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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Study of Environmental Arctic Change (SEARCH) Arctic Futures 2050 Conference. Final Report

The Arctic Futures 2050 Conference was designed as a novel convening of Arctic scientists, Indigenous people, and decision makers, including policy makers at all levels of government. The conference was held 4–6 September 2019 in Washington, D.C. and gathered nearly 400 participants to explore six questions: What do we know, and what do we need to know about the Arctic—and why does it matter? What challenges confront policy makers in the rapidly changing Arctic? What basic research is needed to inform responses to Arctic change? What applied research is needed to inform responses to change? What tools can facilitate informing policy making with science and Indigenous knowledge? What opportunities exist for partnerships between policy makers and scientists? A conference report (see: https://www.searcharcticscience.org/arctic-2050/conference-2019/products) detailed all conference discussions. The main conference conclusion was that holistic understanding and useful adaptation to rapid Arctic change requires bringing together scientists, Indigenous Knowledge holders, and policy makers in all phases of defining the problems, conducting research, and sharing knowledge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Pyrochlore-type lanthanide titanates and zirconates: Synthesis, structural peculiarities, and properties

This contribution provides a thorough examination of the structural characteristics of pyrochlore-type lanthanide titanates and zirconates Ln2Ti2O7 and Ln2Zr2O7, across various length scales. This paper also examines their processing, interesting physical properties (electrical, magnetic, and thermal characteristics), and responses to high pressure and ion irradiation. Brief sections on the elemental oxides' crystal chemistry, pertinent phase diagrams, and energetics of defect formation are also provided. Pyrochlore-type Ln2Ti2O7 and Ln2Zr2O7 stand out as truly multifunctional materials. Moreover, they have emerged as fascinating materials due to magnetic geometrical frustration, arising from the ordering of magnetic Ln3+ and non-magnetic Ti4+ (or Zr4+) cations into separate, interpenetrating lattices of corner-sharing tetrahedra. This results in a diverse array of exotic magnetic ground states, such as spin-ice (e.g., Dy2Ti2O7 or Ho2Ti2O7) or quantum spin ice (e.g., Tb2Ti2O7), observed at both low and room temperatures. They also exhibit varied electrical and electrochemical characteristics. Some members such as Gd2Zr2O7, function as fast ion conductors with a conductivity (σ) of ≈10−2 S·cm−1 at 800 °C and activation energy (Ea) ranging from 0.85 to 1.52 eV, depending on the degree of structural disorder. Others, such as Gd2TiMoO7, are mixed ionic-electronic conductors with σ ≈ 25 S·cm−1 at 1000 °C, making them promising candidate materials for applications in energy conversion and storage devices and oxygen separation membranes. Their exceptionally low thermal conductivity (e.g., κ ∼ 1.1–1.7 W·m−1·K−1 between 700 and 1200 °C for Ln2Zr2O7), close to the glass-like lower limit of highly disordered solids, positions them as valuable materials for thermal barrier coatings. They can also effectively accommodate actinides (e.g., Pu, Np, Cm, Am) in solid solutions and sustain prolonged exposure to radiation due to alpha-decay events, while preserving the integrity of the periodic atomic structure. Proposed as major components in actinide-bearing ceramics, they contribute to the long-term immobilization and disposal of long-lived waste radionuclides from nuclear programs. Some of these properties are displayed simultaneously, opening avenues for new applications. Despite the wealth of data available in the literature, this review highlights the need for a better understanding of order/disorder processes in pyrochlore-type materials and the influence of the structural length scale on their physical and chemical properties. Recent experimental evidence has revealed that pyrochlore short-range structure is far more complex than originally thought. Moreover, pyrochlore local structure is now believed to include short-range, lower symmetry, ordered domains, such as the orthorhombic weberite-type of structure. Notably, short- and long-range structures appear decoupled across different length scales and temperature regimes, and these differences persist even in well-ordered samples. We believe that the pyrochlore structure offers a unique opportunity for examining the interplay between chemical composition, defect chemistry, and properties. In Memoriam: Rodney C. Ewing, Fondly Remembered.

