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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Role of SnO2 Processing on Ionic Distribution in Double-Cation-Double Halide Perovskites

Moving toward a future of efficient, accessible, and less carbon-reliant energy devices has been at the forefront of energy research innovations for the past 30 years. Metal-halide perovskite (MHP) thin films have gained significant attention due to their flexibility of device applications and tunable capabilities for improving power conversion efficiency. Serving as a gateway to optimize device performance, consideration must be given to chemical synthesis processing techniques. Therefore, how does common substrate processing techniques influence the behavior of MHP phenomena such as ion migration and strain? Here, we demonstrate how a hybrid approach of chemical bath deposition (CBD) and nanoparticle SnO2 substrate processing significantly improves the performance of (FAPbI3)0.97(MAPbBr3)0.03 by reducing micro-strain in the SnO2 lattice, allowing distribution of K+ from K-Cl treatment of substrates to passivate defects formed at the interface and produce higher current in light and dark environments. X-ray diffraction reveals differences in lattice strain behavior with respect to SnO2 substrate processing methods. Through use of conductive atomic force microscopy (c-AFM), conductivity is measured spatially with MHP morphology, showing higher generation of current in both light and dark conditions for films with hybrid processing. Additionally, time-of-flight secondary ionization mass spectrometry (ToF-SIMS) observed the distribution of K+ at the perovskite/SnO2 interface, indicating K+ passivation of defects to improve the power conversion efficiency (PCE) and device stability. We show how understanding the role of ion distribution at the SnO2 and perovskite interface can help reduce the creating of defects and promote a more efficient MHP device.

conductive atomic force microscopy↗
DOE OSTI2021

Process modeling, techno-economic assessment, and life cycle assessment of the electrochemical reduction of CO 2 : a review

The electrochemical reduction of CO 2 has emerged as a promising alternative to traditional fossil-based technologies for the synthesis of chemicals. Its industrial implementation could lead to a reduction in the carbon footprint of chemicals and the mitigation of climate change impacts caused by hard-to-decarbonize industrial applications, among other benefits. However, the current low technology readiness levels of such emerging technologies make it hard to predict their performance at industrial scales. During the past few years, researchers have developed diverse techniques to model and assess the electrochemical reduction of CO 2 toward its industrial implementation. The aim of this literature review is to provide a comprehensive overview of techno-economic and life cycle assessment methods and pave the way for future assessment approaches. First, we identify which modeling approaches have been conducted to extend analysis to the production scale. Next, we explore the metrics used to evaluate such systems, regarding technical, environmental, and economic aspects. Finally, we assess the challenges and research opportunities for the industrial implementation of CO 2 reduction via electrolysis.

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

Evaluation of crystalline quality of traveling heater method (THM) grown Cd0.9Zn0.1Te0.98Se0.02 crystals

Because of its excellent opto-electronic properties, CdZnTe (CZT) has been the material of choice for x- and gamma-ray detectors operable at room temperature. CZT is the leading commercially available room-temperature radiation detector material today. Although much progress has been made over the past three decades, today's CZT crystals still face certain challenges, especially the presence of the performance-limiting materials defects and the associated relatively high production cost. In this regard, CdxZn1−xTeySe1−y (CZTS) is emerging as a next-generation compound semiconductor, which overcomes some of the limitations of CZT technology for the stated applications. Here, we conducted a study to evaluate the crystalline quality of the traveling heater method grown CZTS with an optimized alloy composition, i.e., Cd0.9Zn0.1Te0.98Se0.02. The as-grown samples were evaluated by low-temperature photoluminescence (PL) spectroscopy and high-resolution x-ray diffraction using the synchrotron light source at Brookhaven National Laboratory. The full width at half maximum of both the PL and x-ray rocking curves was observed to be broadened due to the lattice disorder of the quaternary compound, eventually degrading the crystalline quality. This was consistent with density functional theory calculations.

