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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Molecular Symmetry in VQE: A Dual Approach for Trapped-Ion Simulations of Benzene

Understanding complex chemical systems—such as biomolecules, catalysts, and novel materials—is a central goal of quantum simulations. Near-term strategies hinge on the use of variational quantum eigensolver (VQE) algorithms combined with a suitable ansatz. However, straightforward application of many chemically-inspired ansatze yields prohibitively deep circuits. In this work, we employ several circuit optimization methods tailored for trapped-ion quantum devices to enhance the feasibility of intricate chemical simulations. The techniques aim to lessen the depth of the unitary coupled cluster with singles and doubles (uCCSD) ansatz's circuit compilation, a considerable challenge on current noisy quantum devices. Furthermore, we use symmetry-inspired classical post-selection methods to further refine the outcomes and minimize errors in energy measurements, without adding quantum overhead. Our strategies encompass optimal mapping from orbital to qubit, term reordering to minimize entangling gates, and the exploitation of molecular spin and point group symmetry to eliminate redundant parameters. The inclusion of error mitigation via post-selection based on known molecular symmetries improves the results to near milli-Hartree accuracy. These methods, when applied to a benzene molecule simulation, enabled the construction of an 8-qubit circuit with 69 two-qubit entangling operations, pushing the limits for variational quantum eigensolver (VQE) circuits executed on quantum hardware to date. 1 1 This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-000R22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan(https://energy.gov/doe-public-access-plan).

Goings, Joshua↗
DOE OSTI2021

Additive Manufacturing Case Study

Geothermal technologies include an extremely wide range of products required for well construction, completion, production, intervention and surface energy conversion activities. Many of these products are geometrically complex, require multi-step and highly specialized fabrication processes, and are expensive due to the low production numbers typically associated with the geothermal market. These challenges along with the high temperature demands of the geothermal environment have also hindered the adoption of many tools routinely used in the oil & gas industry.Recent advancements in Additive Manufacturing (AM) materials of construction, build volumes and part quality have transitioned the technology from primarily cosmetic prototyping applications to the point where AM can be used to make production parts, even for the most demanding applications. These improved AM capabilities along with the inherent ability of AM to produce complex parts and, in some cases, geometries that cannot be manufactured using conventional casting, machining and joining fabrication approaches motivate an exploration of its potential to positively impact geothermal well construction and operations technologies.Sandia National Labs collaborated with Oak Ridge National Laboratory on a case study examining additive manufacturing opportunities for Geothermal applications. The study focused on designing components with improved performance characteristics that cannot be fabricated conventionally. A rotor for a downhole motor was chosen based on the potential for improving its rotational dynamics. Topology optimization was used as a design method to reduce the rotational inertia of the part while preserving sufficient rotational stiffness to transmit the torque required for the drilling application. The optimization resulted in a nearly 50% reduction in polar moment of inertia while maintaining other desired performance characteristics. The design developed using the topology optimization approach was fabricated using additive manufacturing and cannot be fabricated conventionally. This paper will discuss the design approach, performance improvements and manufacturing methods used to produce the part.

Polsky, Yarom↗
DOE OSTI2022

Interaction-driven quantum anomalous Hall insulator in a Dirac semimetal

Here, the interaction-driven quantum anomalous Hall (QAH) insulator has been sought for a long time in a Dirac semimetal with linear band touching points at the Fermi level. By combining exact diagonalization, density matrix renormalization group, and analytical methods, we study a spinless fermion system on the checkerboard lattice with twofold rotational symmetry, which realizes two Dirac band touching points in the absence of interaction. At weak coupling, the Dirac semimetal is stable. At a finite density-density repulsive interaction, we analyze possible symmetry broken states, and find that an QAH state is stabilized when the interaction strength exceeds the energy scale controlling the separation between the Dirac points. Through numerical simulations, we verify the existence of the QAH phase with spontaneous time-reversal symmetry breaking and quantized Chern number C = 1.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Energy efficiency for the growing South Carolina manufacturing industries. Final Report

