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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identifying Hot Spots and Hot Moments of Metabolic Activity in Salt Marsh Sediments through BONCAT-FISH Microscale Mapping (Final Technical Report)

Understanding the biogeography and timing of microbial metabolic activity is a key priority for microbial ecologists. With such knowledge, the cumulative biogeochemical contributions of microbial communities become more predictable, and our ability to both understand the effects of environmental change on microbial activity and build synthetic communities with desired functions will increase substantially. In this project, we advanced this broad, ambitious goal in two substantial ways: we developed a multiplexed Fluorescence In Situ Hybridization (FISH) approach that links microbial identity with metabolic function, and we established a novel Bio-Orthogonal Non-Canonical Amino acid Tagging (BONCAT) technique that can resolve the timing of anabolic activity, providing new resolution of when microbial constituents are growing. We deployed both of these techniques in multiple environmental settings to demonstrate their versatility. At the Little Sippewissett Salt Marsh, we combined a novel dual-BONCAT technique with fluorescence activated cell sorting to determine which population of cells was metabolically active during the day and which was active during the night. We found that Methylobacterium was active during daylight hours, potentially feeding on carbon-rich molecules released from plant roots. Sulfur-cycling microbes dominate the population active during the dark night-time hours. Overall, the work conducted under the auspices of this project developed two promising new techniques for identifying the “hot spots” and “hot moments” of microbial activity in complex communities with taxonomic and functional resolution. We focused largely on a salt marsh sediment context, but are confident that microbial ecologists seeking to understand the microbial role in biogeochemical cycles in a wide range of settings will find our newly developed techniques useful in future work.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Single-Atomic Site Catalyst Enhanced Lateral Flow Immunoassay for Point-of-Care Detection of Herbicide

Point-of-care (POC) detection of herbicides is of great importance due to their impact on the environment and potential risks to human health. Here, we design a single-atomic site catalyst (SASC) with excellent peroxidase-like (POD-like) catalytic activity, which enhances the detection performance of corresponding lateral flow immunoassay (LFIA). The iron single-atomic site catalyst (Fe-SASC) is synthesized from hemin-doped ZIF-8, creating active sites that mimic the Fe active center coordination environment of natural enzyme and their functions. Due to its atomically dispersed iron active sites that result in maximum utilization of active metal atoms, the Fe-SASC exhibits superior POD-like activity, which has great potential to replace its natural counterparts. Also, the catalytic mechanism of Fe-SASC is systematically investigated. Utilizing its outstanding catalytic activity, the Fe-SASC is used as label to construct LFIA (Fe-SASC-LFIA) for herbicide detection. The 2,4-dichlorophenoxyacetic acid (2,4-D) is selected as a target here, since it is a commonly used herbicide as well as a biomarker for herbicide exposure evaluation. A linear detection range of 1-250 ng/mL with a low limit of detection (LOD) of 0.82 ng/mL has been achieved. Meanwhile, excellent specificity and selectivity towards 2,4-D have been obtained. The outstanding detection performance of the Fe-SASC-LFIA has also been demonstrated in the detection of human urine samples, indicating the practicability of this POC detection platform for analyzing the 2,4-D exposure level of a person. We believe this proposed Fe-SASC-LFIA has potential as a portable, rapid, and high-sensitive POC detection strategy for pesticide exposure evaluation.

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

Propane Activation on Pt Electrodes at Room Temperature: Quantification of Adsorbate Identity and Coverage

Abstract C−H bond activation is the first step in manufacturing chemical products from readily available light alkane feedstock and typically proceeds via carbon‐intensive thermal processes. The ongoing emphasis on decarbonization via electrification motivates low‐temperature electrochemical alternatives that could lead to sustainable chemicals production. Platinum (Pt) electrocatalysts have shown activity towards reacting alkanes; however, little is known about propane electrocatalytic activation and conditions suitable for enabling selective oxidation to valuable products. Herein, we utilize a combination of electrochemical mass spectrometry (ECMS) and density functional theory (DFT) calculations to elucidate the potential dependence of propane activation on Pt electrocatalysts. Results show a strong dependence of adsorption on the applied potential in room‐temperature aqueous acidic electrolyte, with a maximum coverage of propane‐derived adsorbates at 0.30 V vs RHE. Using charge deconvolution and deuterated experiments, the mechanism of adsorption was elucidated, and C 3 H 2 * was determined as the average dehydrogenated propane‐derived adsorbate species. DFT calculations further corroborate these results, showing that the formation of deeply dehydrogenated species is energetically accessible at room temperature. The combined theoretical and experimental findings yield insights for selective activation of paraffinic C−H bonds at room temperature, aqueous conditions—a critical step towards decarbonized chemical manufacturing.