Roy, U. N. (ORCID:0000000282089680)↗
DOE OSTI2021

Spectral properties of three-dimensional Anderson model

The three-dimensional Anderson model represents a paradigmatic model to understand the Anderson localization transition. In this work we first review some key results obtained for this model in the past 50 years, and then study its properties from the perspective of modern numerical approaches. Our main focus is on the quantitative comparison between the level sensitivity statistics and the level statistics. While the former studies the sensitivity of Hamiltonian eigenlevels upon inserting a magnetic flux, the latter studies the properties of unperturbed eigenlevels. We define two versions of dimensionless conductance, the first corresponding to the width of the level curvature distribution relative to the mean level spacing, and the second corresponding to the ratio of the Heisenberg time and the Thouless time obtained from the spectral form factor. We show that both conductances look remarkably similar around the localization transition, in particular, they predict a nearly identical critical point consistent with other well-established measures of the transition. We then study some further properties of those quantities: for level curvatures, we discuss particular similarities and differences between the width of the level curvature distribution and the characteristic energy studied by Edwards and Thouless (1972) in their pioneering work, in which the hopping at one lattice edge is changed from periodic to antiperiodic boundary conditions. In the context of the spectral form factor, we show that at the critical point it enters a broad time-independent regime, in which its value is consistent with the level compressibility obtained from the level variance. Finally, we test the scaling solution of the average level spacing ratio in the crossover regime using the cost function minimization approach introduced recently in Šuntajs et al. (2020). The latter approach seeks for the optimal scaling solution in the vicinity of the crossing point, while at the same time it allows for the crossing point to drift due to finite-size corrections. We find that the extracted transition point and the scaling coefficient agree with those from the literature to high numerical accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Unravelling chloride transport/microstructure relationships for blended-cement pastes with the mini-migration method

A chloride mini-migration method is proposed to estimate effective diffusion coefficients at the scale of the cement paste and to investigate mechanisms with complementary microstructure analyses on the same material. Blended-cement pastes with a wide range of properties were investigated in this study: systems at w/b = 0.3–0.5 including Portland cement, white Portland cement, slag-Portland cement, fly ash, glass powder, and/or limestone and calcined clay. Comparisons showed the relative and combined importance of three main parameters on the effective diffusion coefficient: the porosity, the pore connectivity parameter and the conductivity of the pore solution (low values of the latter two are generally key aspects of the high resistance of blended-cement systems against chloride ingress). Notably, a general correlation for all the investigated systems was established between the effective diffusion coefficient and the bulk conductivity (whereas no simple correlation was observed between the effective diffusion coefficient and the formation factor or the pore connectivity parameter).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding the impact of SPMAK and PEGPEA in crosslinked PEGDA membranes: Methanol-carboxylate co-transport behavior and correlating structure-physicochemical-transport properties

Investigating multicomponent transport in dense, hydrated polymer membranes is necessary in applications such as fuel cells, electrolyzers, and desalination systems. Of particular interest are photoelectrochemical CO 2 reduction cells (PEC-CRC) which produce liquid products such as alcohols (methanol) and carboxylates (formate, acetate). Flux coupling and competitive sorption behavior of these products (solutes) have been found to affect permselectivity, thereby motivating us to investigate fundamental membrane structure-physicochemical-transport relationships. Past research has shown that systematic tuning of crosslinked cation exchange membranes (CEMs) with charge-neutral monoacrylate monomers containing alkyl and phenyl groups (i.e., poly(ethylene glycol) methacrylate (PEGMA), and poly(ethylene glycol) phenyl ether acrylate (PEGPEA)) can suppress acetate transport (permeability) in co-permeation with methanol. To further investigate this transport behavior and to enhance membrane ionic conductivities, 3-sulfopropyl methacrylate potassium (SPMAK), a sulfonated monoacrylate monomer is incorporated here. SPMAK content is varied with neutral PEGPEA and diacrylate crosslinker, poly (ethylene glycol) diacrylate (PEGDA) of two different chain lengths (n = 10 and 13) to prepare membranes of various compositions. Electrochemical and physicochemical properties including ionic conductivity, ion exchange capacity, and water uptake increase with increasing charged SPMAK content. Different states of water within hydrated membranes are probed using differential scanning calorimetry (DSC), where increasing intermediate (loosely bound) water is observed with increasing hydrophilic SPMAK content. The transport behavior of methanol and carboxylates (formate, acetate, propionate) are investigated, where permeabilities vary as methanol > formate > acetate ≈ propionate. Interestingly, permeabilities decrease with increasing PEGPEA content and are more dependent on solute diffusion than sorption. Permeabilities and diffusivities decrease while permselectivities increase with decreasing PEGDA chain length.

25 ENERGY STORAGE↗
DOE OSTI2023

Predicting future well performance for environmental remediation design using deep learning

Here in this study, we developed a deep learning (DL) framework with a multi-channel three-dimensional convolutional neural network (MC3D-CNN) to predict well performance and thereby assist future environmental remediation design. Such prediction of extraction well performance at designated locations is critical for configuring pump-and-treat (P&T) well network design and operation, setting reasonable target closure dates for overall remedying, and estimating remedy costs. The framework is developed with operational and monitoring data routinely collected during P&T remedy operations, including well extraction and injection rates as well as in situ contaminant concentrations. Traditionally, the collected data were rarely used for purposes other than assessing past well performance and the accuracy of the conceptual site model. However, recent advances in data-driven computational approaches enable better use of the large datasets to inform future well performance, enhance site characterization, and improve remediation planning. In this study, we established a DL framework to integrate transient three-dimensional contaminant plumes and multiple aquifer properties (e.g., hydraulic conductivity and hydrostratigraphic maps) to identify characteristic patterns controlling and representing extraction well mass recovery, aiming at providing future mass recovery estimates for existing wells and candidate wells at any proposed locations. We evaluated our framework by using a realistic synthetic dataset generated from a well-calibrated flow and transport model used in the 200 West Area of the U.S. Department of Energy’s Hanford Site in southeastern Washington state. The multi-channel feature in our framework allows integration of various types and temporal densities of training datasets for DL model development. Overall, we found that the trained DL model achieved an accuracy of over 90% in ranking extraction well performance in validation datasets, and over 80% in predicting high-performance-ranking well locations. This data-informed approach provides a flexible tool to support adaptive site management, streamline decision-making, and potentially reduce remediation time and costs. Our DL framework can be used as a filtering tool to improve the current P&T network optimization design by reducing the number of candidate well locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US

Abstract Burned areas in the western US have increased ten‐fold since 1980s, which are attributable to multiple factors, including increasing heat, changing precipitation patterns, and extended drought. To better understand how these factors contribute to large fire emissions (gridded monthly fire emissions >95th percentile of all the fire emissions in the western US; 0.009 Gg/month), we build a machine learning model to predict fire emissions (PM 2.5 ) over the western US at 0.25° resolution, interpreted using explainable artificial intelligence (XAI). From the predictor contributions derived from XAI, we conduct k‐means clustering analysis to identify four clusters of predictor variables representing different drivers of large fire emissions. The four clusters feature the contributions of fuel load (Cluster 1) and different levels of dryness (Cluster 2–4), controlled by fuel moisture, drought condition, and fire‐favorable large‐scale meteorological patterns featuring high temperature, high pressure, and low relative humidity. In the past two decades, large fire emissions peak in summer. However, large fire emissions increased significantly in September and October in 2010–2020 relative to 2000–2009, extending the peak large fire emissions from summer to autumn. The larger enhancements of large fire emissions during autumn compared to summer are contributed by decreased fuel moisture, along with more frequent concurrent fire‐favorable large‐scale meteorological patterns and drought. These results highlight fuel drying as a common driver supported by multiple drivers, such as warmer temperature and more frequent synoptic patterns favorable for fires, in increasing the autumn risk of large fire emissions across the western US.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ground-state order in magic-angle graphene at filling ν = - 3 : A full-scale density matrix renormalization group study

Here we investigate twisted bilayer graphene (TBG) at filling ν = -3 in the presence of realistic heterostrain. Strain amplifies the band dispersion and drives the system beyond the strong-coupling regime of previous theoretical studies. We use DMRG to conduct an unbiased, large-scale numerical calculations that include all spin and valley degrees of freedom, up to bond dimension χ = 24576. We establish a global phase diagram that unifies a number of theoretical and experimental results. Near zero strain we find an intervalley-coherent quantized anomalous Hall (QAH-IVC) state, a competitive strong-coupling order that evaded past numerical studies. A tiny strain around 0.05% drives a transition into an incommensurate Kekulé spiral (IKS) phase, supporting the mean-field prediction in [Kwan, Phys. Rev. X 11, 041063 (2021)2160-330810.1103/PhysRevX.11.041063]. Even higher strains above 0.2% favor a flavor-symmetric metallic order, which may explain metals found at ν = -3 in many experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

ORNL Package Testing Program Overview

Radioactive materials are widespread in our everyday activities which are used in many different types of industries: Consumer products, Medicine, Industry, Energy, and Defense. In the United States there is about 3 million shipments of radioactive materials per year. With radioactive material being very widespread the number of new applications to ship these quantities increases daily. As such, ensuring the safe and secure transport of these materials is paramount, necessitating stringent packaging, transportation, and certification requirements. Shipments of radioactive materials have been made from Oak Ridge National Laboratory (ORNL) for the past 65 years. Since the 1940s ORNL has been at the forefront of the early development of regulations pertaining to the transport of radioactive shipments and associated regulatory testing. The early involvement resulted in ORNL being one of the leaders in the development of regulations and testing standards pertaining to the testing and design of packages. Today all package testing activities are conducted under the Package Testing Program (PTP) at ORNL at the Package Evaluation Facility (PEF). The PTP develops and evaluates testing solutions – ensuring that they are safe, efficient, and meet regulatory requirements ORNL PTP has extensive experience in the regulatory testing of radioactive material packages, supporting certification of Type A, Type, B, Type AF, and special form packages. The PEF serves as a one-stop-shop for design, testing, and certification of a wide variety of packages needed for shipment of radioactive materials. The facility provides the space, expertise, and equipment necessary to conduct rigorous performance testing under both normal and accident conditions or transport environments including free drop, dynamic crush, puncture, penetration, compression, vibration, water spray, water immersion, and thermal test. The PTP remains a key contributor to the safety and compliance of radioactive material transportation. This presentation will provide an overview of the program’s history, capabilities, and its ongoing role in advancing regulatory standards and transportation safety.

Martinez, Oscar [ORNL] (ORCID:0000000181814046)↗
DOE OSTI2025

Investigating the Relative Roles of INPs and CCN in a Simulated Thunderstorm Using a New Immersion Freezing Algorithm

Microphysical processes in deep convective clouds are sensitive to the number concentrations of cloud condensation nuclei (CCN) and ice nucleating particles (INPs), but the effects of INPs are less studied. Modeling studies investigating the effects of INPs and/or CCN on deep convection typically retain a volume‐dependent raindrop freezing relation. The resulting neglect of aerosol accumulation in raindrops via drop collisions has likely produced unrealistic storm responses to INPs in past studies. To address this deficiency, a new immersion freezing algorithm was developed and embedded in a bulk microphysics scheme that freezes both cloud drops and raindrops using the same immersion freezing INP (IF‐INP) activity spectrum based on measurements. Multiple idealized simulations of a single case of deep convection observed during the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign were conducted, with microphysical differences produced by independently altering IF‐INP temperature dependencies and CCN number concentrations from their observed values. Surface precipitation in all simulations resulted almost exclusively from riming graupel that melted upon descending to the surface. Rainfall and cold pools were substantially and systematically weakened with increased CCN due to decreased graupel riming rates but were relatively insensitive to variations in the magnitude and slope of IF‐INP spectra due to compensating depletion of supercooled liquid water. These compensating processes were a consequence of the accumulation of IF‐INPs in raindrops, encouraging caution in studying IF‐INP effects upon thunderstorms using traditional volume‐dependent drop freezing relationships.

CCN↗
DOE OSTI2023

COVID-19 Outcomes by Cancer Status, Site, Treatment, and Vaccination

Background: Studies have shown an increased risk of severe SARS-CoV-2–related (COVID-19) disease outcome and mortality for patients with cancer, but it is not well understood whether associations vary by cancer site, cancer treatment, and vaccination status. Methods: Using electronic health record data from an academic medical center, we identified a retrospective cohort of 260,757 individuals tested for or diagnosed with COVID-19 from March 10, 2020, to August 1, 2022. Of these, 52,019 tested positive for COVID-19 of whom 13,752 had a cancer diagnosis. We conducted Firth-corrected logistic regression to assess the association between cancer status, site, treatment, vaccination, and four COVID-19 outcomes: hospitalization, intensive care unit admission, mortality, and a composite “severe COVID” outcome. Results: Cancer diagnosis was significantly associated with higher rates of severe COVID, hospitalization, and mortality. These associations were driven by patients whose most recent initial cancer diagnosis was within the past 3 years. Chemotherapy receipt, colorectal cancer, hematologic malignancies, kidney cancer, and lung cancer were significantly associated with higher rates of worse COVID-19 outcomes. Vaccinations were significantly associated with lower rates of worse COVID-19 outcomes regardless of cancer status. Conclusions: Patients with colorectal cancer, hematologic malignancies, kidney cancer, or lung cancer or who receive chemotherapy for treatment should be cautious because of their increased risk of worse COVID-19 outcomes, even after vaccination. Impact: Additional COVID-19 precautions are warranted for people with certain cancer types and treatments. Further, significant benefit from vaccination is noted for both cancer and cancer-free patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Real-space representation of the quasiparticle self-consistent GW self-energy and its application to defect calculations

The quasiparticle self-consistent (QS) GW (G for Green's function, W for screened Coulomb interaction) approach incorporates the corrections of the quasiparticle energies from their Kohn-Sham density functional theory (DFT) eigenvalues by means of an energy-independent and Hermitian self-energy matrix usually given in the basis set of the DFT eigenstates. By expanding these into an atom-centered basis set (specifically here the linearized muffin-tin orbitals) a real space representation of the self-energy corrections becomes possible. In this work, We show that this representation is relatively short-ranged. This offers opportunities to construct the self-energy of a complex system from parts of the system by a cut-and-paste method. Specifically for a point defect, represented in a large supercell, the self-energy can be constructed from those of the host and a smaller defect-containing cell. The self-energy of the periodic host can be constructed simply from a GW calculation for the primitive cell. We show for the case of the As Ga in GaAs that the defect part can already be well represented by a minimal eight-atom cell and allows us to construct the self-energy for a 64-atom cell in good agreement with direct QSGW calculations for the large cell. Using this approach to an even larger 216-atom cell shows the defect band approaches an isolated defect level. The calculations also allow us to identify a second defect band which appears as a resonance near the conduction band minimum. The results on the extracted defect levels agree well with Green's function calculations for an isolated defect and with experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microwave impedance microscopy and its application to quantum materials

We report materials in which quantum mechanical effects lead to novel properties on the macroscopic scale are of interest both fundamentally and for applications. For such quantum materials, the ability to measure local conductivity and permittivity with nanoscale spatial resolution, minimal sample preparation, in a contact-free fashion and under a wide range of external conditions (such as temperature and magnetic field) is highly desirable. To this end, microwave impedance microscopy, a scanning probe technique that measures tip–sample admittance (inverse of impedance) in a non-contact geometry at microwave frequencies, has matured over the past decade to become a tool that can do just that. This Technical Review describes its fundamental working principles and practical implementations, discusses its application to a wide range of quantum materials, including correlated, topological and 2D van der Waals materials, and outlines future opportunities in expanding the capabilities of microwave impedance microscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Observation and characterisation of trapped electron modes in Wendelstein 7-X

In the past, quasi coherent (QC) modes were reported for nearly all tokamaks. The general definition describes modes as QC when the magnitude squared coherence is in the range of 0.3 to 0.6. QC modes are observed in the plasma core as well as in the plasma edge and can have quite different physical origins. The one in the core are observed in plasmas with low collisionality, where the electron temperature exceeds the ion temperature in the plasma core. This is the case for electron cyclotron heating in general. The origin of these modes are electrons trapped within a magnetic mirror, as reported in the past from various fusion devices. The so-called trapped-electron modes (TEMs) belong to drift wave instabilities and can be destabilized by electron-temperature gradients in the plasma core. From the diagnostic point of view, QC modes appear as fluctuations in electron density and temperature. Therefore, the microwave reflectometer is very well suited to monitor these modes. This paper describes experiments, conducted at the Wendelstein 7-X stellarator (W7-X), which aim at detecting QC modes at low wave numbers. A poloidal correlation reflectometer installed at W7-X, is able to measure low wave numbers ($k_\perp\unicode{x2A7D}{3.5}\,\textrm{cm}^{-1}$). For medium line-averaged densities ($\int n_\textrm{e}\unicode{x2A7D}{6 \times10^{19}}\,\textrm{m}^{-2}$) the plasma core is accessible for this diagnostic. For different magnetic configurations and plasma parameters, broad QC structures are observed in the coherence spectra. From the analysis of the rotation and the poloidal structure, these QC modes show the properties of electron-temperature-gradient driven TEMs. A linear relation between the mode velocity and the rotation frequency is found. The relation is uniform and confirms the nature of QC-mode observation as TEM in tokamaks, too.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Ultrafast photo-induced phonon hardening due to Pauli blocking in MAPbI 3 single-crystal and polycrystalline perovskites