The overall goals of the proposed project were to establish a DOE Industrial Assessment Center with Clemson University as the main center and to cement the Clemson IAC as the "go to" resource for energy efficiency expertise and assistance to manufacturing businesses in the state of South Carolina. The Clemson IAC included a satellite support center through partnership with the SCE&G Energy Innovation Center at the Clemson University Restoration Institute (CURI) in North Charleston, SC. The Clemson IAC was the first IAC based in the state with the goal to serve the entire state. The Clemson IAC provided SMEs with no-cost energy assessments, trained the next generation of energy-savvy engineers, and provided outreach to non-participating SMEs. Project objectives were structured into five 12-month Budget Periods. In the first Budget Period, the primary objective was to establish methods and materials for Clemson IAC assessments, training, and outreach. In the remaining Budget Periods, the primary objectives were to perform assessments, train students, and pursue outreach to hard-to-reach SMEs that did not participate in energy assessments. Expected outcomes in the first Budget Period included the development of standard procedures for performing energy assessments, including data acquisition, processing, and communication both within the team and in assessment reports prepared for SMEs. Outcomes related to student training in the first Budget Period included detailed curriculum and internship plans for students pursuing the DOE IAC Certificate and energy-related Clemson University certificates. Outcomes in the first Budget Period also included the development of outreach materials and plans for outreach events. In Budget Periods 2 through 5, major expected outcomes are trained students and completed energy assessments and reports for SMEs. Decision points and Go-No Go criteria for the end of each Budget Period, presented in more detail below, are based on the number of students in training and the number of energy assessments performed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗
DOE OSTI2020

Calculating Potential Radiological Emissions for Waste Management Activities at INL - 20068

At Idaho National Laboratory (INL), work involving radionuclides is evaluated for potential emissions from a project in order to comply with the National Emission Standards for Hazardous Air Pollutants (NESHAP) regulations, 40 CFR 61 Subpart H. Emission calculations are documented in an Air Permitting Applicability Determination (APAD) to analyze unmitigated and mitigated emissions and determine if an Application to Construct (ATC) or continuous monitoring is required. To calculate the unmitigated and mitigated emissions, a spreadsheet was developed to provide ease in determining potential emissions by providing the maximum operating temperature and the material being used. The spreadsheet aids in determining the potential emissions for research projects and waste management activities at Materials and Fuels Complex (MFC) and other locations across the INL site. Furthermore, it can also be used for periodic confirmatory measurements (PCM) to justify low emissions. Elements that factor into the unmitigated and mitigated calculations include the amount of each radionuclide used (in curies or grams), specific activity (if amount is given in grams), the temperature the material is heated to in Celsius, the dose conversion factor which is derived from Clean Air Act Assessment Package - 1988 (CAP-88) modeling, and the number of HEPA filters used for mitigated measures. The main drivers for calculating the unmitigated emissions for a project are the amount used per radionuclide, the maximum operating temperature, and the location of the work. The maximum operating temperature determines the airborne release factor which is dependent on the physical state of the radionuclide. Prior to October 2017, if the radionuclide was heated to greater than 100 deg. C, the radionuclide was assumed to be a gas, which has the highest airborne release factor. This assumption would be overly conservative for radionuclides with high melting and boiling points, which provided a challenge to demonstrate low emissions. In October 2017, the Environmental Protection Agency (EPA) approved an alternative method for INL. This method allows the airborne release factor to be determined by using the melting point and 90% of the boiling point of the radionuclide. This methodology was included in the spreadsheet to allow unmitigated emission calculations for APADs to be completed more efficiently and effectively. Results show a reduction in time completing air emission calculations as well as lower total emissions across all facilities at INL. MFC annual emissions were reduced by 62% from the previous year and Research and Education Campus (REC) facilities were reduced by 38% due to implementation of the approved alternative method. Time spent on APADs, PCMs, and documentation for the annual NESHAP report was also reduced significantly. The spreadsheet provided in Table I provides the potential emission calculations for the 'Advanced Retrieval and Disposition Techniques for Remote Handled Mixed Low Level Waste (RH MLLW) at the Radioactive Scrap and Waste Facility (RSWF)' project. Calculations show the Potential Effective Dose Equivalent (PEDE) at RSWF to be 7.27 E-04 mrem/yr (7.27 E-09 Sv/yr) which is well below the 0.1 mrem/yr threshold. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Melting and phase relations of Fe-Ni-Si determined by a multi-technique approach

