Search NASASearch

SEARCH · Search NASA

Results for “knowledge engineering”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

National Hydropower Fish Passage Database User's Guide and Methodology

Fish passage facilities are used to mitigate the impacts of hydropower dams on migratory fish in rivers, but information on the location, types, and characteristics of this infrastructure is incomplete at a national scale. Researchers at Oak Ridge National Laboratory partnered with federal agency and industry stakeholders to create the first national-scale database of fish passage infrastructure at U.S. hydropower developments. This database contains information of great value to a broad range of stakeholders; it includes fish passage facility engineering characteristics, targeted fish species, operational schedules, and costs. This data resource addresses a large gap in knowledge of the deployment of fish passage technology and is freely available to members of the hydropower community, including federal and state regulators and resource agencies, non-governmental organizations, industry, and other user groups to support project planning and regulatory (re)licensing activities. This database supports the U.S. Department of Energy Water Power Technologies Office objective to develop decision support tools and data resources that improve environmental performance and ensure hydropower’s long-term value to the American public.

13 HYDRO ENERGY

Transforming Energy Through Computational Excellence: NREL's Computational Science Center

Computational methods underpin advancing the science and engineering of energy efficiency, sustainable transportation, renewable power technologies, and developing a knowledge base to optimize energy systems. NREL's Computational Science Center (CSC) proudly focuses on providing the service of computing, advancing the science of computing, and enabling NREL's clean energy mission.

applied mathematics

Verazine biosynthesis from simple sugars in engineered Saccharomyces cerevisiae

Steroidal alkaloids are FDA-approved drugs (e.g., Zytiga) and promising drug candidates/leads (e.g., cyclopamine); yet many of the ≥697 known steroidal alkaloid natural products remain underutilized as drugs because it can be challenging to scale their biosynthesis in their producing organisms. Cyclopamine is a steroidal alkaloid produced by corn lily (Veratrum spp.) plants, and it is an inhibitor of the Hedgehog (Hh) signaling pathway. Therefore, cyclopamine is an important drug candidate/lead to treat human diseases that are associated with dysregulated Hh signaling, such as basal cell carcinoma and acute myeloid leukemia. Cyclopamine and its semi-synthetic derivatives have been studied in (pre)clinical trials as Hh inhibitor-based drugs. However, challenges in scaling the production of cyclopamine have slowed efforts to improve its efficacy and safety profile through (bio)synthetic derivatization, often limiting drug development to synthetic analogs of cyclopamine such as the FDA-approved drugs Odomzo, Daurismo, and Erivedge. If a platform for the scalable and sustainable production of cyclopamine were established, then its (bio)synthetic derivatization, clinical development, and, ultimately, widespread distribution could be accelerated. Ongoing efforts to achieve this goal include the biosynthesis of cyclopamine in Veratrum plant cell culture and the semi-/total chemical synthesis of cyclopamine. Herein, this work advances efforts towards a promising future approach: the biosynthesis of cyclopamine in engineered microorganisms. We completed the heterologous microbial production of verazine (biosynthetic precursor to cyclopamine) from simple sugars (i.e., glucose and galactose) in engineered Saccharomyces cerevisiae (S. cerevisiae) through the inducible upregulation of the native yeast mevalonate and lanosterol biosynthetic pathways, diversion of biosynthetic flux from ergosterol (i.e., native sterol in S. cerevisiae) to cholesterol (i.e., biosynthetic precursor to verazine), and expression of a refactored five-step verazine biosynthetic pathway. The engineered S. cerevisiae strain that produced verazine contains eight heterologous enzymes sourced from seven different species. Importantly, S. cerevisiae-produced verazine was indistinguishable via liquid chromatography-mass spectrometry from both a commercial standard (Veratrum spp. plant-produced) and Nicotiana benthamiana-produced verazine. To the best of our knowledge, this is the first report describing the heterologous production of a steroidal alkaloid in an engineered yeast. Verazine production was ultimately increased through design-build-test-learn cycles to a final titer of 83 ± 3 μg/L (4.1 ± 0.1 μg/g DCW). Finally, this research lays the groundwork for future microbial biosynthesis of cyclopamine, (bio)synthetic derivatives of cyclopamine, and other steroidal alkaloid natural products.