Chemistry↗
DOE OSTI2022

Investigating Deposition Sequence During Synthesis of Pd/Al2O3 Catalysts Modified with Organic Monolayers

Modification of supported metal catalysts with self-assembled monolayers (SAMs) has been shown to improve selectivity and turnover frequencies (TOFs) for many catalytic reactions. However, these benefits are often accompanied by a decrease in overall mass activity due to partial blocking of active sites by the monolayers. Therefore, a potential method for increasing site accessibility is to deposit the active metal (e.g., Pd) after deposition of a SAM modifier on the support material. In this work, Pd/Al2O3 catalysts were synthesized using both a conventional, "metal-first" sequence in which the phosphonic acid (PA) SAM was deposited on Pd/Al2O3 and a "SAM-first" technique in which the ligands were deposited onto the support prior to deposition of the metal. Although metal-first catalysts showed a significant increase in TOF during benzyl alcohol HDO, they exhibited only a modest increase in overall mass activity due to a decrease in the number of active sites. Meanwhile, SAM-first catalysts showed similar improvements in TOF and toluene selectivity but exhibited significantly improved HDO rates compared to metal-first catalysts. The rate increase was attributed to reduced site blocking as evidenced by CO chemisorption measurements. Additionally, analysis of catalysts having high Pd loadings using transmission electron microscopy (TEM) showed that SAM-first catalysts generally resulted in lower average particle sizes than traditionally modified and unmodified catalysts, suggesting that precoating the support surface with PAs changes the way that Pd is deposited during incipient wetness, leading here to improved activity.

catalytic reactions↗
DOE OSTI2024

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Iron redox behavior and oxygen reduction activity of Fe-N-C electrocatalysts in different electrolytes

The iron redox behavior and oxygen reduction reaction (ORR) activity of Fe-N-C ORR electrocatalysts synthesized by a variety of techniques were investigated as a function of the identity of the electrolyte anion (bisulfate/sulfate or perchlorate) at a constant pH. In situ X-ray absorption spectroscopy data support the assignment of the redox peaks in the voltammograms to the Fe 3+ /Fe 2+ redox couple. It was found that for a given Fe-N-C catalyst, there is a correlation between the Fe redox couple peak potential and the ORR activity in perchloric acid electrolyte, but not in sulfuric acid electrolyte. While a higher Fe redox couple potential (≥ 110 mV higher) was observed in perchloric acid electrolyte, a higher ORR activity was obtained in sulfuric acid electrolyte. Here, the higher ORR activity observed in sulfuric acid than perchloric acid was correlated with the higher peak current and larger faradaic charge for the Fe redox couple. A study of the Fe redox behavior using a cavity microelectrode, eliminating the impact of ionomer, showed that the interaction of H 2 SO 4 with Fe-N-C is stronger than that of HClO 4 and that Fe redox in both electrolytes is a reversible surface electrochemical reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Fox Trails

1. This software utilizes python pandas to pull data from P6 databases or XER files. The software transforms the datasets into multiple main tables by joining, filtering, iteratively flattening hierarchical structured data, and pivoting datasets to give simple flat output tables. The activity table includes all of the information related to an activity including activity codes, global, EPS, and project codes, UDFs, and WBS information as separate columns. This includes the code id, code value and sequence number for all levels in hierarchical codes. The resource table is similar to the activity table and includes all of the information related to resources on activities including UPFs and resource codes. The resource time phased table takes the resource information and time phases it for the budget, forecast, late, and actual dates/units/costs that closely matches P6's user interface's values as it implements the resource curve and calendars. The wbs table contains the WBS structure broken out by levels and includes UDFs, codes, and notebook topics. The final P6 data table is the relationships table which simply contains the relationships. 2. When a user updates the tool with data (via giving it P6 project names with database username/password information or XER files) the system creates the data in #1, then creates a networkx graph with the activity data imbedded in the node data and the relationships added as edges. Each edge also has it's float calculated (working time distance between the predecessor and successor) and attached to the edge. Activities are also tagged as a potential start of a path based on their constraints, constraint dates, remaining start date, and activity status. When a user enters an activity ID into the UI, it runs a shortest path calculation on the network graph between each node tagged as potential start to the entered activity id based on the float tagged on the edge. Each path returned by the algorithm contains all of the nodes on the path in order, as well as the total float of the edges that make the path. This data is then collected and returned to the user in the form of a gantt chart with groupings for each path that includes the total float for each group. 3. Similar to 2, if the user passes through a reference dataset each activity set in the path is checked to see if it had a path in the reference dataset, if that path was the primary path between the start and end activities, and what has changed regarding logic and durations. These changes are color coded and summarized before sent to the user to be displayed by the UI for simple discovery. 4. Utilizing the data from #1, the user can submit desired grouping code(s) and filters to the system. The system will then pull the activities, resources, and relationships and create a gantt chart based on the groupings sent and filtered based on the filters sent. 5. The system will produce a gantt chart in a similar method to #4, but allows interactivity with the data. As the user interacts with the gantt chart, the software captures the changes and stores it with the user making the change so that project controls and implement those changes in P6.