Physics↗
DOE OSTI2023

Glass Additive and Subtractive Manufacturing of a Fiber Optic Rotary Encoder for Downhole Pressure Sensing

This article presents a fiber optic rotary encoder-based pressure sensor for downhole applications. The rotary encoder, which is composed of an encoding pad and an all-glass optical fiber sensing head, converts the rotation angles of a pressure transducer to digital codes. The optical fiber only serves as the telemetry channel to directly transmit the data in digital format such that the environmental temperature influence and the long-time drift are minimized. The glass additive and subtractive manufacturing (ASM) techniques are used to embed the multichannel optical fibers into a bulk-fused silica glass substrate. Because the fused silica glass shares a similar material property to the optical fiber (e.g., thermal expansion coefficient), the optical fiber sensing head is well sealed and fixed even at an elevated temperature. The picosecond laser blackening technique is used to fabricate the high reflectivity contrast encoding pad with high accuracy. Here, the proposed pressure sensor was manufactured and experimentally verified to have a signal-to-noise ratio (SNR) of 23 dB and a linear pressure response with a root-mean-square error (RMSE) of 0.37. During the 400-h 250 °C long-term stability test, there was no digital code variation. In addition, a mathematical model to study the relationships between the sensor’s performances and design parameters was established. According to the model, a 12-bit encoder (0.02% pressure sensitivity) can be achieved with a radius of 20 mm.

02 PETROLEUM↗
DOE OSTI2025

Phenotypically anchored transcriptomics across diverse agrichemicals reveals conserved pathways and unique gene expression signatures in zebrafish

Agrichemicals such as herbicides, fungicides, insecticides, and biocides are widely used in agriculture, yet some are associated with adverse effects in humans and the environment. While many of these chemicals have been extensively studied in vitro and are included in the EPA’s ToxCast program, comprehensive in vivo comparisons using RNA sequencing across structurally diverse agrichemicals, in a single screening platform, are lacking. In this study, we examined structurally diverse agrichemicals found in the U.S. Environmental Protection Agency’s (EPA) Toxcast Phase I and II library by statically exposing early life stage zebrafish at 6 h post fertilization (hpf) until 120 hpf at concentrations ranging from 0.25 to 100 µM. Morphological outcomes were assessed at 120 hpf across 10 endpoints, including yolk sac edema, craniofacial malformations, and axis abnormalities. Chemicals that produced robust concentration-response relationships were selected for transcriptomic profiling. For transcriptomic analysis, zebrafish were statically exposed to each chemical and sampled at 48 hpf, prior to the onset of morphological effects observed at 120 hpf. Differential expression analysis identified between 0 and 4,538 differentially expressed genes (DEGs) per chemical, with no clear correlation to morphological severity. Both DEG and co-expression network analyses revealed chemical-specific expression patterns that converged on shared biological pathways, including neurodevelopment and cytoskeletal organization. Key regulatory genes such as mylpfa and krt4 were identified within co-expression modules, suggesting their potential role in conserved toxicity mechanisms. Semantic similarity analysis of enriched gene ontology (GO) terms, when compared to existing datasets, highlighted gaps in the annotation of neurodevelopmental processes, indicating that some in vivo effects may not be fully captured by current curated resources. The results provide new insights into the modes of action of diverse agrichemicals and establish a framework for understanding how agrichemical structure relates to biological function in a vertebrate model.

agrichemical↗
DOE OSTI2023

Identification of small-molecule protein–protein interaction inhibitors for NKG2D

NKG2D (natural-killer group 2, member D) is a homodimeric transmembrane receptor that plays an important role in NK, γδ + , and CD8 + T cell-mediated immune responses to environmental stressors such as viral or bacterial infections and oxidative stress. However, aberrant NKG2D signaling has also been associated with chronic inflammatory and autoimmune diseases, and as such NKG2D is thought to be an attractive target for immune intervention. Here, in this study, we describe a comprehensive small-molecule hit identification strategy and two distinct series of protein–protein interaction inhibitors of NKG2D. Although the hits are chemically distinct, they share a unique allosteric mechanism of disrupting ligand binding by accessing a cryptic pocket and causing the two monomers of the NKG2D dimer to open apart and twist relative to one another. Leveraging a suite of biochemical and cell-based assays coupled with structure-based drug design, we established tractable structure–activity relationships with one of the chemical series and successfully improved both the potency and physicochemical properties. Together, we demonstrate that it is possible, albeit challenging, to disrupt the interaction between NKG2D and multiple protein ligands with a single molecule through allosteric modulation of the NKG2D receptor dimer/ligand interface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Cation-Tethered Flowable Polymeric Interface for Enabling Stable Deposition of Metallic Lithium

A fundamental challenge, shared across many energy storage devices, is the complexity of electrochemistry at the electrode–electrolyte interfaces that impacts the Coulombic efficiency, operational rate capability, and lifetime. Specifically, in energy-dense lithium metal batteries, the charging/discharging process results in structural heterogeneities of the metal anode, leading to battery failure by short-circuit and capacity fade. In this work, we take advantage of organic cations with lower reduction potential than lithium to build an electrically responsive polymer interface that not only adapts to morphological perturbations during electrodeposition and stripping but also modulates the lithium ion migration pathways to eliminate surface roughening. As a result, we find that this concept can enable prolonging the long-term cycling of a high-voltage lithium metal battery by at least twofold compared to bare lithium metal.

25 ENERGY STORAGE↗
DOE OSTI2019

Structural basis for the evolution of cyclic phosphodiesterase activity in the U6 snRNA exoribonuclease Usb1

U6 snRNA undergoes post-transcriptional 3' end modification prior to incorporation into the active site of spliceosomes. The responsible exoribonuclease is Usb1, which removes nucleotides from the 3' end of U6 and, in humans, leaves a 2',3' cyclic phosphate that is recognized by the Lsm2–8 complex. Saccharomycescerevisiae Usb1 has additional 2',3' cyclic phosphodiesterase (CPDase) activity, which converts the cyclic phosphate into a 3' phosphate group. Here we investigate the molecular basis for the evolution of Usb1 CPDase activity. We examine the structure and function of Usb1 from Kluyveromyces marxianus, which shares 25 and 19% sequence identity to the S. cerevisiae and Homo sapiens orthologs of Usb1, respectively. We show that K. marxianus Usb1 enzyme has CPDase activity and determined its structure, free and bound to the substrate analog uridine 5'-monophosphate. We find that the origin of CPDase activity is related to a loop structure that is conserved in yeast and forms a distinct penultimate (n – 1) nucleotide binding site. These data provide structural and mechanistic insight into the evolutionary divergence of Usb1 catalysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A transcriptome software comparison for the analyses of treatments expected to give subtle gene expression responses

Background: In this comparative study we evaluate the performance of four software tools: DNAstar-D (DESeq2), DNAstar-E (edgeR), CLC Genomics and Partek Flow for identification of differentially expressed genes (DEGs) using a transcriptome of E. coli. The RNA-seq data are from the effect of below-background radiation 5.5 nGy total dose (0.2nGy/hr) on E. coli grown shielded from natural radiation 655 m below ground in a pre-World War II steel vault. The gene expression response to three supplemented sources of radiation designed to mimic natural background, 1952 – 5720 nGy in total dose (71–208 nGy/hr), are compared to this “radiation-deprived” treatment. In addition, RNA-seq data of Caenorhabditis elegans nematode from similar radiation treatments was analyzed by three of the software packages. Results: In E. coli, the four software programs identified one of the supplementary sources of radiation (KCl) to evoke about 5 times more transcribed genes than the minus-radiation treatment (69–114 differentially expressed genes, DEGs), and so the rest of the analyses used this KCl vs “Minus” comparison. After imposing a 30-read minimum cutoff, one of the DNAStar options shared two of the three steps (mapping, normalization, and statistic) with Partek Flow (they both used median of ratios to normalize and the DESeq2 statistical package), and these two programs identified the highest number of DEGs in common with each other (53). In contrast, when the programs used different approaches in each of the three steps, between 31 and 40 DEGs were found in common. Regarding the extent of expression differences, three of the four programs gave high fold-change results (15–178 fold), but one (DNAstar’s DESeq2) resulted in more conservative fold-changes (1.5–3.5). In a parallel study comparing three qPCR commercial validation software programs, these programs also gave variable results as to which genes were significantly regulated. Similarly, the C. elegans analysis showed exaggerated fold-changes in CLC and DNAstar’s edgeR while DNAstar-D was more conservative. Conclusions: Regarding the extent of expression (fold-change), and considering the subtlety of the very low level radiation treatments, in E. coli three of the four programs gave what we consider exaggerated fold-change results (15 – 178 fold), but one (DNAstar’s DESeq2) gave more realistic fold-changes (1.5–3.5). When RT-qPCR validation comparisons to transcriptome results were carried out, they supported the more conservative DNAstar-D’s expression results. When another model organism’s (nematode) response to these radiation differences was similarly analyzed, DNAstar-D also resulted in the most conservative expression patterns. Therefore, we would propose DESeq2 (“DNAstar-D”) as an appropriate software tool for differential gene expression studies for treatments expected to give subtle transcriptome responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Phase 1 NuScale SMR FOAK Nuclear Demonstration Readiness Project (Final Scientific/Technical Report)

