. By offsetting the photoexcitation beam, we can monitor Raman spectral changes as a function of both time and position. We used SO-FSRS on 6,13-bis(triisopropylsilylethynyl) pentacene, a well-studied organic semiconductor used in photovoltaics and field-effect transistors. Furthermore, we demonstrated that the fast exciton and free charge carrier transport axes are identical and observed that exciton transport is less anisotropic by a factor of ~3. SO-FSRS is the first technique that directly tracks molecular structural evolution during exciton transport, which can provide roadmaps for tailor-making molecules for specific electronic devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Mechanically and Thermally Robust Gel Electrolytes Built from A Charged Double Helical Polymer

Polymer electrolytes have received tremendous interest in the development of solid-state batteries, but often fall short in one or more key properties required for practical applications. Herein, a rigid gel polymer electrolyte prepared by immobilizing a liquid mixture of a lithium salt and poly(ethylene glycol) dimethyl ether with only 8 wt% poly(2,2′-disulfonyl-4,4′-benzidine terephthalamide) (PBDT) is reported. The high charge density and rigid double helical structure of PBDT lead to formation of a nanofibrillar structure that endows this electrolyte with stronger mechanical properties, wider temperature window, and higher battery rate capability compared to all other poly(ethylene oxide) (PEO)-based electrolytes. The ion transport mechanism in this rigid polymer electrolyte is systematically studied using multiple complementary techniques. Li/LiFePO 4 cells show excellent capacity retention over long-term cycling, with thermal cycling reversibility between ambient temperature and elevated temperatures, demonstrating compelling potential for solid-state batteries targeting fast charging at high temperatures and slower discharging at ambient temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temperature Dependent Local Atomic Structure and Vibrational Dynamics of Barium Hydride and Calcium Hydride

Solid-state ionic conductors that exhibit pure ionic transport of hydride anions are rare. Here, we investigate two alkaline earth metal hydrides, barium hydride and calcium hydride, using neutron scattering techniques to understand how the local atomic environment plays a role in the diffusion of hydride ions. At high temperatures, barium hydride exhibits exceptional transport properties with ionic conductivities that are higher than those of many of the typical proton and oxide ion conductors in use today. Total neutron scattering and pair distribution function analysis reveal how a structural phase transition converts barium hydride from a modest ionic conductor into a fast ionic conductor through the introduction of disorder, deuterium site splitting, and dynamic structural fluctuations. Furthermore, neutron vibrational spectroscopy is employed to probe changes in the temperature evolution of the lattice dynamics and local energy landscape. These results improve our fundamental knowledge of the interplay between structure and dynamics governing a rare conduction process of hydride ions in solid-state materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Materials Engineering for High Performance and Durability Proton Exchange Membrane Water Electrolyzers

Proton exchange membrane water electrolyzers (PEMWEs) are expected to play a crucial role in the global green energy transition during the 21st century. They provide a versatile and sustainable solution for generating hydrogen with very high purity in combination with renewable energies, such as solar and wind. Despite their promise, PEMWEs face several critical problems, including high costs, performance limitations, and durability challenges, particularly at low iridium (Ir) loading on the anode. Advancing next-generation PEMWEs requires extensive work on materials engineering of all cell components, including the catalyst layer (CL), membrane, porous transport layer (PTL), bipolar plate (BPP), and gasket. This task must be performed with the complementary contribution of different modeling and characterization techniques. This review presents a critical perspective from academia, research centers, and industry, mapping main developments, remaining gaps, and strategic pathways to advance PEMWE technology. A focus is devoted to key aspects, such as operation at low Ir loading, membrane durability, multiscale transport layers, porous and non-porous flow fields, multiphysics modeling, and multipurpose characterization techniques, which are thoroughly discussed. By unifying these topics, this review provides readers with the essential knowledge to grasp current developments and tackle tomorrow's challenges in PEMWE engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermodynamics, local structure, and transport of protons in triple-conducing oxide, BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY4411)

Triple-conducting oxides (TCOs) are an emerging class of mixed ionic and electronically conducting materials that show great promise for oxygen reduction/oxygen evolution (ORR/OER) electrocatalysis—primarily in high-temperature ceramic electrochemical cells— but also in aqueous alkaline environments. Their high activity is attributed, at least in part, to their ability to incorporate and transport three mobile charge carriers: protons, oxygen vacancies, and electron-holes Despite their promise, fundamental studies of TCOs are challenging, as transport dynamics from three charge carriers cannot be fully disentangled via traditional electrical measurement techniques. Characterizing proton dynamics in TCOs is particularly difficult as protons are generally the minority carrier, and their conduction response is typically obscured by the oxygen vacancies and electron holes. Here, we demonstrate successful isolation of the proton behavior in an archetypal TCO, BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY4411), using a combination of non-electrical techniques. We determine proton uptake and oxygen non-stoichiometry (δ) using thermogravimetric analysis (TGA). X-ray absorption near edge structure (XANES) and neutron diffraction (ND) are used to validate the oxidation state of Co and the δ values obtained through TGA. We apply 1H solid-state magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) to provide insights into local structure, dynamics, and proton kinetics. Finally, the proton transport properties are further quantified using tracer isotope exchange with time-of-flight secondary ion mass spectrometry (ToF-SIMS). Despite the very low proton concentrations in BCFZY4411 (<0.2% under most conditions), our analysis suggests that the oxygen Manuscript File Click here to view linked References 2 reduction and evolution reactions are nevertheless limited by the oxygen ion kinetics (e.g., oxygen surface exchange) rather than the proton kinetics at the reduced operating temperatures (<500 °C) that are targeted for electrochemical cell applications. These findings provide a comprehensive understanding of proton behavior in BCFZY4411 and pave the way for advancing the fundamental study of TCOs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Using Machine Learning to Understand Electric and Hybrid Vehicles Ownership in Burdened and Nonburdened Communities

Transitioning to electric and hybrid vehicles (EHVs) for all communities is a pivotal step toward sustainable transportation and environmental conservation. This paper aims to understand the adoption of EHVs, focusing on burdened communities (BCs) in the United States. The EHV ownership-based analysis combines two datasets—behavioral data from the Puget Sound Regional Travel Survey integrated with BCs (Justice40) data covering transportation insecurity, environmental burden, social vulnerability, health vulnerability, and climate and disaster risk burden. After creating this unique database, descriptive analysis and modeling are used to analyze the data and predict EHV ownership in the future. Specifically, we use a new method that combines particle swarm optimization (PSO) with a stacking model named PSO-Stacking, which incorporates heterogeneous base learners of machine learning and deep learning. PSO applies a customized objective function to select the optimal hyperparameters for heterogeneous learners within the stacking model, effectively addressing challenges such as multicollinearity, data imbalance, nonlinearity, and overfitting. The proposed solution covers more accurate results than standard benchmark models for EHV ownership in BCs and non-BCs. In addition, the results of the PSO-Stacking method are explained using the local interpretable model-agnostic explanations technique. Results show a negative correlation between the BCs indicators, that is, higher transportation insecurity associated with lower EHV ownership. Furthermore, BCs have higher future climate risk scores, diesel particulate matter levels, and PM2.5 in the air than non-BCs because of higher conventional vehicle ownership. These communities are at higher risk and can benefit from electrification, EV infrastructure, and EV policies to address environmental challenges.

Aslam, Zeeshan [ORNL]↗
DOE OSTI2026

Predicting river turbidity in Pine Island Bayou using machine learning techniques coupled with variational mode decomposition

Elevated turbidity levels pose significant public health risks by facilitating the transport of harmful pollutants, including metals, organic compounds, and pathogenic microorganisms into the surface water. These conditions create serious challenges for public recreational water use and drinking water treatment, leading to economic losses and health risks. This study utilizes water monitoring data in Pine Island Bayou, Texas, and develops a Sequence-to-Sequence (S2S) model to predict turbidity using Attention-based Gated Recurrent Units with Encoder-Decoder (AT-GRU-ED) and Long Short-Term Memory (LSTM), coupled with Variational Mode Decomposition (VMD). Compared to the model without VMD, the model demonstrates satisfactory 72-hour turbidity prediction performance, achieving MAEs of 2.60 and 3.29 NTU (reductions of 53% and 58%), RMSEs of 21.08 and 31.49 NTU (reductions of 82% and 80%), and R² values of 0.96 and 0.84 on the validation and test sets, respectively. Feature importance analysis reveals that water temperature is the dominant factor influencing seasonal turbidity patterns, while real-time hourly rainfall significantly contributes to short-term variability. Turbidity typically peaks within 48 hours after rainfall events due to lagged effects from surface runoff and upstream flow. Findings suggest suspending recreational water use and water supply pumping for three days after heavy rainfall can benefit public health and improve water treatment processes. Discharges above 100 m3/s are found to accelerate sediment dilution and transport, reducing turbidity levels more quickly after the peak. In conclusion, the proposed model demonstrates reliable 72-hour turbidity prediction, supporting decision-making for water treatment plant operations and providing early warning for public recreational water use.

Deep learning↗
DOE OSTI2024

Pore‐Scale Modeling of Carbon Dioxide and Hydrogen Transport During Geologic Gas Storage

Abstract Geologic storage of CO 2 and H 2 are climate‐positive techniques for meeting the energy transition. While similar formations could be considered for both gases, the flow dynamics could differ due to differences in their thermophysical properties. We conduct a rigorous pore‐scale study of water/CO 2 and water/H 2 systems at relevant reservoir conditions in a Bentheimer rock sample using the lattice Boltzmann method to quantify the effects of capillary, viscous, inertial, and wetting forces during gas invasion. At similar conditions, H 2 invasion is weaker compared to CO 2 due to unfavorable viscosity ratios. Increasing flow rate, however, increases the breakthrough saturation for both gas systems in the range of capillary numbers studied. At isolated conditions of flow rate, viscosity ratio, and wettability, local inertial effects are found to be critical and show consistent increase in the invaded gas saturation. The effect of inertial forces persits for both gases across all field conditions tested.

58 GEOSCIENCES↗
DOE OSTI2024

Gamma-Ray and Cosmic Ray Muon Modalities for Cargo Inspection

Screening and inspection of cargo containers are two essential methods to nondestructively examine the contents of shipment. These methods enable the detection of illicit transportation of unauthorized materials such as nuclear and radioactive materials, explosives, drugs, and so on, typically at borders or secure facilities. Although high-energy X-ray transmission is a standard system and is widely used for cargo inspection, the inherent challenges of high false-positive rates and high attenuation factors necessitate the development of complementary techniques that can increase the detection efficiency and accuracy in large and dense materials. Gamma-rays, which possess higher penetration characteristics because of their high energy, offer an alternative nonintrusive modality for cargo scanning. They represent a promising inspection method when compared to X-rays for three reasons: (1) improved ability to detect nuclear and radioactive materials, (2) higher inspection throughput rates, and (3) lower false-positive rates. Currently, there are two main gamma-ray inspection techniques, active and passive interrogation. Active interrogation can be further grouped into (1) gamma-ray transmission imaging and (2) neutron-induced gamma-ray emission detection. Gamma-ray transmission imaging utilizes differences in material densities for mapping the shipment contents and detecting anomalies. It is analogous to the X-ray transmission method; however, the high-energy photons make it more difficult to shield against, which enables more efficient performance in large and dense material inspection. Neutron-induced gamma-ray emission inspection is designed for the detection of nuclear and radioactive material because those materials emit characteristic gamma-rays when they are activated by neutron absorption. On the other hand, passive interrogation techniques rely on high-efficiency detectors to detect radiation emitted from hidden special nuclear or other radioactive materials. Similar to passive interrogation, cosmic ray muon monitoring and imaging are relatively new techniques that do not require external radioactive sources. These techniques have received attention as a potential next-generation radiographic probe to identify illicit transportation of nuclear and radioactive materials in cargo containers. Cosmic ray muons have unique features, (1) much higher energies than X-rays or gamma-rays (on the order of 10−1—104 GeV), (2) enhanced penetration capability, and (3) natural occurrence, thereby eliminating the need for induced radiation sources. These features enable cosmic ray muons to be utilized for detection of special nuclear materials in high-background-noise environments. By analyzing incoming and outgoing muon trajectories, scattering angles, and energies, it has been shown that it would be possible to locate hidden and well-shielded materials in cargo containers via three-dimensional muon tomography images or signal analysis. Gamma-rays, cosmic ray muons, and other nonintrusive cargo inspection modalities are complementary to each other, allowing them to address various cargo inspection conditions (i.e., scanning time, cost, radiation exposure level, and types of target materials). This chapter presents a detailed review of the theoretical fundamentals and technical principles behind the current gamma-ray and cosmic ray muon modalities for cargo inspection. Additionally, critical assessments and suggestions for the future directions to advance the use of gamma and muon modalities are discussed.

Bae, Junghyun↗
DOE OSTI2020

Enabling high rate capability, low internal resistance, and excellent cyclability for vanadium redox flow batteries utilizing ultrafast laser-structured graphite felt

The electrochemical performance of vanadium redox flow batteries (VRFBs) was enhanced via laser-patterned graphite felt (GF) electrodes. The laser-structured GF electrodes engineered via preparing a series of well-ordered microscopic channel structures with an average width of 200 μm, creating a three-dimensional carbon framework. The ultrafast laser patterning increased the porosity by 10%, as compared to pristine electrode. The analysis of the overpotential distribution using electrochemical impedance spectroscopy revealed that the electrode polarization involving charge transfer and diffusion resistance is strongly alleviated with the aid of carbon micro-perforation. The advanced design of laser-structured GF electrode also exhibits high rate capability, low internal resistance, and excellent cyclability. The improved performance was attributed to the synergistic effect involving (i) high electrochemically active surface area for rapid electrochemical reactions (i.e., V(II)/V(III) and V(IV)/V(V) redox couples) and (ii) excellent transport properties for facile electron/ion/species transport. The micro-scale channels created with the laser-ablation technique act as capillary structures and enabled homogeneous and rapid wetting of GF electrodes as formulated with the classical Washburn equation. The VRFB equipped with the laser-structured GF electrodes delivered a high discharge capacity with exceptional capacity retention upon extended cycling (>84.9%). In conclusion, accordingly, the design of laser-structured electrode paves the pathway towards finely tuning the electrode internal microstructure for improved cyclability, durability, and capacity retention in various electrochemical energy storage/conversion devices (e.g. all-vanadium redox flow batteries).

25 ENERGY STORAGE↗
DOE OSTI2021

Joining Light Metals with Polymer Composites Through Metal Overcasting

This work investigates a unique technique to join aluminum (Al) and magnesium (Mg) alloys to carbon fiber reinforced polymer (CFRP) composites without the use of adhesives or mechanical fasteners. The joints were made using an overcasting technique where the molten alloys were cast around the polymer composites using high pressure die casting method. Rapid cooling during casting allowed the composite to be embedded inside the cast metal without causing any gross damage to the former even though the molten metal temperature exceeded the melting point of the composite matrix by several 100’s of deg. C. The metal/composite interface was examined using optical microscopy and x-ray imaging and the joint strength was examined through tensile testing. Although evidence of polymer melting was evident in the x-ray images, the embedded section of the composite coupons retained their overall shape and integrity. Preliminary tension tests on Al/CFRP composites showed strength degradation of the CFRP and it failed near the metal/CFRP interface (outside the joint). Strength degradation in the CFRP suggests that the overcasting process needs further optimization to minimize thermal excursion in the CFRP. Nevertheless, the overcasting process shows great promise as a unique joining technique with application in fabricating light-weight structures for automotive and transportation industries.

overcasting, Casting, Mg Castings, Al Casting, Joi↗
DOE OSTI2024

A spatially-resolved model of neutron-irradiated tungsten coupling stochastic cluster dynamics and finite deformation plasticity

Structural materials used in nuclear reactors face severe degradation in mechanical properties, such as hardening and embrittlement. At the microscopic scale, this occurs due to creation and accumulation of irradiation-induced defects and their interaction with system dislocations. Although techniques exist which can model evolution of irradiation defects, for instance kinetic transport theory-based models, their interaction with mechanical deformation of the bulk material has not been investigated extensively. In this work, we demonstrate a novel spatially-resolved multiscale coupling between microscopic irradiation defect evolution, modeled using Stochastic Cluster Dynamics (SCD) and macroscopic mechanical deformation modeled using a finite-deformation plasticity model. SCD is used to determine the statistically averaged defect cluster spacing, dependent on operating conditions such as irradiation dose and temperature. This acts as an initial condition that governs the critical resolved shear stress of dislocation glide in the macroscopic plasticity model. This framework is used to predict mechanical behavior in post-mortem test of irradiated Tungsten samples, which has found its importance as structural material used in nuclear reactors. The results obtained using the coupled approach are in good agreement with experimental data of uniaxial tension tests. The model is able to capture the effect of temperature and irradiation dose on the material hardening. Two methods are proposed to estimate hardness – using Tabor's Law relating uniaxial yield stress to hardness and from flat-punch simulations. The results are in reasonable agreement with hardness data from micro-indentation experiments of irradiated Tungsten samples. Finally, the model is also able to reveal microstructural details such as spatial variation in defect density and local stress.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

A New General Paradigm for Understanding and Preventing Li Metal Penetration through Solid Electrolytes

The use of lithium (Li) or sodium (Na) metal anodes together with highly ion-conductive solid electrolytes (SEs) could provide batteries with a step improvement in volumetric and gravimetric energy densities. Unfortunately, these SEs face significant technical challenges, in large part because Li and Na dendrites can penetrate through SEs, leading to short circuits. The ability of such a soft material (Li or Na metal) to penetrate through ceramic is surprising from the point of view of models widely used in the Li-battery field. We introduce a concept, new to the battery field, for preventing penetration of lithium dendrites through SEs by putting the SE surfaces into a state of residual compressive stress. For a sufficiently high compressive stress, cracks have difficulty forming, and cracks that do form are forced to close, inhibiting dendrite penetration. This approach is widely used to solve commercially important stress corrosion cracking problems in metals and static fatigue problems in ceramics and glasses (e.g., Gorilla Glass). However, the technique will not be useful for SEs if the Li-ion transport rate through a SE is substantially reduced when the SE is under compression. Our molecular dynamics calculations for Li-ion transport through a common SE demonstrate that the introduction of even very high residual compressive stresses (~10 GPa) has only a modest effect on Li-ion transport kinetics, suggesting that this approach is viable and capable of providing a new paradigm for developing high-performance and mechanically stable SEs.

25 ENERGY STORAGE↗
DOE OSTI2025

Interactions between Per- and Polyfluoroalkyl Substances (PFAS) at the Water–Air Interface

Per- and polyfluoroalkyl substances (PFAS)--so-called “forever chemicals”--contaminate the drinking water of about 100 million people in the U.S. alone and are inefficiently removed by standard treatment techniques. A key property of these compounds that underlies their fate and transport and the efficacy of several promising remediation approaches is that they accumulate at the water−air interface. This phenomenon remains incompletely understood, particularly under conditions relevant to natural and treatment systems where water−air interfaces often carry significant loads of other organic contaminants or natural organic matter. To understand the impact of organic loading on PFAS adsorption, we carried out molecular dynamics simulations of PFAS at varying interfacial densities. We find that adsorbed PFAS form strong mutual interactions (attraction between perfluoroalkyl chains and electrostatic interactions among charged head groups) that give rise to ordered interfacial coatings. Furthermore, these interactions often involve near-cancellation of hydrophobic attraction and Coulomb repulsion. Our findings explain an apparent paradox whereby PFAS adsorption isotherms often suggest minimal mutual interactions while simultaneously displaying a high sensitivity to the composition and density of interfacial coatings. Consideration of the compounds present with PFAS at the interface has the potential to allow for more accurate predictions of fate and transport and the design of more efficient remediation approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Adaptive responses of marine diatoms to zinc scarcity and ecological implications

Scarce dissolved surface ocean concentrations of the essential algal micronutrient zinc suggest that Zn may influence the growth of phytoplankton such as diatoms, which are major contributors to marine primary productivity. However, the specific mechanisms by which diatoms acclimate to Zn deficiency are poorly understood. Using global proteomic analysis, we identified two proteins (ZCRP-A/B, Zn/Co Responsive Protein A/B) among four diatom species that became abundant under Zn/Co limitation. Characterization using reverse genetic techniques and homology data suggests putative Zn/Co chaperone and membrane-bound transport complex component roles for ZCRP-A (a COG0523 domain protein) and ZCRP-B, respectively. Metaproteomic detection of ZCRPs along a Pacific Ocean transect revealed increased abundances at the surface (<200 m) where dZn and dCo were scarcest, implying Zn nutritional stress in marine algae is more prevalent than previously recognized. These results demonstrate multiple adaptive responses to Zn scarcity in marine diatoms that are deployed in low Zn regions of the Pacific Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Statistically elucidated responses from low-signal contrast mechanisms in ultrafast electron microscopy

The emergence of ultrafast electron microscopy (UEM) has enabled the discovery of strongly correlated dynamic mechanisms, including electron–phonon coupling, structural phase transitions, thermal transport, and electromagnetic deflection. Most UEM systems operate stroboscopically, meaning that the technique is susceptible to artifacts, mistakes, and misinterpretation of the data due to extensive experimental effort. In contrast to the ultrafast designation, data acquisition is extraordinarily slow because the electron beam has significantly reduced signal compared to traditional transmission electron microscopy due to pulsing the electron beam. Consequently, the sample may drift, tilt, or undergo irreversible structural changes that are independent of the time-resolved dynamics throughout the experimental time frame. Furthermore, these datasets require significant user interpretation that can be problematic when proper controls are not implemented thoroughly. Here, we demonstrate a new algorithm designed to separate ultrafast structural dynamics from long-term artifacts using a LiNbO 3 sample experiencing electrically driven surface acoustic wave propagation. Additionally, we provide examples of the impact of user bias when analyzing the data and provide a methodology, which enables the extraction of time-resolved responses when the image signal is extraordinarily low. Overall, the goal of this publication is to provide methods that validate the experimental results and reduce researcher biases during UEM data interpretation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

An extended moments model of quantum efficiency for metals and semiconductors

The complexity of photocathode designs and detector materials, and the need to model their performance for short pulse durations, response to high frequency photons, presence of coatings and/or thinness of the absorptive layer, necessitates modifications to three-step and moments models of photoemission that are used in simulation codes. Here, methods to include input from computationally intensive approaches, such as density functional theory to model optical properties and transfer matrix approaches to treat emission from the surface or transport past coatings, by means of parametric models are demonstrated. First, a technique to accurately represent optical behavior so as to model reflectivity and penetration depth is given. Second, modifications to bulk models arising from the usage of thin film architectures, and a means to rapidly calculate them, is provided. Third, a parameterization to model the impact of wells associated with coatings and surface layers on the transmission probably is given. In all cases, the methods are computationally efficient and designed to allow for including input from numerically intensive approaches that would otherwise be unavailable for simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