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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Helimagnetism in MnBi 2 Se 4 Driven by Spin-Frustrating Interactions Between Antiferromagnetic Chains

We report the magnetic properties and magnetic structure determination for a linear-chain antiferromagnet, MnBi 2 Se 4 . The crystal structure of this material contains chains of edge-sharing MnSe 6 octahedra separated by Bi atoms. The magnetic behavior is dominated by intrachain antiferromagnetic (AFM) interactions, as demonstrated by the negative Weiss constant of –74 K obtained by the Curie–Weiss fit of the paramagnetic susceptibility measured along the easy-axis magnetization direction. The relative shift of adjacent chains by one-half of the chain period causes spin frustration due to interchain AFM coupling, which leads to AFM ordering at TN = 15 K. Neutron diffraction studies reveal that the AFM ordered state exhibits an incommensurate helimagnetic structure with the propagation vector k = (0, 0.356, 0). The Mn moments are arranged perpendicular to the chain propagation direction (the crystallographic b axis), and the turn angle around the helix is 128°. The magnetic properties of MnBi2Se4 are discussed in comparison to other linear-chain antiferromagnets based on ternary mixed-metal halides and chalcogenides.

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

IEEE PES GM Poster - Cyber-Informed Engineering Approach to Mitigating BESS Supply Chain Concerns

Battery energy storage systems (BESS) are increasingly important to meet the needs of grid resilience and reliability. BESS provide critical grid services, maintaining stability of the grid with increased variable conditions. However, there are significant geopolitical and security concerns regarding their operation in critical infrastructure, due to lack of a domestic supply chain and prevalence of foreign entity of concern (FEOC) components in BESS and associated inverter-based resources. The supply chain challenge is dually exacerbated by a lack of alternative suppliers who can meet the economic targets for energy delivery and a potentially adversarial supply chain. Solutions are needed to secure components, addressing mixed layers of risk and engineering controls. This paper presents a specific application of Cyber-Informed Engineering (CIE) principles for BESS and recommends an alternative strategy to blocking the supply chain, ensuring that grid modernization targets can be met despite lack of a validated or secure supply chain. This study focuses on the United State (U.S.) use case, but the process can be applied globally to address supply chain security challenges. CIE practices represent the next step in functional assurance and risk mitigation, ensuring optimal resource allocation and enhancing security measures to safeguard the future of energy in the U.S. and beyond.

25 - ENERGY STORAGE↗
DOE OSTI2023

Gap Analysis of Supply Chain Cybersecurity for Distributed Energy Resources

A supply chain is the combination of the ecosystem of resources needed to design, manufacture, and distribute a product. In the context of supply chain cybersecurity, the resources that directly influence this ecosystem include software, data, and/or other digital components. Compromised equipment or software in the supply chain may lead to attacks such as financial loss; denial of service; a breach of confidential or proprietary information from a company, its customers, or its suppliers; ransomware that denies operation of automated equipment for payment; and malicious control actions that could damage equipment and endanger personnel. Currently 60.8% of US energy comes from fossil fuels, 18.9% comes from nuclear energy, and the last 20.1% comes from renewable sources. Federal Energy Regulatory Commission order FERC 2222 and Executive Order 14017 on America's Supply Chains are important milestones for safely expanding generation from renewable energy and achieving the goal of a decarbonized U.S. energy sector by 2035. This report analyzes gaps and opportunities in the supply chain currently available to the renewable energy sector, to help stakeholders formulate a coordinated response.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Crystal Structure and Characterization of Human Heavy-Chain Only Antibodies Reveals a Novel, Stable Dimeric Structure Similar to Monoclonal Antibodies

We report the novel crystal structure and characterization of symmetrical, homodimeric humanized heavy-chain-only antibodies or dimers (HC2s). HC2s were found to be significantly coexpressed and secreted along with mAbs from transient CHO HC/LC cotransfection, resulting in an unacceptable mAb developability attribute. Expression of full-length HC2s in the absence of LC followed by purification resulted in HC2s with high purity and thermal stability similar to conventional mAbs. The V H and C H 1 portion of the heavy chain (or Fd) was also efficiently expressed and yielded a stable, covalent, and reducible dimer (Fd2). Mutagenesis of all heavy chain cysteines involved in disulfide bond formation revealed that Fd2 intermolecular disulfide formation was similar to Fabs and elucidated requirements for Fd2 folding and expression. For one HC2, we solved the crystal structure of the Fd2 domain to 2.9 Å, revealing a highly symmetrical homodimer that is structurally similar to Fabs and is mediated by conserved (C H 1) and variable (V H ) contacts with all CDRs positioned outward for target binding. Interfacial dimer contacts revealed by the crystal structure were mutated for two HC2s and were found to dramatically affect HC2 formation while maintaining mAb bioactivity, offering a potential means to modulate novel HC2 formation through engineering. These findings indicate that human heavy-chain dimers can be secreted efficiently in the absence of light chains, may show good physicochemical properties and stability, are structurally similar to Fabs, offer insights into their mechanism of formation, and may be amenable as a novel therapeutic modality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Generative AI in Supply Chain Management: Applications, Challenges, and Future Directions

Supply chain management (SCM) is undergoing rapid transformation due to increasing global complexity, demand volatility, and operational disruptions. Generative Artificial Intelligence (GenAI) has emerged as a powerful paradigm capable of synthesizing data, simulating operational scenarios, and enabling adaptive decision-making across supply chain networks. This paper presents a survey of GenAI’s role in SCM, focusing on its applications in predictive analytics, autonomous logistics, and fraud detection. Unlike traditional AI systems that rely primarily on predictive analytics, GenAI models, including large language models, generative adversarial networks, and diffusion-based architectures, enable the creation of synthetic supply chain scenarios and autonomous optimization strategies. This survey provides (1) a taxonomy of GenAI techniques for supply chain applications, (2) a comparative analysis of generative AI approaches with traditional machine learning, reinforcement learning, and blockchain-based methods, and (3) a discussion of key challenges such as data privacy, interpretability, and integration with legacy enterprise systems. Furthermore, we outline open research problems and propose directions for future research toward autonomous, resilient, and sustainable AI-driven supply chains.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2024

Business Opportunities in Clean Energy Supply Chains: Guidebook for Small and Medium-Sized Automotive Suppliers

This is the final report for the referenced TCF award which ran from Oct. 2019 through Jan. 2024 in conjunction with the industry partner Swift Solar. The long duration of the program was due to several factors including the pandemic and a technical work stoppage due to changes in the scope. Additionally, Swift’s business focus shifted during the course of the program. As a result of these factors, this program underwent two distinct modifications that dramatically changed the work scope. The following report is organized into three separate sections, each of which addresses a distinct work scope. Those scope changes, what necessitated them, and any new tasks/milestones are given, briefly, at the top of each section. The work performed was research on the hybrid halide perovskites (HHP), both the absorber material itself as well as other material layers that are required in a full device stack. At the start of the period of performance, there were two distinct challenges that we sought to address: (1) a wide band gap absorber (>1.6 eV), and (2) a recombination layer for tandem devices that provided good sequestration of the individual cell absorber materials in their respective device layers. NREL had previously published, and patented, advancements in both of these areas and they were the focus of much of the work throughout the program. The auto manufacturing space is evolving quickly. Sales of various electrified vehicles (xEVs) continue to grow steadily, which has medium to long-term ramifications for the thousands of U.S. manufacturers and hundreds of thousands of workers that contribute to the domestic automotive supply chain. In tandem with this growth in xEV sales, domestic clean energy manufacturing is surging (both for the xEV supply chain and other technologies), with public incentives spurring billions in private sector investment. Moreover, the next 2–3 years will see new and expanded industrial facilities come online to make products like hydrogen electrolyzers, solar panels, batteries, advanced electronics—and will create new supply chain needs and business opportunities as they do. DOE’s Office of Manufacturing and Energy Supply Chains (MESC) and Argonne National Laboratory developed this report to help automotive manufacturers—alongside various business support partners— understand these trends and their response options, and to make the most of current federal assistance programs for manufacturers. These market changes may create opportunities for small- and medium-sized manufacturers (SMMs) to expand production, grow profit margins, and diversify their businesses. For instance, SMMs could take advantage of engineering and process design similarities with new end-use industries that might enable greater business growth and stability as markets continue to change.

