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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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DOE OSTI2023

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

FY22 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY22. As an extension of the effort from FY21, this year’s work focuses primarily on the two-phase modeling of the NSTF using RELAP5-3D, particularly with the inclusion of the cavity model. The results from simulations were used to compare against experimental data for benchmarking purposes of the RELAP5 deck. Additionally, RELAP5 was used as a predictive tool to guide planned test operations and identify expected system behaviors. In the first part of this report, details are provided of the cavity omitted model where heat flux is applied directly as a boundary condition to the risers. The general trend predicted by the RELAP5 model matches that from the experimental data when a single-phase natural circulation flow is first established, followed by an oscillatory two-phase period and finally a stable two-phase flow. However, the onset of oscillations is predicted early by the model due to the smaller thermal mixing region in the tank. However, by expanding the simulated thermal mixing region in the tank, the onset of oscillations predicted by the model is able to match that from the experiment. These oscillations where studied in depth and are deduced to be flashing-induced instability. The model was then modified to simulate an accident scenario case where a representative heat load based on the full-scale Framatome’s 625 MW t SC-HTGR was applied directly to the riser channels. The simulated initial and boundary conditions were identical to those performed experimentally, facilitating direct comparisons between the predicted and experimental results. It was determined that the results showed some discrepancies remain, likely due to the overprediction of vapor generation rate by the computer model. In the second part of this report, the cavity model is re-introduced where it is observed that the RELAP5 prediction is now able to capture the major trends of the observed flow commonly observed during two-phase conditions. However, the onset of oscillations is once again predicted early by the model, possibly caused by the underprediction of heat loss from the heater and cavity. This is likely due to the omission of support structures in the cavity that can act as additional pathways for heat to escape to the environment. To overcome the underprediction of heat loss, part of the insulation surrounding the cavity side panels and the back of the heaters are removed to allow heat to escape directly to the environment, which then improves the RELAP5 prediction. Parametric studies are also performed to investigate the effects of heater power, tank inventory level, and tank gas space pressure on flow behaviors, also in direct comparison to conditions tested experimentally. User option-61 in the RELAP5-3D input deck, which changes the heat transfer coefficient correlations used for calculating the vapor generation, is also investigated where it is found that by enabling the option, the overall duration of oscillations is increased and matches that from the experiment better. The RELAP5 model is further benchmarked with a header inlet- throttling case where it is observed that the prediction from the model fails to capture some major features observed in the experiment. By using a modified loss coefficient curve for the valve, the accuracy of the prediction is improved where most of the major features observed in the experiment are predicted by the model. Lastly, the model is benchmarked with an inventory depletion scenario where it is observed that despite the modeling limitation of RELAP5, the prediction shows good agreement with the experimental data where major trends and features are captured by the model. Future work will see continued development of the current RELAP5-3D input deck of the NSTF to both improve the accuracy of the model’s predictive capability and continuing serving the experimental program. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

Abstract Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination

Mycobacterium tuberculosis (Mtb), the causative infectious agent of tuberculosis (TB), kills more individuals per year than any other infectious agent. Granulomas, the hallmark of Mtb infection, are complex structures that form in lungs, composed of immune cells surrounding bacteria, infected cells, and a caseous necrotic core. While granulomas serve to physically contain and immunologically restrain bacteria growth, some granulomas are unable to control Mtb growth, leading to bacteria and infected cells leaving the granuloma and disseminating, either resulting in additional granuloma formation (local or non-local) or spread to airways or lymph nodes. Dissemination is associated with development of active TB. It is challenging to experimentally address specific mechanisms driving dissemination from TB lung granulomas. Herein, we develop a novel hybrid multi-scale computational model, MultiGran, that tracks Mtb infection within multiple granulomas in an entire lung. MultiGran follows cells, cytokines, and bacterial populations within each lung granuloma throughout the course of infection and is calibrated to multiple non-human primate (NHP) cellular, granuloma, and whole-lung datasets. We show that MultiGran can recapitulate patterns of in vivo local and non-local dissemination, predict likelihood of dissemination, and predict a crucial role for multifunctional CD8+ T cells and macrophage dynamics for preventing dissemination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Unraveling the Mechanics: Computational Modeling of Residual Stresses in U10Mo Fuel with Aluminum Cladding