The overarching objective of the Phase 1 NuScale SMR First-of-a-Kind (FOAK) Nuclear Demonstration Readiness Project was to enhance competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale small modular reactor (SMR). The scope of this Phase 1 project continued to advance the licensing and design maturity, particularly in those areas related to supporting customer readiness, supply chain integration, cost competitiveness, and cost confidence. This investment provided by the Government has accelerated development of these designs and technologies so that the existing domestic fleet of nuclear power plants remains viable and the most mature in the nuclear industry. The intent is to have the new, advanced U.S. designs be deployed as early 2026, and be globally competitive. As a part of the First-of-a-Kind Nuclear Demonstration Readiness Project, NuScale has been developing an advanced reactor design, leading the path for other development projects or complex technology advancements for existing plants that have significant technical and licensing risk. The NuScale Power team (NuScale) is advancing licensing, engineering, supply chain development, testing, and other required activities to enhance the innovation and competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale SMR. Specifically, NuScale is performing the following activities in Phase 1. Fully supporting the NRC review of the NuScale DCA to ensure approval of a final safety evaluation report by the end of 2020. Improving plant cost confidence and cost competitiveness through design and supply chain advancement, incorporation of constructability best practices, and margin recovery to increase plant power output. Accelerating design maturity, technology development, and operational program readiness to support a customer commitment for plant deployment. The Department of Energy (DOE) Office of Scientific and Technical Information (OSTI), a unit of the Office of Science, fulfills agency-wide responsibilities to collect, preserve, and disseminate both unclassified and classified scientific and technical information (STI) emanating from DOE-funded research and development (R&D) activities at DOE national laboratories and facilities and at universities and other institutions nationwide. This scientific and technical report provides summaries of the analyses and research that was performed by NuScale under this project that achieves the objective of disseminating information to the nuclear industry to ensure the innovations realized are shared for the benefit of the industry at large.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Selective Amnesia using Contrastive Subnet Erasure for Class Level Unlearning in Vision Models

We study concept-level forgetting in pretrained vision models: removing an entire semantic category so the system no longer recognizes that object in unseen images and contexts, rather than merely forgetting specific training examples. Prior work either applies blunt global projections or fine-tunes parameters, which can introduce collateral damage to unrelated features, add compute, and become unstable as forgetting strength increases. We introduce Contrastive Subnet Erasure (CSE), a training-free, encoder-centric edit that targets a compact set of channels most responsible for the class and attenuates them in a calibrated manner. The modification is algebraically folded into the subsequent layer, yielding no inference-time overhead and leaving task heads unchanged. To evaluate whether forgetting generalizes beyond the data used to specify the class, we introduce a cross dataset protocol in which the class is defined on a source dataset and performance is measured on a disjoint target dataset drawn from a different distribution with no shared images. This setup tests whether the model still fails to recognize the object when it looks different or appears in new scenes, and it helps avoid overfitting to patterns in the source dataset. Across CIFAR 10, CIFAR 100, and ImageNet under this protocol, CSE achieves stronger forgetting of the target class while better preserving non target utility than existing baselines in both single class and multi class settings. Overall, CSE provides a simple, stable, and deployment-ready mechanism for class-level unlearning in vision.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
DOE OSTI2023

Lepton–Nucleus Interactions within Microscopic Approaches

This review paper emphasizes the significance of microscopic calculations with quantified theoretical error estimates in studying lepton–nucleus interactions and their implications for electron scattering and accelerator neutrino oscillation measurements. We investigate two approaches: Green’s Function Monte Carlo and the extended factorization scheme, utilizing realistic nuclear target spectral functions. In our study, we include relativistic effects in Green’s Function Monte Carlo and validate the inclusive electron scattering cross section on carbon using available data. We compare the flux-folded cross sections for neutrino-carbon scattering with T2K and MINER$v$ A experiments, noting the substantial impact of relativistic effects in reducing the theoretical curve strength when compared to MINER$v$ A data. Additionally, we demonstrate that quantum Monte Carlo-based spectral functions accurately reproduce the quasi-elastic region in electron scattering data and T2K flux-folded cross sections. By comparing results from Green’s Function Monte Carlo and the spectral function approach, which share a similar initial target state description, we quantify errors associated with approximations in the factorization scheme and the relativistic treatment of kinematics in Green’s Function Monte Carlo.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Dual Context: Leveraging Structured Application Context for Code Generation and Runtime Feature Activation via Chat Interfaces

Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.

