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NASA NTRSDate not supplied

Architectural Framework for Conceptualizing Exploration Class Medical Operations

Currently, discrete projects within NASA’s Human Research Program (HRP) take aim at providing future exploration missions with the capabilities necessary to operate within a progressively Earth-independent operative environment. Realizing an entire ecosystem that can accomplish these goals requires a clear visualization on how each project contributes to the overall objectives of Human Health and Performance (HH&P) in that context. The Exploration Medical Capability (ExMC) Element has developed an architectural framework for exploration class medical operations by utilizing a systems engineering approach using model-based systems engineering (MBSE). This model, a System of Systems Architecture (SoSA), captures a means of integrating various independent but related efforts into a comprehensive view associated with HRP’s goal of providing progressively Earth-Independent Medical Operations (EIMO). This level of visibility is realized by identifying interfaces between development efforts and existing programs that contribute to the overall mission of EIMO even if those extend past the traditional boundary of HRP. Potential interfaces that are considered important when constructing an architecture include program/project Needs, Goals, and Objectives (NGOs), capabilities, envisioned use cases/scenarios, and system/subsystem structure. This presentation will focus on the processes that were used to generate the SoSA along with a means to realize its utility amongst other MBSE products from ExMC. Evaluation of the best architecture moving forward can then be achieved that promotes cohesion between various functional areas of HH&P. Additionally, the SoSA is developed with a long-term vision for the dynamic integration of novel technological developments that may be implemented in the future. The SoSA is intended to enable Stakeholders the ability to view the broader interconnections that exist and begin to create avenues of communication between various efforts. The benefits of a SoSA provide an essential step towards addressing the unique challenges of attaining the goals of broader exploration class medical missions of the future.

Systems engineering↗
NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗
NASA NTRS2024

Architectural Framework for Conceptualizing Exploration Class Medical Operations

Currently, discrete projects within NASA’s Human Research Program (HRP) take aim at providing future exploration missions with the capabilities necessary to operate within a progressively Earth-independent operative environment. Realizing an entire ecosystem that can accomplish these goals requires a clear visualization on how each project contributes to the overall objectives of Human Health and Performance (HH&P) in that context. The Exploration Medical Capability (ExMC) Element has developed an architectural framework for exploration class medical operations by utilizing a systems engineering approach using model-based systems engineering (MBSE). This model, a System of Systems Architecture (SoSA), captures a means of integrating various independent but related efforts into a comprehensive view associated with HRP’s goal of providing progressively Earth-Independent Medical Operations (EIMO). This level of visibility is realized by identifying interfaces between development efforts and existing programs that contribute to the overall mission of EIMO even if those extend past the traditional boundary of HRP. Potential interfaces that are considered important when constructing an architecture include program/project Needs, Goals, and Objectives (NGOs), capabilities, envisioned use cases/scenarios, and system/subsystem structure. This presentation will focus on the processes that were used to generate the SoSA along with a means to realize its utility amongst other MBSE products from ExMC. Evaluation of the best architecture moving forward can then be achieved that promotes cohesion between various functional areas of HH&P. Additionally, the SoSA is developed with a long-term vision for the dynamic integration of novel technological developments that may be implemented in the future. The SoSA is intended to enable Stakeholders the ability to view the broader interconnections that exist and begin to create avenues of communication between various efforts. The benefits of a SoSA provide an essential step towards addressing the unique challenges of attaining the goals of broader exploration class medical missions of the future.