LEU (Low Enriched Uranium) plate-type fuel elements consist of a high-density, low-enrichment U–Mo alloy-based fuel foil encapsulated in an aluminum cladding and is fabricated through the Hot Isostatic Pressing (HIP) technique. Understanding the mechanism of possible failure modes of nuclear fuel is critical to mitigate potential consequences. One of the major contributing factors in various failure modes is stress and it greatly affects the integrity under temperature, pressure, and irradiation. These stresses could originate from various sources, including manufacturing, and operation, and can lead to deformation, cracking, or even complete failure of fuel elements. This study focuses on the development of a computational model that accurately predicts the residual stresses generated in the U10Mo fuel during fabrication. It has been observed that cladding creep has a substantial impact on the residual stresses in the U10Mo fuel post the HIP fabrication process. Furthermore, during the HIP bonding process the fuel plate system is heated to a temperature of 560 oC and as a result, the aluminum cladding transitions from (Al 6061-T6 to -O). This presents a challenge in capturing the change in material properties accurately. Therefore, a temperature dependent creep model such as hyperbolic sine creep model is considered to estimate the creep properties of the Aluminum cladding. The proposed calibrated creep model accurately predicts the residual stresses in the U10Mo fuel foil and agrees well with the experiments.

42 ENGINEERING↗
DOE OSTI2019

Multiscale Computational Model for Particle Size Evolution during Coprecipitation of Li-Ion Battery Cathode Precursors

Next generation lithium ion batteries require higher energy and power density, which can be achieved by tailoring the cathode particle morphology, such as particle size, size distribution, and internal porosity. All these morphological features are determined during the cathode synthesis process, which consists of two steps, (i) coprecipitation and (ii) calcination. Transition metal hydroxide precursors are synthesized during the coprecipitation process, whereas their oxidation and lithiation occur during calcination. The size and size distribution of crystalline primary and aggregated secondary particles and their internal porosity are determined during coprecipitation. Operating conditions of the chemical reactor, such as solution pH, ammonia concentration, and stirring speed control the final morphological features. Here, a multiscale computational model has been developed to capture the nucleation and growth of crystalline primary particles and their aggregation into secondary transition metal hydroxide precursor particles. The simulations indicate that increasing solution pH and decreasing ammonia concentration lead to smaller sizes of the secondary particles. Finally, a phase map has been developed that can help identify the synthesis conditions needed for a specified particle size and size distribution.

25 ENERGY STORAGE↗
DOE OSTI2024

Establishing a clostridia foundry for biosystems design by integrating computational modeling, systems-level analyses, and cell-free engineering technologies (Final Report)

Rapid population growth, a rise in global living standards, and economic competitiveness have intensified the need for sustainable, low-cost biofuels and bioproducts production. Industrial biotechnology using microbial cell factories – and waste and/or renewable feedstocks – is one of the most attractive approaches for addressing this need, particularly when large-scale chemical synthesis is untenable. Unfortunately, designing, building, and optimizing biosynthetic pathways in cells remains a complex challenge. With support from the Department of Energy, we worked to address this challenge in a new interdisciplinary venture that established the world’s first clostridial Foundry for Biosystems Design (cBioFAB). Working both in vitro (cell-free) and in vivo, the goal of this project was to interweave and advance state-of-the-art computational modeling, genome editing, omics measurements, systems-biology analyses, and cell-free technologies to expand the set of platform organisms that meet DOE bioenergy goals. Specifically, we manufactured fuel and chemical intermediates via existing and de novo pathways. This report covers the outcomes of our research project.

09 BIOMASS FUELS↗
DOE OSTI2024

Computational Modeling, Simulation, and Potential Applications of Optical Stochastic Cooling

With the rising demand for intense particles beams, much research is being conducted in the area of particle beam cooling. One of these methods, called Stochastic Cooling (SC) (developed at CERN in the 1970's), delivered a feedback method to improve the quality and lifetime of circulating proton beams by reducing their 6D phase-space and has been widely implemented in a number of hadron machines. However, traditional stochastic cooling schemes are limited by the bandwidth of microwave frequency systems. Optical Stochastic Cooling (OSC) is a promising extension of the stochastic cooling beam cooling technique. OSC instead uses optical wavelengths which allows for improved control and increased cooling but creates its own technical challenges. This lays out work conducted toward the experimental demonstration of OSC at Fermilab's Integrable Optics Test Accelerator (IOTA) storage ring. This includes the design and characterization of parts of the optical delay system, the development and validation of a high-fidelity computational model of the OSC process, and the investigations into possible applications of the OSC mechanism to advanced beam manipulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Computational modeling and validation of a modified Marple cascade impactor

Oak Ridge National Laboratory (ORNL) is investigating respirable aerosol fractions from failed high-burnup (HBU) commercial spent nuclear fuel (CSNF) rods (Montgomery et al., 2022). The work aims to characterize the source term of radioactive aerosols that could result from mechanical failure and handling of failed fuel rods during storage and/or transportation. The experiment involves capturing and characterizing aerosols from a four-point bending experiment of fueled rod segments at ORNL’s Irradiated Fuels Examination Laboratory (IFEL). For this, a Marple cascade impactor (Series 290) with the ability to collect particles up to aerodynamic equivalent diameters of ~15 μm was tested for feasibility. The commercially available Marple cascade impactor design was modified for the experiment, where the cascade inlet was replaced with a 3D printed inlet nozzle. Collection efficiency curves were then generated with the modified impactor, and the cascade’s performance was tested using ISO dust capture experiments followed by SEM analysis of the collection and computational modeling. The current work highlights the performance testing and experimental validation of this modified Marple Impactor for spent nuclear fuel aerosol collection.