Metal-halide perovskite semiconductors have attracted intense interest over the past decade, particularly for applications in photovoltaics. Low-energy optical phonons combined with significant crystal anharmonicity play an important role in charge-carrier cooling and scattering in these materials, strongly affecting their optoelectronic properties. We have observed optical phonons associated with Pb–I stretching in both MAPbI 3 single crystals and polycrystalline thin films as a function of temperature by measuring their terahertz conductivity spectra with and without photoexcitation. An anomalous bond hardening was observed under above-bandgap illumination for both single-crystal and polycrystalline MAPbI 3 . First-principles calculations reproduced this photo-induced bond hardening and identified a related lattice contraction (photostriction), with the mechanism revealed as Pauli blocking. For single-crystal MAPbI 3 , phonon lifetimes were significantly longer and phonon frequencies shifted less with temperature, compared with polycrystalline MAPbI 3 . We attribute these differences to increased crystalline disorder, associated with grain boundaries and strain in the polycrystalline MAPbI 3 . Thus we provide fundamental insight into the photoexcitation and electron–phonon coupling in MAPbI 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2024

Recent Progress on Dominant Sulfide‐Type Solid‐State Na Superionic Conductors for Solid‐State Sodium Batteries

Abstract Over the past decade, solid‐state batteries have garnered significant attentions due to their potentials to deliver high energy density and excellent safety. Considering the abundant sodium (Na) resources in contrast to lithium (Li), the development of sodium‐based batteries has become increasingly appealing. Sulfide‐based superionic conductors are widely considered as promising solid eletcrolytes (SEs) in solid‐state Na batteries due to the features of high ionic conductivity and cold‐press densification. In recent years, tremendous efforts have been made to investigate sulfide‐based Na‐ion conductors on their synthesis, compositions, conductivity, and the feasibility in batteries. However, there are still several challenges to overcome for their practical applications in high performance solid‐state Na batteries. This article provides a comprehensive update on the synthesis, structure, and properties of three dominant sulfide‐based Na‐ion conductors (Na 3 PS 4 , Na 3 SbS 4 , and Na 11 Sn 2 PS 12 ), and their families that have a variety of anion and cation doping. Additionally, the interface stability of these sulfide electrolytes toward the anode is reviewed, as well as the electrochemical performance of solid‐state Na batteries based on different types of cathode materials (metal sulfides, oxides, and organics). Finally, the perspective and outlook for the development and practical utilization of sulfide‐based SE in solid‐state batteries are discussed.

Guo, Xiaolin↗
DOE OSTI2024

On the emerging potential of quantum annealing hardware for combinatorial optimization

Abstract Over the past decade, the usefulness of quantum annealing hardware for combinatorial optimization has been the subject of much debate. Thus far, experimental benchmarking studies have indicated that quantum annealing hardware does not provide an irrefutable performance gain over state-of-the-art optimization methods. However, as this hardware continues to evolve, each new iteration brings improved performance and warrants further benchmarking. To that end, this work conducts an optimization performance assessment of D-Wave Systems’ Advantage Performance Update computer, which can natively solve sparse unconstrained quadratic optimization problems with over 5,000 binary decision variables and 40,000 quadratic terms. We demonstrate that classes of contrived problems exist where this quantum annealer can provide run time benefits over a collection of established classical solution methods that represent the current state-of-the-art for benchmarking quantum annealing hardware. Although this work does not present strong evidence of an irrefutable performance benefit for this emerging optimization technology, it does exhibit encouraging progress, signaling the potential impacts on practical optimization tasks in the future.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