Systems engineering↗
NASA NTRSDate not supplied

Contracting Quality Early in the Lifecycle Using AS9145 Data Deliverables

Development schedules and a highly dynamic supply chain are a challenge to developers of complex systems produced at low volume. Flaws in designs, parts and materials availability problems, poor manufacturability, and a lack of knowledge about critical items and key process attributes can be realized well before traditional second-party quality assurance activities begin. Supplier audits and product inspections may have little mitigating effect once these foundational problems have been realized. Their impacts can be significant lifecycle disruption, cost overruns, inability to deliver to plan, and even project cancellation. AS9145, Requirements for Advanced Product Quality Planning and Production Part Approval Process, can be used to drive quality engineering practices into early development lifecycles to significantly reduce this late-cycle risk and to reduce the cost of quality overall. Since its initial publication in 2016, it has had very limited adoption by the DoD, no adoption by NASA, and sparse adoption in the aerospace and defense supply chain. A task group within the Aerospace Industries Association's (AIA) Joint Strategic Quality Council (JSQC) identified that both acquirers and suppliers see as AS9145 as a cost-adder and are hesitant to use it as an alternative to late-stage-heavy quality assurance approaches. A lack of prior use creates large capability gaps in request-for-proposal (RFP) teams, proposal teams, suppliers’ quality management systems (QMS), and in experienced personnel executing the early lifecycle approach. To create a more realizable on-ramp for using AS9145 in the space and defense sectors, the AIA JSQC task team created five deliverable requirements descriptions (DRDs) that can be used in a contract to begin to engage both parties in early lifecycle quality engineering and quality assurance activities, that reduce exposure to late-stage cost and schedule collapse due to unidentified risks in design, supply chain, and manufacturability. These DRDs drive the parties to engage in planning and analysis discussions early on to understand what production risks can be known and how they will focus resources based on safety criticality and the key elements of design and construction. The suppliers and acquirers who will produce the data and information required by the DRD will be able to incrementally evolve their QMS and the acquirer will incrementally be able to track and understand the benefits of cost shifting from late to early development phases. A white paper describing this approach and the five recommended DRDs will be published by the AIA in late 2024 or early 2025.

Jeannette Plante↗
DOE OSTI2020

Market Segmentation Analysis of Medium and Heavy Duty Trucks with a Fuel Cell Emphasis

The medium- and heavy-duty transportation sector is experiencing rapid changes in powertrain technology innovation with recent announcements of battery electric and fuel cell electric trucks being offered. However, the economics of these alternative powertrain vehicles are uncertain and difficult to compare directly. This analysis seeks to bridge the gap of techno-economic analyses for these alternative powertrain vehicles by comparing all of them within the same analytic framework. Specifically, this report evaluates the total cost of ownership (TCO) of six different truck powertrain technologies (diesel, diesel hybrid-electric, plug-in hybrid electric, compressed natural gas, battery electric, and fuel cell electric) for three different truck vocations (Class 8 long haul [750 mile range], Class 8 short haul [300 mile range], and Class 4 parcel delivery), for different Department of Energy technology statuses (2018, 2025, and Ultimate). The TCO framework includes direct costs (purchase price, fuel, operating and maintenance), indirect costs (dwell time costs due to refueling/recharging and payload opportunity costs from forgone revenue due to the truck being weight-limited), but excludes general operation costs (driver wages and benefits, insurance, tire replacements, permits, tolls) that are assumed to be the same across powertrains. The TCO was evaluated for four scenarios that reflect typical business operating conditions. The TCO analysis results highlight that each powertrain technology may have an economic advantage on a TCO basis in certain business operating conditions and depending on fuel price realized. For Class 8 long haul trucks when payload opportunity costs are not incurred, battery electric and fuel cell electric powertrains could be cost competitive with diesel if the 2025 targets are achieved and fuel prices are low. If payload opportunity costs are incurred, battery electric powertrains are not estimated to reach TCO parity with diesel even if Ultimate targets and low electricity prices are realized, indicating a need for significant vehicle lightweighting. In Class 8 short haul commercial applications when payload opportunity costs are not incurred, battery electric, fuel cell electric, and compressed natural gas vehicle powertrains have very competitive TCOs with diesel if the 2025 targets are achieved. In Class 8 short haul commercial applications when payload opportunity costs are incurred, the battery electric vehicle powertrains can achieve TCO parity with diesel only if the Ultimate battery prices are met ($80/kWh). In Class 4 parcel delivery truck operating scenarios where there are no dwell time costs incurred, the plug-in hybrid electric vehicle, battery electric vehicle, and fuel cell electric vehicle could be cost-competitive with diesel and compressed natural gas with current (2018) technology performance and costs. In general, the payload opportunity costs can be a significant driver to TCO for the Class 8 long and short haul commercial vehicle applications while the dwell time costs could be a major TCO cost driver for the Class 4 parcel delivery vehicle if the business scenario realizes those costs.

advanced powertrains↗
DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator

Designing manufacturing processes with high yield and strong reliability relies on effective methods for rare event estimation. Genealogical importance splitting reduces the variance of rare event probability estimators by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is difficult when applied to deterministic systems where the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. However, this random perturbation strategy may be effective for some systems while failing for others, preventing variance reduction in the probability estimate. This work seeks to address this limitation using a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The proposed GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗
DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator: Preprint