14 SOLAR ENERGY↗
DOE OSTI2022

Polymerized Small Molecular Acceptor with Branched Side Chains for All Polymer Solar Cells with Efficiency over 16.7%

The power conversion efficiencies (PCEs) of small molecule acceptor (SMA)-based organic solar cells have already exceeded 18%. However, the development of polymer acceptors still lags far behind their SMA counterparts mainly due to the lack of efficient polymer acceptors. In this work, a series of polymer acceptors named PY-X (with X being the branched alkyl chain) are designed and synthesized by employing the same central core with the SMA L8-BO but with different branched alkyl chains on the pyrrole motif. It is found that the molecular packing of SMA-HD featuring 2-hexyldecyl side chain used in the synthesis of PY-HD is similar to L8-BO, in which the branched alkyl chains lead to condensed and high-order molecular assembly in SMA-HD molecules. When combined with PM6, PY-HD-based all polymer solar cell (all-PSC) exhibits a high PCE of 16.41%, representing the highest efficiency for the binary all-PSCs. Moreover, the side-chain modification on the pyrrole site position further improves the performance of the all-PSCs, and the PY-DT-based device delivers a new record high efficiency of 16.76% (certified as 16.3%). The work provides new insights for understanding the structure–property relationship of polymer acceptors and paves a feasible avenue to develop efficient conjugated polymer acceptors.

14 SOLAR ENERGY↗
DOE OSTI2021

A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions

We develop an Evolutionary Markov Chain Monte Carlo (EMCMC) algorithm for sampling spatial partitions that lie within a large, complex, and constrained spatial state space. Our algorithm combines the advantages of evolutionary algorithms (EAs) as optimization heuristics for state space traversal and the theoretical convergence properties of Markov Chain Monte Carlo algorithms for sampling from unknown distributions. Local optimality information that is identified via a directed search by our optimization heuristic is used to adaptively update a Markov chain in a promising direction within the framework of a Multiple-Try Metropolis Markov Chain model that incorporates a generalized Metropolis-Hastings ratio. We further expand the reach of our EMCMC algorithm by harnessing the computational power afforded by massively parallel computing architecture through the integration of a parallel EA framework that guides Markov chains running in parallel.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Evaluation of strategies to narrow the product chain-length distribution of microbially synthesized free fatty acids

The dominant strategy for tailoring the chain-length distribution of free fatty acids (FFA) synthesized by heterologous hosts is expression of a selective acyl-acyl carrier protein (ACP) thioesterase. However, few of these enzymes can generate a precise (greater than 90% of a desired chain-length) product distribution when expressed in a microbial or plant host. The presence of alternative chain-lengths can complicate purification in situations where blends of fatty acids are not desired. We report the assessment of several strategies for improving the dodecanoyl-ACP thioesterase from the California bay laurel to exhibit more selective production of medium-chain free fatty acids to near exclusivity. We demonstrated that matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) was an effective library screening technique for identification of thioesterase variants with favorable shifts in Journal Pre-proof chain-length specificity. This strategy proved to be a more effective screening technique than several rational approaches discussed herein. With this data, we isolated four thioesterase variants which exhibited a more selective FFA distribution over wildtype when expressed in the fatty acid accumulating E. coli strain, RL08. We then combined mutations from the MALDI isolates to generate BTE-MMD19, a thioesterase variant capable of producing free fatty acids consisting of 90% of C12 products. Of the four mutations which conferred a specificity shift, we noted that three affected the shape of the binding pocket, while one occurred on the positively charged acyl carrier protein landing pad. Lastly, we fused the maltose binding protein (MBP) from E. coli to the N – terminus of BTE-MMD19 to improve enzyme solubility and achieve a titer of 1.9 g per L of twelve-carbon fatty acids in a shake flask.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Weakly coupled alternating S = 1 2 chains in the distorted honeycomb lattice compound Na 2 Cu 2 TeO 6

Spin- 1 2 chains with alternating antiferromagnetic (AF) and ferromagnetic (FM) couplings exhibit quantum entanglement as the integer-spin Haldane chains and might be similarly utilized for quantum computations. Such alternating AF-FM chains have been proposed to be realized in the distorted honeycomb lattice compound Na 2 Cu 2 TeO 6 , but to confirm this picture a comprehensive understanding of the exchange interactions including terms outside of the idealized model is required. Here, we employ neutron scattering to study the spin dynamics in Na 2 Cu 2 TeO 6 and accurately determine the coupling strengths through the random phase approximation and density functional theory approaches. We find the AF and FM intrachain couplings are the dominant terms in the spin Hamiltonian, while the interchain couplings are AF but perturbative. This hierarchy in the coupling strengths and the alternating signs of the intrachain couplings can be understood through their different exchange paths. Our results establish Na 2 Cu 2 TeO 6 as a weakly coupled alternating AF-FM chain compound and reveal the robustness of the gapped ground state in alternating chains under weak interchain couplings.