Kumar, Vineet↗
DOE OSTI2016

Computational modeling predicts simultaneous targeting of fibroblasts and epithelial cells is necessary for treatment of pulmonary fibrosis

Pulmonary fibrosis is pathologic remodeling of lung tissue that can result in difficulty breathing, reduced quality of life, and a poor prognosis for patients. Fibrosis occurs as a result of insult to lung tissue, though mechanisms of this response are not well-characterized. The disease is driven in part by dysregulation of fibroblast proliferation and differentiation into myofibroblast cells, as well as pro-fibrotic mediator-driven epithelial cell apoptosis. The most well-characterized pro-fibrotic mediator associated with pulmonary fibrosis is TGF-β1. Excessive synthesis of, and sensitivity to, pro-fibrotic mediators as well as insufficient production of and sensitivity to anti-fibrotic mediators has been credited with enabling fibroblast accumulation. Available treatments neither halt nor reverse lung damage. In this study we have two aims: to identify molecular and cellular scale mechanisms driving fibroblast proliferation and differentiation as well as epithelial cell survival in the context of fibrosis, and to predict therapeutic targets and strategies. We combine in vitro studies with a multi-scale hybrid agent-based computational model that describes fibroblasts and epithelial cells in co-culture. Within this model TGF-β1 represents a pro-fibrotic mediator and we include detailed dynamics of TGFβ1 receptor ligand signaling in fibroblasts. PGE 2 represents an anti-fibrotic mediator. Using uncertainty and sensitivity analysis we identify TGF-β1 synthesis, TGF-β1 activation, and PGE 2 synthesis among the key mechanisms contributing to fibrotic outcomes. We further demonstrate that intervention strategies combining potential therapeutics targeting both fibroblast regulation and epithelial cell survival can promote healthy tissue repair better than individual strategies. Combinations of existing drugs and compounds may provide significant improvements to the current standard of care for pulmonary fibrosis. In conclusion, a two-hit therapeutic intervention strategy may prove necessary to halt and reverse disease dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Computational Modeling, Simulation and Analysis of the RPI Walthousen Reactor Critical Facility (RCF)

The Walthousen Reactor Critical Facility (RCF), located in Schenectady, New York, is currently owned and operated by Rensselaer Polytechnic Institute (RPI). The facility was originally constructed by the American Locomotive Company (ALCO) for the research and development of small, portable reactors. Originally designed for highly-enriched uranium fuel, the prototype reactor first came online in August 26, 1956, and was transferred to RPI ownership in 1963. Several changes to the reactor's design and operation have been made, the most notable of which was the conversion from high-enriched uranium to low-enriched uranium fuel. The RCF is an open-pool critical assembly that operates at a low power with a license limit of less than 100 watts. This low operating power permits a much greater flexibility in configuration and operation as compared to other research reactors. Because of this, experiments may be designed that would be unfeasible for research reactors that operate at much higher powers. The RCF's functional capabilities provide opportunities to perform several reactor experiments and measurements, such as: core criticality experiments, differential and integral rod worth measurements, moderator temperature coefficient of reactivity calculations, critical rod height and critical water height measurements, etc.. These experiments are regularly performed in conjunction with RPI course-work education and Senior Reactor Operator (SRO) training. The unique capabilities and experiments that may be performed in the RCF are particularly useful for validating certain aspects of computational analysis codes. A computational model of the RCF reactor has been previously generated and validated using the Monte Carlo N-Particle (MCNP) code. For the purpose of future experiments, this model is also being adapted for use with the SHARP Toolset, which includes the PROTEUS neutronics code, the Nek5000 fluid dynamics code, and the Diablo structural mechanics code. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Synthesis, characterization, and computational modeling of 6,6'-(((2-hydroxyethyl)azanediyl)bis(methylene))bis(2,4-di-tert-butylphenol) modified group 4 metal alkoxides