Fox, Ben↗
DOE OSTI2020

Use of in Situ Synchrotron Techniques to Probe the Oxidized Surface of Molybdenum Nitride Oxygen Reduction Electrocatalysis

The development of active and stable earth-abundant catalysts for the oxygen reduction reaction (ORR) is needed for widespread, economic development of fuel cell technologies. Designing and optimizing these non-platinum group metals is challenging, however, because they are susceptible to composition and structure changes, including dissolution, oxidation, and corrosion, both in air and under reaction conditions. To identify the active surface, and thus understand the properties that affect activity, the catalyst surface must be characterized in situ. Herein, we utilize a grazing incidence electrochemical cell to investigate in situ composition and morphology changes of a molybdenum nitride (Mo-N) thin film catalyst using grazing incidence x-ray absorption spectroscopy (GI-XAS) and x-ray reflectivity (XRR). In rotating ring disk electrode measurements, we find that the activity, selectivity, stability, and capacitance of the Mo-N catalyst is dependent on the maximum potential to which it has been exposed. Specifically, the overpotential required to reach -2 mA cm-2geo decreases by over 90 mV when the maximum potential is increased from 0.3 to 0.8 V vs RHE (Figure 1). Because the Mo-N oxidizes rapidly in air, ex situ characterization methods including x-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry can provide only limited insight into these in situ catalyst changes. Using in situ GI-XAS measurements at applied potentials between 0.3 and 0.9 V vs RHE, however, we are able to determine that the surface of the film oxidizes and becomes more amorphous when exposed to increasingly higher potentials (Figure 1). Furthermore, the surface remains oxidized on the order of several hours when returned to "ORR relevant potentials" (< 0.6 V vs RHE), indicating that this surface-oxidized nitride is the active surface for ORR. Using in situ XRR measurements, we find that there is no change in surface roughness at potentials below 0.7 V vs RHE, but the film roughens significantly at 0.8 V vs RHE, correlating with ex situ measurements of Mo dissolution at this potential (Figure 1). We therefore conclude that the intrinsic activity of the Mo-N catalyst increases when exposed to potentials up to 0.7 V vs RHE, while above that potential activity enhancements are due to the exposure of more active sites through dissolution. The in situ electrochemical surface-sensitive x-ray characterization as used here is a promising methodology for understanding and leveraging surface dynamics to improve the performance of non-traditional catalysts.

Kreider, Melissa↗
DOE OSTI2024

Distinguishing homolytic vs heterolytic bond dissociation of phenylsulfonium cations with localized active space methods

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Furthermore, our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium.

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

Anodic electrocatalytic conversion of carboxylic acids on thin films of RuO 2 , IrO 2 , and Pt

The electrocatalytic upgrading of carboxylic acids, abundant biomass-derived molecules, remains a challenging task. In this paper, we report an electrocatalytic decarboxylation (ECDX) approach for the conversion of carboxylic acids into paraffins, olefins, and alcohols via (non-)Kolbe electrolysis on thin films (TFs). The ECDX rate, product selectivity, and current efficiency were potential and electrode dependent. For example, the ECDX activity of RuO 2 -TF was similar to that of Pt foil, but the selectivity to Kolbe products was lower on the former. RuO 2 -TF showed about five times higher rates for the oxygen evolution reaction than Pt foil, which resulted in lower current efficiency. The ECDX and O 2 evolution activities of IrO 2 -TF were potential dependent, but this electrode was selective to non-Kolbe products with low current efficiency (<10 %). This work highlights the performance of thin films as an alternative to bulk metals as anodes for oxidative upgrading of carboxylic acids.