To reduce the variance of rare event probability estimator, genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. It is shown that a random perturbation strategy may be effective for some systems but may also fail for others, thereby preventing variance reduction in the probability estimate. To address this limitation, it is proposed to use a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗
DOE OSTI2020

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

PFLOTRAN: Reactive Flow & Transport Code for Use on Laptops to Leadership-Class Supercomputers. In: Groundwater Reactive Transport Models

PFLOTRAN, a next-generation reactive flow and transport code for modeling subsurface processes, has been designed from the ground up to run efficiently on machines ranging from leadership-class supercomputers to laptops. Based on an object-oriented design, the code is easily extensible to incorporate additional processes. It can interface seamlessly with Fortran 9X, C and C++ codes. Domain decomposition parallelism is employed, with the PETSc parallel framework used to manage parallel solvers, data structures and communication. Features of the code include a modular input file, implementation of high-performance I/O using parallel HDF5, ability to perform multiple realization simulations with multiple processors per realization in a seamless manner, and multiple modes for multiphase flow and multicomponent geochemical transport. Chemical reactions currently implemented in the code include homogeneous aqueous complexing reactions and heterogeneous mineral precipitation/dissolution, ion exchange, surface complexation and a multirate kinetic sorption model. PFLOTRAN has demonstrated petascale performance using 217 processor cores on problems composed of over 2 billion degrees of freedom. The code is currently being applied to simulate uranium transport at the Hanford 300 Area and CO2 sequestration in deep geologic formations.

carbon sequestration↗
NASA NTRSDate not supplied

Authoring, Analyzing, and Monitoring Requirements for a Lift-Plus-Cruise Aircraft

Requirements specification and analysis is widely applied to ensure the correctness of industrial systems in safety critical domains. Requirements are often initially written in natural language, which is highly ambiguous, and as a second step transformed into a language with rigorous semantics for formal analysis. [Question/problem] In this paper, we report on our experience in requirements creation and analysis, as well as run-time monitor generation using the Formal Requirement Elicitation Tool (FRET), on an industrial case study for a Lift-Plus-Cruise concept aircraft. [Principal ideas/results] We study the creation of requirements directly in the structured language of FRET without a prior definition of the same requirements in natural language. We focus on requirements describing state machines and discuss the challenges that we faced, in terms of creating requirements and generating monitors. We demonstrate how realizability, i.e., checking whether a requirements specification can be implemented, is crucial for understanding temporal interdependencies among requirements. [Contribution] Our study is the first complete attempt at using FRET to create industrial, realizable requirements and generate run-time monitors. Insight from lessons learned was materialized into new features in the FRET and JKind analysis frameworks.

Requirements engineering↗
NASA NTRSDate not supplied

Authoring, Analyzing, and Monitoring Requirements for a Lift-Plus-Cruise Aircraft

Requirements specification and analysis is widely applied to ensure the correctness of industrial systems in safety critical domains. Requirements are often initially written in natural language, which is highly ambiguous, and as a second step transformed into a language with rigorous semantics for formal analysis. In this paper, we report on our experience in requirements creation and analysis, as well as run-time monitor generation using the Formal Requirement Elicitation Tool (FRET), on an industrial case study for a Lift-Plus-Cruise concept aircraft. We study the creation of requirements directly in the structured language of FRET without a prior definition of the same requirements in natural language. We focus on requirements describing state machines and discuss the challenges that we faced, in terms of creating requirements and generating monitors. We demonstrate how realizability, i.e., checking whether a requirements specification can be implemented, is crucial for understanding temporal interdependencies among requirements. Our study is the first complete attempt at using FRET to create industrial, realizable requirements and generate run-time monitors. Insight from lessons learned was materialized into new features in the FRET and JKind analysis frameworks.

Requirements engineering↗
DOE OSTI2024

Environmental and economic analyses of chemical recycling via dissolution of waste polyethylene terephthalate

Globally, more than 1000 organizations and 175 nations are facing the plastic waste problem and have realized the need to transition from “linear-to-circular” economy of plastics. While the current mechanical recycling technologies for plastics are struggling to increase the U.S. plastic recycling rates beyond 9%, chemical recycling technologies become important complementary technologies to the predominant mechanical recycling that are needed to realize the circular economy in plastics supply chains. Dissolution is one such chemical recycling technology that can recycle waste plastic back into high-quality virgin grade plastic. However, the environmental and economic impacts of chemical recycling of waste polyethylene terephthalate (PET) via dissolution technology using a green solvent are unknown. Our study evaluated environmental metrics such as greenhouse gas (GHG) emissions and cumulative energy demand, and economic metrics such as net present value (NPV), minimum selling price, payback period, return on investment, and discounted internal rate of return for three dissolution processes with polymer recovery via anti-solvent, evaporation, and cooling precipitation techniques. The dissolution process with evaporation technique was the most economically favorable, whereas that with cooling technique was the most environmentally favorable. The anti-solvent approach had low economic performance and the highest environmental impacts. The NPV for all of these technologies ranged from $2.67 MM to $10.93 MM for a capacity of 8,400 MT/year and was found to be the highest for dissolution with evaporation approach and the least for anti-solvent approach. The cradle-to-gate GHG emissions and energy demand for PET dissolution processes ranged from 1.33-3.77 kg CO2-eq/kg of chemically recycled (CR) PET and18.9-56.1 MJ/kg of CR-PET, respectively. These economic and environmental metrics will be helpful in evaluating the sustainability of circular PET supply chains in the U.S.

09 BIOMASS FUELS↗
DOE OSTI2019

Efficient Quaternary Organic Solar Cells with Parallel‐Alloy Morphology

Abstract Two compatible donors (PBDB‐T and PTB7‐Th) and two miscible acceptors (ITIC and FOIC) are employed to deliver a parallel‐alloy morphology model in non‐fullerene‐based quaternary organic solar cells. PBDB‐T and PTB7‐Th form a parallel link with a slight adjustment of molecular packing into enhanced face‐on crystallites while ITIC disperses into discontinuous FOIC microcrystal regions to form continuous and ordered alloy‐like acceptor phases. Characterization of blend morphology highlights the parallel‐alloy model—enabled by the introduction of PBDB‐T and ITIC, which contributes to improved molecular packing and reduced domain size resulting in efficient charge generation and consistent transport channels. This successful parallel‐alloy quaternary blend morphology demonstrates an enhanced optical absorption, optimized domain size, and nanostructures toward simultaneous improvement in charge transfer and transport. Therefore, a power conversion efficiency of 12.52% is realized for a quaternary device which is 6% higher than the ternary device (PBDB‐T:PTB7‐Th:FOIC) and 12% higher than the binary device (PTB7‐Th:FOIC). Domination of quaternary devices over ternary and binary blends, which is another feasible way to realize highly efficient devices through further investigation of quaternary OSCs, is presented.

Bi, Zhaozhao↗
DOE OSTI2020

High-Power Lithium Metal Batteries Enabled by High-Concentration Acetonitrile-Based Electrolytes with Vinylene Carbonate Additive

To enable next-generation high power, high-energy-density lithium (Li) metal batteries (LMBs), an electrolyte possessing both high Li Coulombic efficiency (CE) at high-rate and good anodic stability on cathodes is critical. Acetonitrile (AN) is a well-known organic solvent for high anodic stability and high ionic conductivity, yet its application in LMBs is limited due to its poor compatibility with Li metal anode even at high salt concentration conditions. Here, we developed a highly concentrated AN-based electrolyte with vinylene carbonate (VC) additive to suppress Li+ depletion at high current densities. Addition of VC in the AN-based electrolyte leads to the formation of a polycarbonate-based solid electrolyte interphase which minimizes Li corrosion and leads to very high Li CE of up to 99.1% at a current density of 0.2 mA cm-2. Using such an electrolyte, fast charging of Li||NMC333 cells has been realized at a high current density of 3.6 mA cm-2, and stable cycling of Li||NMC622 cells with a high cathode loading of 4 mAh cm-2 has also been demonstrated.

Peng, Zhe↗
DOE OSTI2020

Van der Waals Nanowires with Continuously Variable Interlayer Twist and Twist Homojunctions

Abstract Moiré patterns at van der Waals interfaces between twisted 2D crystals give rise to distinct optoelectronic excitations, as well as, narrowly dispersive bands responsible for correlated electron phenomena. Contrasting with the conventional, mechanically stacked planar twist moirés, recent work shows twisted van der Waals interfaces spontaneously formed in nanowires of layered crystals, where Eshelby twist due to axial screw dislocations stabilizes a chiral structure with small interlayer rotation. Here, the realization of tunable twist in germanium(II) sulfide (GeS) van der Waals nanowires is reported. Tapered nanowires host continuously variable interlayer twist. Homojunctions between dislocated (chiral) and defect‐free (achiral) segments are obtained by triggering the emission of axial dislocations during growth. Measurements across such junctions, implemented here using local absorption and luminescence spectroscopy, provide a convenient tool for detecting twist effects. The results identify a versatile system for 3D twistronics, probing moiré physics, and for realizing moiré architectures without equivalent in planar systems.

Sutter, Peter↗
DOE OSTI2023

Bandwidth Control and Symmetry Breaking in a Mott‐Hubbard Correlated Metal

Abstract In Mott materials strong electron correlation yields a spectrum of complex electronic structures. Recent synthesis advancements open realistic opportunities for harnessing Mott physics to design transformative devices. However, a major bottleneck in realizing such devices remains the lack of control over the electron correlation strength. This stems from the complexity of the electronic structure, which often veils the basic mechanisms underlying the correlation strength. This study presents control of the correlation strength by tuning the degree of orbital overlap using picometer‐scale lattice engineering. This study illustrates how bandwidth control and concurrent symmetry breaking can govern the electronic structure of a correlated SrVO 3 model system. This study shows how tensile and compressive biaxial strain oppositely affect the SrVO 3 in‐plane and out‐of‐plane orbital occupancy, resulting in the partial alleviation of the orbital degeneracy. The spectral weight redistribution under strain is derived and explained, which illustrates how high tensile strain drives the system toward a Mott insulating state. Implementation of such concepts can push correlated electron phenomena closer toward new solid‐state devices and circuits. These findings therefore pave the way for understanding and controlling electron correlation in a broad range of functional materials, driving this powerful resource for novel electronics closer toward practical realization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Unconventional Spintronics from Chiral Perovskites

Spintronic devices typically employ heterostructures with ferromagnets which break time-reversal symmetry and have non-vanishing magnetization. With the growing class of materials that support spin-polarized carriers, current, and excitations, it is possible to envision emerging spintronic applications that are not limited to magnetoresistance. Here, chiral perovskites with no net magnetization are considered, where the space-inversion and mirror symmetries are broken to induce chiral structure. The known importance of these perovskites is further expanded by the demonstration of the chiral-induced spin selectivity (CISS). However, the generation of the spin-polarized carriers across the interface with these chiral perovskites remains to be fully understood. These first-principles studies for 2D PbBr4-based chiral perovskites provide their electronic structure and an orbital-based symmetry analysis, which allows to establish an effective Hamiltonian to elucidate the underlying origin of their chirality. The same analysis is used for the Edelstein effect, responsible for electrical generation of the nonequilibrium spin polarization in many materials, which in chiral perovskites can be a mechanism contributing to CISS. Furthermore, by examining optical properties of chiral perovskites and the opportunity to use them to realize tunable altermagnets, another class of zero-magnetization spintronic materials, a versatile materials platform is put forth for unconventional spintronics.

14 SOLAR ENERGY↗
DOE OSTI2026

The Evolution of Magnetism in a Thin Film Pyrochlore Ferromagnetic Insulator

The pyrochlore vanadates are compelling candidates for next-generation dissipationless devices. Lu 2 V 2 O 7 and Y 2 V 2 O 7 are ferromagnetic insulators (T c ~ 70 K) that are believed to exhibit the magnon Hall effect and are expected to host topological magnons. Their completely dissipationless magnon edge states could be harnessed to realize low-power information transport in spintronic or magnonic devices. As a crucial step in the realization of devices, we synthesize the first thin films of pyrochlore Y 2 V 2 O 7 on isostructural Y 2 V 2 O 7 substrates and explore the evolution of their magnetic properties down to the ultrathin limit. All films are insulating ferromagnets with transition temperatures of up to the bulk value (T c ~ 68 K) that decrease with thickness according to finite-size effects. Our films also exhibit a change in anisotropy from in-plane to out-of-plane easy axis coincident with the development of partial strain relaxation and nonzero magnetic hysteresis in an applied field. Furthermore, this evolution demonstrates the impact of strain on magnetic anisotropy and paves the way to tunable magnon topology.

Anderson, Margaret A. [Harvard University, Cambrid↗