The coordination behavior of the tridentate alkoxy ligand 6,6'-(((2-hydroxyethyl)azanediyl)bis(methylene)) bis(2,4-di-tert-butylphenol) (termed H 3 -AM-DBP 2 ) with group 4 metal alkoxides ([M(OR) 4 ]) in a 1:1 ratio was previously found to generate [(ONep)Ti(κ 4 (O,O’,O”,N)-AM-DBP2)] and [(OR)Zr(κ 4 (μ-O,O’,O”,N)-AM-DBP 2 )] 2 (M = Zr, Hf). Additional studies revealed that increasing the stoichiometric ratio to 1:2 H3-AM-DBP 2 :[M(OR) 4 ] led to the isolation of [(ONep)Ti(κ 4 (μ-O,O’,O”,N)-AM-DBP2)(μ-ONep)Ti(ONep) 3 ] (1)•tol, [(OBu t)Zr(κ 4 (μ-O,O’,O”,N)-AM-DBP2)(μ-OBu t)Zr(OBu t )3] (2) and [(OBu t)Hf(κ 4 (μ-O,O’,O”,N)-AM-DBP2)(μ-OBu t )Hf(OBu t ) 3 ] (3). The asymmetric dinuclear complexes of 1-3 resemble the chelation of a [M(OR) 4 ] moiety to a “(OR)M(κ 4 (O,O’,O”,N)-AM-DBP 2 )” fragment. The metal complexed by the AM-DBP 2 ligand has a pseudo octahedral geometry while the other metal adopts an intermediate trigonal bipyramidal (TBP-5)/square base pyramidal (SBP-5) geometry for 1 but a distorted SBP-5 for both 2 and 3. The structure and properties of 1-3 were analyzed by computational modeling and fully characterized by standard analytical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

SST-GPU: An Execution -Driven CUDA Kernel Scheduler and Streaming-Multiprocessor Compute Model

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of massive amounts of data have created a space for massively parallel acceleration where the context for thousands of concurrent threads are resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. The design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. To address the need for a scalable, decentralized GPU model that can model large GPUs, chiplet-based GPUs and multi-node GPUs, this report details the first steps in integrating the open-source, execution driven GPGPU-Sim into the SST framework. The first stage of this project, creates two elements: a kernel scheduler SST element accepts work from SST CPU models and schedules it to an SM-collection element that performs cycle-by-cycle timing using SSTs Mem Hierarchy to model a flexible memory system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗
DOE OSTI2015

Review of the synergies between computational modeling and experimental characterization of materials across length scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends in which predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure–property relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to “simply” support experimental work. This is illustrated by examples from several application areas on structural materials. In conclusion this manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.

3-D microstructure characterization↗
DOE OSTI2017

Interfacial Structure and Electric Field Probed by in Situ Electrochemical Vibrational Stark Effect Spectroscopy and Computational Modeling

Interfacial electric fields play crucial roles in electrochemistry, catalysis, and solar energy conversion. Understanding of the interfacial electric field effects has been hindered by the lack of a direct spectroscopic method to probe of the interfacial field at the molecular level. Here, we report the characterization of the field and interfacial structure at Au/diisocyanide/aqueous electrolyte interfaces, using a combination of in situ electrochemical vibrational sum frequency generation (SFG) spectroscopy, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. For 1,4-phenylene diisocyanide (PDI), 4,4'-biphenyl diisocyanide (BPDI), and 4,4"-p-terphenyl diisocyanide (TPDI), our results reveal that the frequency of the gold-bound NC stretch mode of the diisocyanide self-assembled monolayer (SAM) increases linearly with the applied potential, suggesting that SFG can be an in situ probe of the strength of the electric field at electrode/electrolyte interfaces. Using DFT-computed Stark tuning rates of model complexes, the electric field strength at the metal/SAM/electrolyte interfaces is estimated to be 108–109 V/m. The linear dependence of the vibrational frequency (and field) with applied potential is consistent with an electrochemical double-layer structure that consists of a Helmholtz layer in contact with a diffused layer. The Helmholtz layer thickness is approximately the same as the molecular length for PDI, suggesting a well-ordered SAM with negligible electrolyte penetration. For BPDI and TPDI, we found that the Helmholtz layer is thinner than the monolayer of molecular adsorbates, indicating that the electrolyte percolates into the SAM, as shown by molecular dynamics simulations of the Au/PDI/electrolyte interface. The reported analysis demonstrates that a combination of in situ SFG probes and computational modeling provides a powerful approach to elucidate the structure of electrochemical interfaces at the detailed molecular level.

Ge, Aimin↗
DOE OSTI2024

Computational modeling of phononic pseudocrystal isolators

Methods for the efficient computational prediction of the performance of phononic pseudocrystals (structured materials capable of blocking extraordinary ranges of frequency) in COMSOL and other comparable finite element method codes are set forth. These methods include boundary conditions that make possible halving the size of the computational domain. Also included is an introduction of elastic energy density methods for assessing the extinction of elastic waves within the patterned region.

Swift, Stephen Hales↗