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

Field-Coupled Water Splitting with Metal-Free Donor–Acceptor Covalent Organic-Framework Junctions

Advancing metal-free electrocatalysts for hydrogen and oxygen evolution reactions (HER/OER) across acidic and alkaline media requires coordinated control of intermediate binding thermodynamics, interfacial charge delivery, and near-electrode transport dynamics. Here, we design amide-linked benzene–triazine covalent organic frameworks (BTA/TzTA-Hz COFs) and integrate them with carbon nanotubes (CNTs) to form COF–CNT junctions that establish a built-in interfacial electric field. Density functional theory (DFT) and electrostatic potential maps indicate complementary active motifs, with benzene-proximal fragments associated with HER and triazine-proximal motifs associated with OER. CNT integration shifts the contact-potential difference by ≈0.20 V, while operando electrochemical impedance spectroscopy suggests partially separable high-frequency junction-charging and lower-frequency Faradaic/transport responses. A 300 mT static magnetic field lowers the HER and OER overpotentials by tens of millivolts. Under anodic bias, the effective interfacial charging capacitance increases, and Mott–Schottky analysis shows an apparent ∼0.15 V flat-band shift with an essentially unchanged slope. Together, these observations are consistent with field-perturbed interfacial charging and altered bias partitioning. Field-dependent impedance and bubble imaging are consistent with magnetohydrodynamic convection that promotes bubble detachment and near-electrode mass transport for both half-reactions, and they reveal an OER-specific high-frequency perturbation under anodic bias. Under field, the heterostructure reaches an OER onset overpotential of ∼261 mV and requires an overpotential of 366 mV at 10 mA cm –2 in alkaline electrolyte. These results illustrate how reticular-framework chemistry, junction engineering, and both built-in and applied fields can program reactivity through interfacial electrostatics and near-electrode transport in organic-framework electrocatalysts.

Garcia-Enriquez, Lissette [Univ. of Texas at El Pa↗
DOE OSTI2021

Rotational Dynamics of an Amphidynamic Zirconium Metal–Organic Framework Determined by Dielectric Spectroscopy

A zirconium metal–organic framework with a difluorophenylene rotator bearing a permanent electric dipole of ~3.2 D was synthesized, and its rotational motion was analyzed by temperature- and frequency-dependent broadband dielectric spectroscopy. While solid-state NMR confirms fast rotation qualitatively, the dissipation factors measured between 113 and 153 K suggested an activation energy E a = 2.6 kcal/mol, but deviations from a single Debye relaxation suggested a dynamic process that cannot be accounted for by a well-defined potential with a single activation barrier. The dynamic heterogeneity of the dipolar rotor was confirmed by analysis in terms of a Cole–Cole relaxation, which suggested a mean barrier of ~1.9 kcal/mol, with a heterogeneity that decreases as temperature increases. Based on the single-crystal structure, we propose that the kinetic heterogeneity results from a temperature-dependent potential where rotation motion is mediated by the escape of the rotator from an energy well created by a double Ph–H···F–Ph hydrogen bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Nonaqueous Redox‐Matched Flow Battery with Charge Storage in Insoluble Polymer Beads**

Abstract We describe the nonaqueous redox‐matched flow battery (RMFB), where charge is stored on redox‐active moieties covalently tethered to non‐circulating, insoluble polymer beads and charge is transferred between the electrodes and the beads via soluble mediators with redox potentials matched to the active moieties on the beads. The RMFB reported herein uses ferrocene and viologen derivatives bound to crosslinked polystyrene beads. Charge storage in the beads leads to a high (approximately 1.0–1.7 M) effective concentration of active material in the reservoirs while preventing crossover of that material. The relatively low concentration of soluble mediators (15 mM) eliminates the need for high‐solubility molecules to create high energy density batteries. Nernstian redox exchange between the beads and redox‐matched mediators was fast relative to the cycle time of the RMFB. This approach is generalizable to many different redox‐active moieties via attachment to the versatile Merrifield resin.

25 ENERGY STORAGE↗
DOE OSTI2023

Unraveling the Cooperative Activity of Hydrophilicity, Conductivity, and Interfacial Active Sites in Alginate‐CNT‐Cuo Self‐Standing Electrodes with Benchmark‐Close Activity for Alkaline Water Splitting