59 BASIC BIOLOGICAL SCIENCES

Advanced Transmission Technologies – GETs and HPCs Session 1: ATT Foundations and Dynamic Line Ratings (DLRs)

The INL TADA GETs Cohort Session 1, held on November 4, 2025, convened experts to address the integration of advanced transmission technologies, including Grid-Enhancing Technologies (GETs) and High Performance Conductors (HPCs), with a focus on digital assurance challenges. The session highlighted the growing importance of cybersecurity, supply chain transparency, reliability, and business risk management in deploying GETs, especially Dynamic Line Ratings (DLRs). Participants examined how expanded attack surfaces, limited vendor pools, and new regulatory requirements—such as FERC Orders 881, 2023, and 1920—are influencing utilities and technology providers. The workshop underscored the need for cyber-informed engineering, secure-by-design principles, and practical risk management strategies, while fostering collaboration and knowledge sharing among industry peers. Technical discussions covered the evolution from static to dynamic line ratings, complexities of cloud-based architectures, and NERC CIP compliance challenges. The session concluded with a collaborative risk exercise and a preview of future workshops on advanced power flow control and transmission topology optimization, reinforcing the cohort’s commitment to advancing digital assurance in the energy sector.

24 - POWER TRANSMISSION AND DISTRIBUTION

Characterizing Electrode Materials and Interfaces in Solid-State Batteries

Solid-state batteries (SSBs) could offer improved energy density and safety, but the evolution and degradation of electrode materials and interfaces within SSBs are distinct from conventional batteries with liquid electrolytes and represent a barrier to performance improvement. Over the past decade, a variety of imaging, scattering, and spectroscopic characterization methods has been developed or used for characterizing the unique aspects of materials in SSBs. These characterization efforts have yielded new understanding of the behavior of lithium metal anodes, alloy anodes, composite cathodes, and the interfaces of these various electrode materials with solid-state electrolytes (SSEs). This review provides a comprehensive overview of the characterization methods and strategies applied to SSBs, and it presents the mechanistic understanding of SSB materials and interfaces that has been derived from these methods. This knowledge has been critical for advancing SSB technology and will continue to guide the engineering of materials and interfaces toward practical performance.

25 ENERGY STORAGE

Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)

Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources.We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues.These findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION

Do Research Software Engineers and Software Engineering Researchers Speak the Same Language?

Anecdotal evidence suggests that research software engineers (RSEs) and software engineering researchers (SERs) often use different terminologies for similar concepts, creating communication challenges. To better understand these divergences, we have started investigating how software engineering fundamentals from the SER community are interpreted within the RSE community, identifying aligned concepts, knowledge gaps, and areas for potential adaptation. In conclusion, our preliminary findings reveal opportunities for mutual learning and collaboration, and our systematic methodology for terminology mapping provides a foundation for a crowdsourced extension and validation in the future.

Kehrer, Timo [Univ. of Bern (Switzerland)] (ORCID:

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J

MCNP® Code Version 6.3.2 Theory & User Manual (Rev. 1)

This document acts as a repository of knowledge for the Monte Carlo N-Particle (MCNP) transport computer code. It is maintained alongside the source code and attempts to introduce new users and re-familiarize experienced users with the theory and practices of using the MCNP code for the wide range of particle transport analyses that it is appropriate for. The latest version of the MCNP code, version 6.3.2, provides the Monte Carlo particle transport community with the latest feature developments and bug fixes in the MCNP code. The MCNP code version 6.0 and later is also known as the MCNP6 code.

42 ENGINEERING

Stable-Cycling Sustainable Na-Ion Batteries with Olivine Iron Phosphate Cathode in an Ether Electrolyte

Sustainable batteries using nontoxic, earth-abundant, and low-cost materials are key to decarbonization. Olivine NaFePO 4 fulfills these criteria, is attractive for Na-ion batteries, and can be derived from LiFePO 4 recycled from Li-ion battery wastes. Critical knowledge is needed for transforming LiFePO 4 to NaFePO 4 to enable such a sustainable, green engineering path toward high-performance Na-ion batteries. Herein, we report on the development of a stable-cycling, sustainable olivine iron phosphate-based Na-ion battery empowered by an improved understanding of materials transformation and electrolyte chemistry. First, we found that the conventional carbonate electrolyte with fluoroethylene carbonate additive causes an additional plateau (~2.4 V) at the end of the discharge process of the FePO 4 ||Na metal cell, leading to lower initial discharge capacity and voltage. This result shows that the voltage profile is influenced by not only intrinsic materials phase transformation during battery cycling but also the electrolyte additives and interphases formed. With the 1 M NaPF 6 diglyme electrolyte, we achieved an excellent capacity retention of 96% and 98% after 500 cycles at 1 and 5 C, respectively. Second, we chemically sodiated FePO 4 to form single-phase Na 0.9 FePO 4 . Na 0.9 FePO 4 ||hard carbon full cells demonstrated a remarkable capacity retention of ~84% at 3 and 5 C after 1000 cycles. The successful implementation of hard carbon, which can be derived from biomass waste, will further improve the sustainability of energy storage technologies. Our research demonstrates that electrolyte chemistry influences the voltage profile of phase-changing electrodes and provides effective electrolyte and full-cell design solutions for stable-cycling NaFePO 4 .