1-dimensional spin chains↗
DOE OSTI2021

Perturbative instability of nonergodic phases in non-Abelian quantum chains

An important challenge in the field of many-body quantum dynamics is to identify nonergodic states of matter beyond many-body localization (MBL). Strongly disordered spin chains with non-Abelian symmetry and chains of non-Abelian anyons are natural candidates, as they are incompatible with standard MBL. In such chains, real space renormalization group methods predict a partially localized, nonergodic regime known as a quantum critical glass (a critical variant of MBL). Here, this regime features a treelike hierarchy of integrals of motion and symmetric eigenstates with entanglement entropy that scales as a logarithmically enhanced area law. We argue that such tentative nonergodic states are perturbatively unstable using an analytic computation of the scaling of off-diagonal matrix elements and accessible level spacing of local perturbations. Our results indicate that strongly disordered chains with non-Abelian symmetry display either spontaneous symmetry breaking or ergodic thermal behavior at long times. We identify the relevant length and timescales for thermalization: Even if such chains eventually thermalize, they can exhibit nonergodic dynamics up to parametrically long timescales with a nonanalytic dependence on disorder strength.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Random-exchange Heisenberg behavior in the electron-doped quasi-one-dimensional spin-1 chain compound AgVP 2 ⁢S 6

Recent theoretical work suggests that a pair-density wave superconducting state can be realized by doping a one-dimensional spin-1 chain. Here, we report the physical properties of single crystals of Mg x Ag 1–x VP 2 S 6 [x = 0, x = 0.017(6), x = 0.067(8), and 0.098(11)] prepared by solid-state synthesis. Single-crystal x-ray-diffraction measurements confirm that Mg 2+ is substituting for Ag + to electron dope the V 3+ zigzag chains. Magnetization measurements reveal that electron doping breaks up the V 3+ chains, resulting in unpaired spins at the chain ends. The Mg x Ag 1–x VP 2 S 6 series is consistent with random-exchange Heisenberg antiferromagnetic chain behavior and can be well described by the exchange-coupled pair model at low temperatures. As a result, transport measurements show Mg x Ag 1–x VP 2 S 6 remains insulating in the range 0 ≤ x ≤ 0.098(11), with the band gap decreasing to ~ 0.2 eV at x = 0.098(11).

1-dimensional spin chains↗
DOE OSTI2021

The FEWSION for Community Resilience (F4R) Process: Building Local Technical and Social Capacity for Critical Supply Chain Resilience

Local business leaders, policy makers, elected officials, city planners, emergency managers, and private citizens are responsible for, and deeply affected by, the performance of critical supply chains and related infrastructures. At the center of critical supply chains is the food-energy-water nexus (FEW); a nexus that is key to a community’s wellbeing, resilience, and sustainability. In the 21st century, managing a local FEW nexus requires accurate data describing the function and structure of a community’s supply chains. However, data is not enough; we need data-informed conversation and technical and social capacity building among local stakeholders to utilize the data effectively. There are some resources available at the mesoscale and for food, energy, or water, but many communities lack the data and tools needed to understand connections and bridge the gaps between these scales and systems. As a result, we currently lack the capacity to manage these systems in small and medium sized communities where the vast majority of people, decisions, and problems reside. This study develops and validates a participatory citizen science process for FEW nexus capacity building and data-driven problem solving in small communities at the grassroots level. The FEWSION for Community Resilience (F4R) process applies a Public Participation in Scientific Research (PPSR) framework to map supply chain data for a community’s FEW nexus, to identify the social network that manages the nexus, and then to generate a data-informed conversation among stakeholders. F4R was piloted and co-developed with participants over a 2-year study, using a design-based research process to make evidence-based adjustments as needed. Results show that the F4R model was successful at improving volunteers’ awareness about nexus and supply chain issues, at creating a network of connections and communication with stakeholders across state, regional, and local organizations, and in facilitating data-informed discussion about improvements to the system. In this paper we describe the design and implementation of F4R and discuss four recommendations for the successful application of the F4R model in other communities: 1) embed opportunities for co-created PPSR, 2) build social capital, 3) integrate active learning strategies with user-friendly digital tools, and 4) adopt existing materials and structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