Designing electrocatalysts that excel in hydrogen and oxygen electrochemistry is crucial for sustainable hydrogen generation through electrochemical water splitting. This study presents a novel tricomponent catalyst composed of an alginate hydrogel (AL) infused with single-walled carbon nanotubes (CNTs) and copper oxide (CuO) nanoparticles. The catalyst exhibits benchmark-close bifunctional activity toward hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) under alkaline conditions. The aerophobic nature of the AL-gel facilitates superior bubble release from the electrode, while the inclusion of CNTs mitigates charge transfer resistance. Moreover, heterojunctions of CuO and CNTs create unique interfacial active sites, culminating in high electrocatalytic water-splitting activity. The structural rigidity of the composite permits its use as self-standing electrodes (SSE) without using substrates or binders, enabling a direct evaluation of its activity. The composite electrode demonstrates exceptional electrocatalytic HER activity in an alkaline solution, with onset potentials of 93 mV and moderate OER activity with an onset of 155 mV. Furthermore, a water electrolysis cell featuring the bifunctional SSE exhibits an open circuit voltage of 1.85 V at 100 mA.cm −2 , and only 8% efficiency loss after 100 h marking this a significant stride in developing self-standing nonprecious electrocatalysts with impressive catalytic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Active motion of multiphase oil droplets: emergent dynamics of squirmers with evolving internal structure

Synthetic soft matter systems, when driven beyond equilibrium by active processes, offer the potential to achieve dynamical states and functions of a complexity found in living matter. Emulsions offer the basis of a simple yet versatile system for identification of the physicochemical principles underlying active soft matter, but how multiple internal phases within emulsion droplets (e.g., Janus morphologies) organize to impact emergent dynamics is not understood. Here, we create multiphase oil droplets with ultralow interfacial tensions but distinct viscosities, and drive them into motion in aqueous micellar solutions. Preferential solubilization of select components of the oil both drives the droplet motion and yields a progression of internal phase morphological states with distinct symmetries. In this work, we find the active droplets to exhibit five dynamical states during morphogenesis. By quantifying microscopic flow fields, we show that it is possible to map the diverse droplet behaviors to squirmer models of spherical microswimmers in Stokes flow, thus showing that multiphase droplets offer the basis of a versatile platform with which to study and engineer the hydrodynamics of microswimmers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Magnetized Strongly Turbulent Corona as the Source of Neutrinos from NGC 1068

Abstract The cores of active galactic nuclei are potential accelerators of 10–100 TeV cosmic rays, in turn producing high-energy neutrinos. This picture was confirmed by the compelling evidence of a TeV neutrino signal from the nearby active galaxy NGC 1068, leaving open the question of what is the site and mechanism of cosmic-ray acceleration. One candidate is the magnetized turbulence surrounding the central supermassive black hole. Recent particle-in-cell simulations of magnetized turbulence indicate that stochastic cosmic-ray acceleration is nonresonant, in contrast to the assumptions of previous studies. We show that this has important consequences on a self-consistent theory of neutrino production in the corona, leading to a more rapid cosmic-ray acceleration than previously considered. The turbulent magnetic-field fluctuations needed to explain the neutrino signal are consistent with a magnetically powered corona. We find that strong turbulence, with turbulent magnetic energy density higher than 1% of the rest-mass energy density, naturally explains the normalization of the IceCube neutrino flux, in addition to the neutrino spectral shape. Only a fraction of the protons in the corona, which can be directly inferred from the neutrino signal, are accelerated to high energies. Thus, in this framework, the neutrino signal from NGC 1068 provides a testbed for particle acceleration in magnetized turbulence.

Fiorillo, Damiano F. G. (ORCID:0000000349279850)↗
DOE OSTI2024

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, in this study, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electrochemical Modeling of Iodide Oxidation in Metal-Halide Molten Salts

The oxidation of iodide in NaI-AlBr 3 , NaI-AlCl 3 , and NaI-GaCl 3 molten salts was analyzed using simulation software to extract relevant kinetic parameters. The experimental oxidation potentials were ordered AlCl 3 < AlBr 3 < GaCl 3 , with higher oxidation potentials correlating with softer Lewis acidity of the metal halide. An iodide oxidation and metal halide speciation model was developed and simulated to fit the electrochemical response, enabling determination of electrochemical charge transfer parameters and chemical equilibrium constants. NaI-AlBr 3 displayed the fastest electron transfer rates yet showed the lowest current densities. All salts revealed smaller than expected current densities, explained by equilibrium between various species, where some are not electrochemically active at the studied potentials. These equilibrium reactions are due to the various metal halide species, controlling the reactant concentration of iodide and the resultant current. We hypothesize the electrochemically active iodide species, present as a metal halide monomer (MX 3 I − ), is decreased dramatically from the expected concentration, sequestered as a more stable metal halide dimer species (M 2 X 6 I − ) with a higher oxidation potential. Traditional Tafel analysis of the experimental data supports the validity of the simulations. These results increase understanding of iodide oxidation in low-temperature Lewis acidic molten salts and inform task-specific molten salt design.

Lee, Rose Y. (ORCID:0000000226587220)↗