36 MATERIALS SCIENCE

GeoBridge: Unearthing Insights from Connecting Communities to Geothermal Information and Opportunities: Preprint

Knowledge is essential for overcoming obstacles in the development and adoption of geothermal technologies, and the geothermal community is home to numerous tools, events and organizations dedicated to sharing knowledge. However, many of these tools can be difficult to find, their resources undiscoverable by search engines, available only to members, or hidden away behind pay walls (Weers et al., 2024). The Department of Energy's (DOE) GeoBridge was developed by the National Renewable Energy Laboratory (NREL) to help bridge gaps in information and connect the geothermal community to the resources it needs. Launched in October 2024, GeoBridge aspires to expand the pool of geothermal stakeholders by providing in-roads to geothermal information, tools, and community resources. It helps to make these resources available to the broader geothermal community as well as those looking to join, such as entrepreneurs or innovators in adjacent industries looking to expand into geothermal energy. This paper explores a post-launch analysis of GeoBridge including data from analytics, feedback from GeoBridge users, the geothermal community, and the GeoBridge Advisory Group as well as an analysis of efficacy of various promotions for GeoBridge.

15 GEOTHERMAL ENERGY

Juvenile Salmon and Their Habitats in the Columbia River Estuary: A Review and Synthesis of Knowledge Development 2000–2025

[This is a 90% discussion draft.] This is the third Synthesis Memorandum funded by the U.S. Army Corps of Engineers and developed for the Columbia Estuary Ecosystem Restoration Program (CEERP) on the topic of habitat restoration in the Columbia River Estuary (CRE) from Bonneville Dam to the river mouth. While the first two were developed by PNNL and NOAA without the benefit of stakeholder participation, for the current memo, two key activities were initiated: (1) review, by the Expert Regional Technical Group (ERTG), of status and trends monitoring and action effectiveness monitoring funded by CEERP, and (2) a workshop including representatives of the Bonneville Power Administration and the U.S. Army Corps of Engineers (the action agencies [AAs]), the National Oceanic and Atmospheric Administration (NOAA), major research agencies contributing to CEERP, and sponsors who implement CEERP restoration actions. A systematic literature review was conducted using ClarivateTM Web of ScienceTM database. The topics of interest for CRE relevant research included salmon ecology, physical processes, and wetland habitats, and therefore required the use of broad search terms. Our final search criteria included a combination of Boolean operators and an approach to combine different sets of search terms. The final search result yielded 669 records. The records were classified by groups and assigned to the relevant disciplinary expert for review. The review identified substantive advances in understanding the provision of salmon habitat functions through spatiotemporally dynamic physical and ecological processes, and the use of CRE habitats by numerous stocks of juvenile salmon. It also uncovered heretofore unincorporated historical documentation of riparian habitats across the CRE. The characterization of the structural components of floodplain habitat including plant associations and channel networks has advanced considerably, together with the understanding of seasonal changes and long-term trends. The relative influence of salmon-habitat location in the CRE as compared with temporal factors, mainly season, has been well described, which affects the prioritization of restoration. Stressors on the ecosystem and fish, and the drivers of these stressors, have been more carefully elucidated and predictive models are in various stages of development. The vision, aims, and design of restoration projects have advanced together with methods of data collection, analysis, and modeling that have seen substantial improvements. Experiments intended to inform the design of restoration projects are underway or have been completed. An important outstanding area of research that has lagged behind the advances in fundamental understanding of the ecosystem and salmon habitat functions remains the peer-reviewed documentation of the outcomes of restoration for both habitats and fish functions.

estuary

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence

Rewiring Aromatic Compound Consumption: Chromosomal Amplification and Evolution of a Foreign Pathway in Acinetobacter baylyi ADP1