Tadimeti, Vijay [ORNL]↗
DOE OSTI2026

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗
DOE OSTI2026

Substrate-Mediated Evaporation and Stochastic Evolution of Supported Au Nanoparticles

Here, we use in situ transmission electron microscopy with automated tracking to study supported gold nanoparticles (NPs) during high-temperature vacuum annealing. The average mass loss per NP is governed by a flat, nearly size-independent substrate-mediated evaporation profile. On top of this mean shrinkage, individual NPs show significant fluctuations in apparent growth or shrinkage, and NP volume follows a random-walk-like trajectory. To rationalize both the ensemble-mean behavior and the particle-resolved variability, we develop a self-consistent theory that couples substrate-mediated evaporation to collective 2D Ostwald-type mass exchange through a shared adatom field, described in terms of a renormalized screening length and background concentration. In the experimentally relevant regime, the theory predicts an approximately size-independent mean shrinkage rate and clarifies how net mass loss suppresses classical coarsening. Superimposed on this deterministic drift, we quantify stochastic volume trajectories and capture their fluctuation spectrum with a minimal Langevin description consistent with intermittent adatom attachment and detachment events. In addition, we characterize the lateral diffusive motion of NPs, which is responsible for their coalescence. Altogether, our results highlight that stochasticity is intrinsic at the nanoscale and that predicting the evolution of supported NPs at early and intermediate times requires a unified framework combining substrate-mediated evaporation, collective mass exchange, and stochastic fluctuations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Modified Andronov-Hopf Oscillator-Based Grid-Forming Converter with Emulated Virtual Cable for Enhanced Power Sharing Performance

Nonlinear oscillator-based grid-forming converters offer superior dynamic and steady-state performance, making them an attractive solution for interconnecting renewable resources. This paper proposes a novel modified Andronov-Hopf oscillator to enhance the operating spectrum and facilitate the integration of renewable energy sources. An inner loop controller based on the Lyapunov energy function is implemented to achieve robust stability and performance, while a virtual cable emulation strategy enables seamless parallel operation. Comprehensive modeling and simulation studies validate the effectiveness of the proposed system, demonstrating its capabilities in addressing diverse operating scenarios, including grid faults, renewable energy fluctuations, and parallel operation. The proposed solution exhibits fast transient response, robust stability, and flexible operation, making it a valuable contribution to the field of renewable energy integration. The results of this study can be used to inform the design and implementation of next-generation grid-forming converters, enabling a more sustainable and reliable energy future. Additionally, the proposed system's ability to operate in both grid-connected and islanded modes makes it an ideal candidate for remote and off-grid renewable energy applications. The proposed solution's scalability and modularity also make it suitable for large-scale renewable energy integration. The proposed system is verified through MATLAB/Simulink and PLECS simulations, demonstrating its effectiveness in ensuring robust and efficient operation.

Andronov-Hopf Oscillator (AHO)↗
DOE OSTI2022

Remining and Restoring Abandoned US Mining Sites: The Case for Materials Needed for Zero-Carbon Transition

The electricity generation sector is responsible for 25% of the world’s greenhouse gas (GHG) emissions and thus has been the focus of efforts to transition to clean energy and sustainable development in many nations. In the past 20 years, renewable energy sources have been the fastest-growing energy source in the world, comprising almost 29% of the world’s electricity generation in 2020. Renewable energy sources are expected to comprise nearly 95% of the world’s power capacity growth through 2026, with a share of planned capacity expansion of up to 46% in 2026. The rapid development of renewable energy sources and technologies will require an enormous amount of raw materials to replace coal and gas plants and increase in the capacity to handle growing electricity demand because renewable energy sources have a low-power density and intermittent behavior. Accounting for the expected scale of rapidly deploying renewable energy sources that require rare earth elements (REEs), cement, and steel, the mining industry may face a supply problem for the materials critical for clean energy. And, as the exploration and development of new mining sites can be expensive and risky, the mining industry may require economic stimuli to grow supply. The increasing demand for renewable energy resources makes mining a threat to the environment unless proper regulations are established and calls for remining, cleanup, and circular economic development are made. Mining also contributes to environmental injustices related to the exploitation and pollution of lands near communities that are dependent on biodiversity in the area, while not always benefiting from technological advancements provided by the use of renewable energy and technologies. This study explored the opportunity of remining abandoned mining waste to extract metals and minerals essential for the production of renewable energy sources. The authors analyzed materials used in the production of these technologies, materials readily available in the United States, and which materials can be extracted locally in the United States from abandoned mine waste. The authors also studied environmental injustices that populations near mining sites experience and ways to mitigate these injustices, such as providing more control over extraction and cleanup activities, providing more job opportunities in those areas, and offsetting costs associated with cleanup and land restoration projects.

42 ENGINEERING↗