Many studies have suggested silicon as a candidate light element for the cores of Earth and Mercury. However, the effect of silicon on the melting temperatures of core materials and thermal profiles of cores is poorly understood, due to disagreements among melt detection techniques, uncertainties in sample pressure evolution during heating, and sparsity of studies investigating the combined effects of nickel and silicon on the phase diagram of iron. Here, in this study we develop a multi-technique approach for measuring the high-pressure melting and solid phase relations of iron alloys and apply it to Fe 0.8 Ni 0.1 Si 0.1 (Fe-11wt%Ni-5.3wt%Si), a composition compatible with recent estimates for the cores of Earth and Mercury. This approach combines results (20-83 GPa) from two atomic-level techniques: synchrotron Mossbauer spectroscopy (SMS) and synchrotron x-ray diffraction (XRD). Melting is independently detected by the loss of the Mossbauer signal, produced exclusively by solid-bound iron nuclei, and the onset of a liquid diffuse x-ray scattering signal. The use of a burst heating and background updating method for quantifying changes in the reference background during heating facilitates the determination of liquid diffuse signal onsets and leads to strong reproducibility and excellent agreement in melting temperatures determined separately by the two techniques. XRD measurements additionally constrain the hcp-fcc phase boundary and in-situ pressure evolution of the samples during heating. We apply our updated thermal pressure model to published SMS melting data on fcc-Fe and fcc-Fe 0.9 Ni 0.1 to precisely evaluate the effect of silicon on melting temperatures. We find that the addition of 10 mol% Si to Fe 0.9 Ni 0.1 reduces melting temperatures by ~250 K at low pressures (<60 GPa) and flattens the hcp-fcc phase boundary. Extrapolating our results, we constrain the location of the hcp-fcc-liquid quasi-triple point at 147±14 GPa and 3140±90 K, which implies a melting temperature reduction of 500 K compared with Fe 0.9 Ni 0.1 . The results demonstrate the advantages of combining complementary experimental techniques in investigations of melting under extreme conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗
DOE OSTI2020

QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing the accuracy. Advances in real space methods include techniques for accurate computation of bandgaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods, including GW and density functional based techniques. To provide an improved foundation for these calculations, we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

An efficient protocol for excited states of large biochromophores

Efficient energy transport in photosynthetic antenna is a long-standing source of inspiration for artificial light harvesting materials. However, characterizing the excited states of the constituent chromophores poses a considerable challenge to mainstream quantum chemical and semiempirical excited state methods due to their size and complexity and the accuracy required to describe small but functionally important changes in their properties. In this paper, we explore an alternative approach to calculating the excited states of large biochromophores, exemplified by a specific method for calculating the Q y transition of bacteriochlorophyll a, which we name Chl-xTB. Using a diagonally dominant approximation to the Casida equation and a bespoke parameterization scheme, Chl-xTB can match time-dependent density functional theory’s accuracy and semiempirical speed for calculating the potential energy surfaces and absorption spectra of chlorophylls. We demonstrate that Chl-xTB (and other prospective realizations of our protocol) can be integrated into multiscale models, including concurrent excitonic and point-charge embedding frameworks, enabling the analysis of biochromophore networks in a native environment. We exploit this capability to probe the low-frequency spectral densities of excitonic energies and interchromophore interactions in the light harvesting antenna protein LH2 (light harvesting complex 2). The impact of low-frequency protein motion on interchromophore coupling and exciton transport has routinely been ignored due to the prohibitive costs of including it in simulations. Our results provide a more rigorous basis for continued use of this approximation by demonstrating that exciton transition energies are unaffected by low-frequency vibrational coupling to exciton interaction energies.

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

Measurement of the Low-Energy Electron Inelastic Mean Free Path in Monolayer Graphene

Measuring the electron-transport properties of substrate-supported nanomaterials with the traditional two-point comparison method is difficult at electron energies below 50 eV, where core-level signals are too feeble to be detected against the strong secondary-electron background. Herein, a data-driven spectral analysis technique is used to study the low-energy electron-transport properties of substrate-supported target nanomaterials, while eliminating the influence of the substrate signal. Applying this technique, the electron-transport properties of the effective attenuation length and the inelastic mean free path (IMFP) can be determined with extremely high efficiency over the entire measured energy range of 6–600 eV. Further, these results show excellent agreement with other experimental and theoretical results. In this work, significant differences are observed between monolayer graphene and the bulk graphite IMFP, which illustrates the importance of the nanometer effect in the electron-transport properties of the material. Furthermore, this technique is readily applicable to any ultrathin material that can be transferred onto a polycrystalline gold substrate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Software Development for Data Visualization and Analysis of PN-Diodes & MOSFET Devices

The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Decoherence of $V^{–}_{B}$ spin defects in monoisotopic hexagonal boron nitride

Spin defects in hexagonal boron nitride (hBN) are promising quantum systems for the design of flexible two-dimensional quantum sensing platforms. Here we rely on hBN crystals isotopically enriched with either 10 B or 11 B to investigate the isotope-dependent properties of a spin defect featuring a broadband photoluminescence signal in the near infrared. By analyzing the hyperfine structure of the spin defect while changing the boron isotope, we first confirm that it corresponds to the negatively charged boron-vacancy center ($V^{–}_{B}$). We then show that its spin coherence properties are slightly improved in 10B-enriched samples. This is supported by numerical simulations employing cluster correlation expansion methods, which reveal the importance of the hyperfine Fermi contact term for calculating the coherence time of point defects in hBN. Using cross-relaxation spectroscopy, we finally identify dark electron spin impurities as an additional source of decoherence. This work provides new insights into the properties of $V^{–}_{B}$ spin defects, which are valuable for the future development of hBN-based quantum sensing foils.

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

Towards engineering the growth morphology of anisotropic bicrystals

Eutectic alloys, such as Pb-free Bi-Sn-Ag or Sn-Ag-Cu, are essential for their low melting points in solder joints but suffer from brittle intermetallic phases, reducing reliability. Traditional solder design relies on equilibrium phase diagrams, often neglecting the kinetic influence of crystalline anisotropy during solidification. This study hypothesizes that the energetics at the solid-solid-liquid trijunction dictate crystalline facet selection. Using the Al-Al 3 Ni alloy as a model, this project combines atomistic simulations and experimental methods to understand interfacial energies and develop predictive models. This approach aims to mitigate the negative effects of intermetallics, enhancing component reliability in electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Intrinsically sodiophilic, mesoporous metal-free wetting layers based on inexpensive carbon black for sodium-metal batteries

In this article, elevated temperature molten Na batteries are seeing a resurgence of interest for low-cost electrochemical energy storage for the grid. Of the many recent innovations in this battery concept, new methods focused on intermediate temperature operation (e.g. 110–190 °C) have gained prominence as a way to enable comparable performance with less thermal energy loss and lower-cost materials of construction. However, the poor wettability of molten Na on suitable solid-electrolyte separators such as sodium Beta Alumina Solid-Electrolyte (Na-β”-Al 2 O 3 , ‘BASE’) requires continued innovation in interface engineering to promote full utilization of the solid-electrolyte surface area and minimize cell resistance. There have been many successful approaches to improve Na-wettability to-date including heat treatment in an inert atmosphere to remove adsorbed surface species, deposition of alloying metals such as Pb, Sn, or Bi, and use of carbon-based interfacial layers. However, these approaches either lack the ability to provide good wetting at very low temperatures (near the melting point of Na) or rely on non-scalable processes and/or toxic/expensive metals. To solve these issues, a new carbon-based sodiophilic treatment is demonstrated, which utilizes inexpensive components to form a meso/macroporous sodiophilic layer, is easily applied via drop-casting or spray-coating, provides excellent wetting as low as 110 °C, and is completely metal-free. It is found that the good sodium wetting can be attributed to the wider range of pore sizes in the carbon layers demonstrated in this study. Na wetting may occur as surface tension is initially broken by larger pores, followed by the intrusion of molten Na into smaller pores due to the apparent intrinsic affinity of Na-metal for carbon surfaces, in conjunction with the capillarity effect. Low cell-level area specific resistances of 20–30 and 13–15 Ω·cm 2 are demonstrated at 110 and 140 °C respectively. Finally, the utility of this metal-free wetting layer for solid-Na anodes is explored, showing that the metal-free wetting layer can reach a critical current density of 1.88 mA·cm -2 at 30 °C.

25 ENERGY STORAGE↗
DOE OSTI2022

Promoting CO 2 Release from CO 3 2- -Containing Solvents during Water Electrolysis for Direct Air Capture

The pH swings from water electrolysis are leveraged to condition OH – -based facile CO 2 capture solvents using an electrochemical flow cell for direct air capture (DAC). Besides demonstrating the DAC using a membrane contactor, promoting CO 2 release from a CO 3 2– solution at the anode is specifically studied by adjusting the volumetric flow rate, anode chamber volume, residence time, and K 2 CO 3 concentration. Through case-by-case comparisons coupled with modeled results, increasing current, reducing volumetric flow rate, and/or reducing CO 3 2– concentration are the effective methods to promote CO 2 release from a CO 3 2– -containing solvent, whereas enlarging the anode chamber volume poses a minor effect. Moreover, the discrepancies between the experimental and modeled results may be caused by H + crossover rather than K + transport through the Nafion membrane during water electrolysis based upon the total alkalinity measurements for the K 2 CO 3 solutions gleaned from the anode. Here, it is believed that such results will provide guidance to design and operate an electrochemical flow cell for electrochemistry-assisted DAC and point source CO 2 capture.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Direct link between disorder and magnetoresistance in topological semimetals

The extent to which disorder influences the properties of topological semimetals is relevant to the understanding of topological states and their use in practical applications. Using molecular beam epitaxy, we achieve systematic control of point defect concentrations in the prototypical Dirac semimetal Cd 3 As 2 to gain insight into the role of disorder on electron transport behavior. Using the guiding center diffusion model for linear magnetoresistance, we extract point defect densities as a function of deposition conditions. We find that reducing cadmium defect concentrations by an order of magnitude results in an 2x increase in the magnetoresistance from 450% to 900%. This finding yields important information in the quest to identify the origin of linear magnetoresistance in a wider range of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