DeepComplex: A Web Server of Predicting Protein Complex Structures by Deep Learning Inter-chain Contact Prediction and Distance-Based Modelling

Proteins interact to form complexes. Predicting the quaternary structure of protein complexes is useful for protein function analysis, protein engineering, and drug design. However, few user-friendly tools leveraging the latest deep learning technology for inter-chain contact prediction and the distance-based modelling to predict protein quaternary structures are available. To address this gap, we develop DeepComplex, a web server for predicting structures of dimeric protein complexes. It uses deep learning to predict inter-chain contacts in a homodimer or heterodimer. The predicted contacts are then used to construct a quaternary structure of the dimer by the distance-based modelling, which can be interactively viewed and analysed. The web server is freely accessible and requires no registration. It can be easily used by providing a job name and an email address along with the tertiary structure for one chain of a homodimer or two chains of a heterodimer. The output webpage provides the multiple sequence alignment, predicted inter-chain residue-residue contact map, and predicted quaternary structure of the dimer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Supply Chain for Photovoltaics in the United States: 2024 in Review

Solar photovoltaic (PV) and battery energy storage system (BESS) technologies are two immediately available options for meeting U.S. electricity demands, which are increasing due to expansion of loads from end uses including data centers, buildings, vehicles, and factories. Globally, PV and BESS supply chains are dominated by products manufactured in China and elsewhere by Chinese companies. However, U.S. PV and BESS manufacturing have recently grown, with some capacity in each step of the PV supply chain, albeit not enough to currently meet demand with domestic manufacturing alone. This study analyzes U.S. PV supply chains and costs in 2024, for the crystalline silicon and cadmium telluride module supply chains. The full report additionally addresses the PV balance of system, inverter and BESS supply chains. The study concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.

14 SOLAR ENERGY↗
DOE OSTI2025

Protein–Protein Complex Stability Controls Substrate Scope in a β‐Ketoacyl‐ACP Reductase Specific for Medium Chains

Assembly-line enzymes carry out multistep synthesis of important metabolites by using acyl carrier proteins (ACPs) to shuttle intermediates along defined sequences of active sites. Despite longstanding interest in reprogramming these systems for metabolic engineering and biosynthetic chemistry, the mechanisms underlying their reaction order remain poorly understood and difficult to control. In this work, we describe a β-ketoacyl-ACP reductase from Pseudomonas putida (PpFabG4) with an unusual selectivity for medium chains and use it to explore the molecular basis of substrate specificity in enzymes that pull intermediates from fatty acid synthesis, a common route to specialized products. X-ray crystallography shows no obvious barriers to short-chain binding. Molecular simulations and supporting mutational analyses indicate that substrate preference arises instead from a weak enzyme–ACP interaction that is stabilized by medium acyl chains but not by short chains. Indeed, mutations that strengthen this interaction for PpFabG4 or weaken it for EcFabG, an Escherichia coli β-ketoacyl-ACP reductase with a broad substrate specificity, can enhance or reduce activity on short-chain substrates by over 100-fold. Our findings show how the stability of enzyme-ACP interactions can control substrate scope in promiscuous enzymes and guide the exchange of intermediates between (and within) assembly-line systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Chain trajectories, domain shapes, and terminal boundaries in block copolymers

The packing geometry of macromolecules in complex mesophases is of key importance to self-organization in synthetic and biological soft materials. While approximate or heuristic models rely on often-untested assumptions about how flexible molecules “fit in” to distinct locations of complex assemblies, physical assemblies derive from ensembles of fluctuating conformations, obscuring the connection between mesophase geometry and the underlying arrangements. Here, we present an approach to extract and analyze features of molecular packing in diblock block copolymer (BCP) melts, a prototypical soft matter system, based on the statistical description of chain conformations in self-consistent field (SCF) theory. We show how average BCP chain trajectories in ordered morphologies can be analyzed from the SCF-derived orientational order parameter of chain segments. We use these extracted trajectories to analyze the features of local packing geometry, including chain bending and tilt, as well as the terminal boundaries that delineate distinct domains in ordered BCP morphologies. In conclusion, we illustrate this analysis by focusing on measurable features of packing frustration in 2D (columnar) and 3D (spherical and bicontinuous) morphologies, notably establishing an explicit link between chain conformations in complex morphologies and their medial geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