Rational engineering strategies that seek to harness the remarkable diversity of microbial metabolism can be limited by incomplete biological knowledge. As described here, a novel approach to address this challenge involved replacing a native pathway for degrading lignin-derived aromatic compounds via ortho cleavage of protocatechuate in Acinetobacter baylyi ADP1 with a foreign meta-cleavage pathway that uses different enzymes, metabolites, and redox carriers. This alteration may improve lignin valorization and coordinate catabolism with bioproduction strategies. When a 14-kbp region of foreign DNA was inserted in the chromosome, the heterologous genes failed to confer growth on target substrates. Regional gene dosage was increased using a synthetic DNA fragment to promote recombination, and higher copy number enabled growth. During adaptive laboratory evolution, compensatory mutations arose that permit growth with one copy of the foreign genes. This complex metabolic remodeling was accomplished without assumptions about the impediments that initially prevented growth. To understand the changes that emerged, a novel transformation assay identified a combination of mutations sufficient for the new phenotype. Three unexpected changes were revealed: loss of one foreign enzyme, loss of one native enzyme, and loss of a two-component transcriptional regulatory system. This study establishes that large multicopy tandem arrays of poorly adapted pathway genes can confer new functions and improve understanding of metabolism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Quantifying Membrane Structure and Dynamics during Bioproduct Production in Zymomonas mobilis by Molecular Simulation

The conversion of lignocellulosic biomass into biofuels and bioproducts by microbial biorefineries is central to a sustainable chemical industry. Zymomonas mobilis is one such biorefinery chassis and is resistant to ethanol stress, leading to its use in biomass conversion to biofuels and bioproducts. However, Z. mobilis growth is often inhibited by organic acids, aldehydes, alcohols, ketones, and amides found in biomass hydrolysate. The resulting slow growth inhibits production and as a result drives up the price for the resulting products. One hypothesis is that these molecules interact with or disrupt the bacterial membrane, triggering stress responses and hindering growth. To test this hypothesis at the molecular level, we employ all-atom molecular dynamics (MD) simulations to investigate lignocellulose-derived small molecules and their impact on a biologically relevant Z. mobilis membrane model. Simulations were conducted across a range of inhibitor concentrations from 0 to 2.5 mol %, analyzing key membrane properties such as area per lipid (APL), membrane thickness, lipid-order parameter (−S CH ), lateral diffusion coefficient (D xy ), and permeability coefficient (Pm). From simulation, we observed altered membrane structure and dynamics at these modest small molecule concentrations commonly found in hydrolysates. Generally, the membranes become thinner, with a higher area per lipid and lower-order parameter as the small molecule concentration increases. These trends are stronger for more hydrophobic molecules with greater hydrophobic bulk, as isobutanol, propanol, and propanoic acid showed greater membrane perturbations as the concentration increased compared to other small molecules. Tracking small molecule distributions directly in our equilibrium simulations allows us to determine concentration-dependent free energy profiles for these molecules. While the trends are noisy, generally the barriers to crossing the membrane decrease as the concentration increases, indicating that the membranes become leakier as small molecule concentrations rise. Comparing between native Z. mobilis membranes with hopanoids and membranes sharing the same phospholipid composition but without hopanoids, hopanoids stabilize and order the membrane for smaller molecules to maintain membrane structure but appear insufficient for larger hydrophobic molecules like isobutanol. These findings provide a mechanistic understanding of how small molecules found in biomass degradation streams interact with the Z. mobilis membrane, offering valuable insights for future strain engineering efforts to optimize biofuel and bioproduct synthesis from biomass feedstocks by highlighting limits to small molecule tolerance. This knowledge can guide the modification of membrane composition to develop more robust microbes, thereby improving microbial survival and yields in industrial contexts.

Singh, Nitin Kumar [Michigan State Univ., East Lan

FAIR to WISE (F2W) v1.0.0

FAIR to WISE (F2W) is an iterative, large-language model (LLM) driven pipeline that turns unstructured research PDFs into structured, queryable knowledge graphs (KGs). Core features include schema-driven extraction to a LinkML model; full provenance capture; ontology-grounded enrichment (e.g., chemical validation and ChEBI lookup); graph construction to JSON-LD with stable IDs; and KG-RAG question answering with evidence-aware retrieval. The system is engineered for reproducibility and accessibility (open-source Ollama models, temperature=0, NVTX/Nsight profiling) with robust QA (relation verification, deduplication, and deterministic outputs). Primary uses are literature-to-KG automation, knowledge-grounded Q&A, and experimental steering support. We demonstrate the approach in organic photovoltaics, where the pipeline ingests papers, builds a domain KG, and evaluates answers against expert competency questions to guide experimental planning and interpretation. Compared with off-the-shelf LLMs and ad-hoc NLP tools, F2W addresses ontology gaps and reduces hallucination risk by grounding responses in extracted evidence and enforcing schema constraints; it also offers deterministic, provenance-linked outputs and open, cost-aware deployment. Evidence-aware ranking further improves answer quality over pure vector search.

Abramov, David [Lawrence Berkeley National Laborat

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy