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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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ALchemist is a modular Python toolkit that brings active learning and Bayesian optimization to experimental design in chemical and materials research. It is designed for scientists and engineers who want to efficiently explore or optimize high-dimensional variable spaces—without writing code—using an intuitive graphical interface.
In collaboration with the Universities Research Association, Inc. (URA), establishment of the Undergraduate Women in STEM Internship pilot program assists Fermi Research Alliance, LLC (FRA) with honoring its commitment to increasing gender, racial and ethnic workforce diversity. This focused initiative is intended to invite, support and yield a qualified pipeline of alumnae underrepresented in FRA’s science and technology management and technical staff positions. Interns in this program spend 10-12 weeks at Fermilab working under the direct leadership, guidance and supervision of scientists, engineers, computing professionals, technicians and staff across all directorates performing hands-on research. In addition, the intern cohort meets with mentors and advisors to grow their professional networks, to take part in engaging and inclusive intellectual discussions, to directly benefit from workplace resources, and to participate in professional development and social engagement opportunities. The design of each research project and the supervision, mentorship and evaluation is conducted by a scientific, engineering, computing professional at Fermilab.
In situ processing does not only allow scientific applications to face the explosion in data volume and velocity but also to address the time constraints of many simulation-analysis workflows by providing scientists with early insights about their applications at runtime. Multiple frameworks implement the concept of a data transport layer (DTL) to enable such in situ workflows. These tools are very versatile, directly or indirectly access the data generated on the same node, another node of the same compute cluster, or a completely distinct node, and allow data publishers and subscribers to run on the same computing resources or not. This versatility puts on researchers the onus of taking key decisions related to resource allocation and how to transport data to ensure the most efficient execution of their in situ workflows. However, domain scientists and workflow practitioners lack the appropriate tools to assess the respective performance of particular design and deployment options. In this paper we introduce a versatile simulated DTL designed to provide researchers with insights on the respective performance of different execution scenarios of in situ workflows. This open-source, standalone library builds on the SimGrid toolkit and can be linked to any SimGrid-based simulator. It facilitates the evaluation of the performance behavior, at scale, of different data transport configurations and the study of the effects of resource allocation strategies. We demonstrate the scalability, versatility, and accuracy of this simulated DTL by reproducing the execution of two synthetic benchmarks and of a real-world in situ workflow composed of an MPI application and a parallel data analysis. Results of simulations run on a single core show that the proposed library can simulate the interactions of tens of thousands of simulated processes deployed on two interconnected commodity clusters in a few seconds, and the execution by a thousand simulated processes of an in situ workflow in less than three minutes.
A new facility was designed around the thermal column beam port of the 1 MW Research Reactor at the University of Massachusetts Lowell. Thermal neutrons are collimated to a 1-inch diameter beam and incident on samples to induce the radiative neutron capture. New measurements of capture gamma rays are planned for Mn, Cu, Ni, Cr, and Gd samples in the next few years. The experiments will be carried out in close collaboration with the ENSDF (Evaluated Nuclear Structure Data File) evaluation group at Brookhaven National Laboratory. The gamma rays are measured using an array of high-resolution HPGe detectors. Some of the HPGe detectors use active Compton shields that were designed from scintillation detectors and improve significantly the signal-to-background in the measured gamma-ray spectra with HPGe. The experimental spectra will be validated by the GEANT4 simulations of the array and theoretical models of the emission of gamma rays from the compound nucleus. In conclusion, the new experimental results on the capture gamma ray intensities will be incorporated in future ENSDF evaluations.
This article provides an in-depth analysis of blockchain research in the energy sector, focusing on projects funded by the U.S. Department of Energy (DOE) and comparing them with industry-funded initiatives. A total of 110 funded activities within the U.S. power industry were successfully tracked and mapped into a newly developed categorization framework. This framework is designed to help research agencies to systematically understand their funded portfolio. Such characterization is expected to help them make effective investments, identify research gaps, measure impact, and advance technological progress to meet national goals. In line with this need, the proposed framework proposes a 2-D categorization matrix to systematically classify blockchain efforts within the energy sector.Under the proposed framework, the Energy System Domain serves as the primary classification dimension, categorizing use cases into 30 distinct applications. The second dimension, Blockchain Properties, captures the specific needs and functionalities provided by Blockchain technology. The aim was to capture blockchain’s applicability and functionality: where and why blockchain? Principles behind the selection of the viewpoint dimensions were carefully defined based on consensus obtained through the Blockchain for Optimized Security and Energy Management (BLOSEM) project. The mapped results show that activities within the Grid Automation, Coordination, and Control (31.8%), Marketplaces and Trading (25.5%), Foundational Blockchain Research (19.1%), and Supply Chain Management (17.3%) domains have been actively pursued to date. The three leading specific use case applications were identified as Transactive Energy Management for Marketplaces and Trading, Asset Management for Supply Chain Management, and Fundamental Blockchain for Foundational Blockchain Research. The Marketplaces and Trading and Retail Services Enablement domains stood out as being favored by industry by a factor greater than 2 (2.3 and 2.6, respectively), yet there seemed to be little to zero investment from DOE. Approximately 76% of the total projects prioritized Immutability, Identity Management, and Decentralization and/or Disintermediation compared to Asset Digitization and/or Tokenization, Automation, and Privacy and/or Anonymity. The greatest discrepancies between DOE and industry were in Asset Digitization and/or Tokenization and Automation. The industry efforts (36% in Asset Digitization/Tokenization and 22% in Automation) was 14 times and 2.4 times, respectively, more intensive than the DOE-sponsored efforts, indicating a significant discrepancy in industry versus government priorities. Overall, quantifying DOE-sponsored projects and industry activities through mapping provides clarity on portfolio investments and opportunities for future research.
Awareness of how buildings interact with the occupant experience—especially human performance—is becoming more prevalent, as seen by increasing interest and investment in healthy built environments. However, there is a need to synthesize the wide array of existing indoor environmental assessment and performance research in a way that can translate directly to building design and operation. Existing research in this area typically focuses on a single isolated metric and has not focused on making the results utilizable by building practitioners. The aim of this research is to investigate existing office performance literature through meta‐analyses and produce regression models for four indoor environmental quality (IEQ) metrics to support critical decision‐making for building operation and renovation. To reach this aim, a literature review was conducted to identify studies that measure the impact of changing ventilation rate, temperature, horizontal illuminance, and noise level in offices on occupant task performance. This repository of field and laboratory studies was analyzed to visualize the trends between the selected IEQ metrics and task performance. The temperature, ventilation rate, and horizontal illuminance regression models showed clear improvement potential when modifying indoor conditions toward the defined high‐performance range, while the regression model for noise level was inconclusive. The discussion notes the importance of designing holistically for all components of these IEQ categories to utilize the results, for example, good filtration on outdoor air for quantifying ventilation impact and uniform overhead lighting with low contrast for quantifying horizontal illuminance impact. The novelty of this work is in considering multiple facets of the indoor environment under a single, unified analysis schema and producing IEQ‐based performance gains that can directly inform cost‐benefit analyses of building design and renovation.
Higher-order foldamers represent a unique class of supramolecules at the forefront of molecular design. Herein we control quaternary folding using a novel approach that combines halogen bonding (XBing) and hydrogen bonding (HBing). We present the first anion-templated double helices induced by halogen bonds (XBs) and stabilized by “hydrogen bond enhanced halogen bonds” (HBeXBs). Our findings demonstrate that the number and orientation of hydrogen bond (HB) and XB donors significantly affect the quaternary structure and guest selectivity of two similar oligomers. Finally, this research offers new design elements to engineer foldamers and tailor their quaternary structure for specific guest binding.
Efforts to identify the most-economic methods to decarbonize several sectors of the U.S. economy are underway. Industrial processes such as crude-oil refining rely heavily on energy-dense and easily stored and transported fossil fuels for powering their operations. Refineries use large amounts of energy, primarily derived from fossil sources to separate crude-oil components, break down heavier hydrocarbons into lighter compounds, remove impurities, reform hydrocarbon molecules, and generate steam and electricity for pumps and compressors and other various auxiliary systems. Crude-oil refining operations such as distillation, cracking, desulfurization, reforming, utilities systems and some offsite facilities collectively account for most of the energy consumption. Other operations such as hydrocracking or hydrotreating also require hydrogen for developing hydrogenation reactions which involve substantial heating to keep the reactors at high-temperature and pressure levels. All heat and energy demands are typically provided by natural gas (NG), oil, or other fuels, which makes refinery industry one of the most-difficult sectors to decarbonize. Nuclear power is a viable and energy-dense source of clean electricity, heat, and hydrogen to provide the large, sustainable energy supply that the refining industry demands. The U.S. Department of Energy’s (DOE’s) Integrated Energy Systems (IES) program is working to perform research and development, design, economic siting, and risk analysis. This state-of-the-art work will enable the first on-site demonstrations and commercial deployments of advanced small modular nuclear reactors (SMNRs) integrated with industries such as chemical production, refining, iron and steel making, and more. IES seeks to demonstrate the ability of advanced nuclear reactors to meet the heat and power demands of these industries while reducing carbon emissions in a sustainable and cost-competitive way. The primary objective of this research effort is to analyze industrial-scale SMNR integration intended to decarbonize refining facilities. The foreseen outcome is the provision of reliable, cost-competitive, and sustainable clean energy, alongside a reduction of carbon emissions. Specifically, the focus of this work lies on meeting the reference facilities’ heat and electricity demands with nuclear power while also supplying clean hydrogen via integrated high-temperature steam electrolysis (HTSE). This report presents a comprehensive technical and economic assessment of the integration of advanced nuclear reactors into a reference refinery, leveraging financial incentives from the Inflation Reduction Act (IRA). The evaluation aims to explore the potential economic benefits and challenges associated with incorporating advanced nuclear reactors into refinery operations, particularly in terms of energy efficiency, economic implications and environmental impact. By examining both the technical feasibility and economic viability, this analysis seeks to identify existing gaps and propose solutions for successful nuclear integration implementation. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the refining sector. A refinery reference-plant was developed, using an open-source refinery model, Petroleum Refinery Lifecycle Inventory Model (PRELIM) and expert assessment, as a base case for comparison with various nuclear integration options. The capacity of 100 kbd/day (KBD) of heavy crude-oil feed was selected to represent a general coking-type refinery with deep conversion capabilities (incorporating heavy-oil upgrading with FCC, coking, and associated hydrotreating process units), using a heavy crude-oil feed, which represents about 70% of U.S. refineries configurations. A summary of all cases considered in this study is shown in Table 1.
PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.
Biomass presents a promising opportunity for converting waste into valuable energy, fuels, and chemicals through various thermochemical processes, including hydrothermal carbonization, hydrothermal liquefaction, pyrolysis, gasification, and combustion. However, these processes operate under extreme conditions, introducing significant safety hazards that necessitate meticulous management to prevent accidents. This review discusses potential hazards, risk mitigation strategies, and safety management practices, emphasizing the importance of integrated safety measures into the design and operation of these processes. It also highlights the critical need for robust safety engineering and environmental management strategies tailored to each thermo-chemical process. As these processes transition from laboratory to industrial scale, there is an imperative to develop a clear and concise pathway for emerging industries to achieve regulatory compliance, achieve safety certification, and enable effective stewardship of potential fugitive emissions. By addressing safety and environmental concerns, stakeholders can optimize economic benefits, rural development, and achieve sustained domestic energy generation benefits offered by biomass conversion technologies. Further research on plant design optimization, operational safety, environmental evaluation standardization, and innovative waste management solutions will support the safe and effective scaling of these technologies, ultimately contributing to sustainable management and resource recovery.
Hybrid metal halides, particularly main group halide perovskites, are a unique class of materials that offer exceptional optoelectronic properties along with a remarkable materials design space. Initial research on this class of materials was driven by the ability of the prototype hybrid 3D perovskite-structured compound methylammonium lead iodide to function as the active layer in thin film solar cells. It is now known that this class of materials comprise a large family with tunable band gaps, relatively high charge carrier mobilities in both single crystal and polycrystalline forms, and relatively low concentrations of (deleterious) electrically active states within the band gap. Beyond applications in solar cells, the potential of these materials has been extended to emitters in light emitting diodes, and active components of radiation detectors. Complementing new functionality, the design space for hybrid metal halides continues to increase with discovery of new structural motifs. In this project, the combination of organic and inorganic functionalities has been employed to open pathways to the design and synthesis new, functional hybrid metal halides. Beyond the simple perovskites, Ruddlesden-Popper and Dion-Jacobsen compounds, and other variants, such as the newly advanced “hollow” perovskites have been studied. The materials have provided routes to understanding the unique electronic properties of hybrid metal halides because of their natural quantum well structures as well as other means of controlling band gaps and band dispersions. Understanding these materials, including the design rules for their formation, their structures and compositions in bulk and in thin films form, and the role of local (non-crystallographic) structure has an important aspect of this endeavor. The goal of advancing new materials and new fundamental understanding within this deceptively simple, yet fascinating class of compounds, so richly endowed with interesting and useful functionality, has been fulfilled.
Solar energy harnessed through concentrating solar power (CSP) systems offers a promising path to sustainable energy production, with the efficiency and longevity of these systems relying on key components like solar receivers. This study analyzes the thermomechanical behavior of an innovative enclosed light-trapping solar receiver optimized for particle heating applications. The receiver utilizes sheet metal alloys to form enclosed cavities that reflect and trap incoming solar flux, as well as enclosed channels that contain fluidized particle beds absorbing solar heat. Finite element analysis (FEA) is applied to predict the receiver's thermomechanical performance under extreme solar flux conditions. Temperature distributions from a thermal model simulating a multi-panel assembly at steady state are input into the FEA thermomechanical model for stress analysis. A key aspect of the analysis focuses on evaluating creep-fatigue damage, with a design target of achieving a 30- year service life. Various stress relief techniques are also proposed to extend the receiver's service life. The results highlight the significant impact of the particle-to-wall heat transfer coefficients (HTCs), ranging from 800 W/m2*K to 1400 W/m2*K. The 800 W/m2*K case shows a maximum von Mises stress of 164 MPa, while the 1400 W/m2*K case reduces it to 150 MPa. The creep life increases from 4,000 hrs in the 800 W/m2*K case to over 100,000 hrs in the 1400 W/m2*K case with Inconel 740H used, indicating that higher HTCs reduce stress and extend lifespan. This research advances the design of high-efficiency, low-stress solar receivers for particle-based thermal energy storage in CSP and industrial heating applications.
Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.
Well characterized experimental data for consequence model validation is important in progressing the use of liquid hydrogen as an energy carrier. In 2019, the Health and Safety Executive (HSE) undertook a series of liquid hydrogen dispersion and combustion experiments as a part of the Pre-normative Research into the Safe Use of Liquid Hydrogen (PRESLHY) project. In partnership between the National Renewable Energy Laboratory (NREL) and HSE, time and spatially varying hydrogen concentration measurements were made in 25 dispersion experiments and 23 congested ignition experiments associated with PRESLHY WP3 and WP5, respectively. These measurements were undertaken using the hydrogen wide area monitoring system developed by NREL. During the 23 congested ignition experiments, high variability was observed in the measured explosion severity during experiments with similar initial conditions. This led to the conclusion that wind, including localized gusts, had a large influence on the dispersion of the hydrogen, and therefore the quantity of hydrogen that was present in the congested region of the explosions. Using the hydrogen concentration measurements taken immediately prior to ignition, the hydrogen clouds were visualized in an attempt to rationalize the variability in overpressure between the tests. Gaussian process regression was applied to quantify the variability of the measured hydrogen concentrations. This analysis could also be used to guide modifications in experimental designs for future research on hydrogen combustion behavior.
Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.
Electrochemical interfaces are critical to the performance and durability of lithium-ion batteries (LIBs). The solid electrode-electrolyte interphase (SEI and CEI) structures that form during cycling can passivate reactive surfaces, ensuring safe operation, but also may contribute to performance degradation. Understanding the microscopic factors influencing interphase formation, growth, and evolution is essential for balanced battery design. While significant research has focused on the anode-electrolyte interphase (SEI), the cathode-electrolyte interphase (CEI) remains less explored, despite its importance in high-voltage and advanced battery technologies. Challenges in conducting in-situ or operando experiments arise from the occluded nature of these interfaces and the long timescales involved, often leading to biased interpretations. A validated multi-scale, multi-physics modeling approach, integrated with advanced characterization techniques, can effectively elucidate the intrinsic stability of electrolyte and cathode surfaces, the impact of chemical heterogeneity, and the role of microstructural features on CEI performance. In conclusion, this article reviews current modeling and simulation strategies for studying CEI in advanced LIBs and highlights opportunities for future methodological advancements and experimental integration.
The industry-standard approach for designing and operating research reactors cores relies on well-established methodologies that consider uncoupled neutronic calculations and a subchannel analysis of the Thermal-Hydraulic (TH) associated problem. Advancements in computing power and codes allow detailed Multiphysics approaches to be implemented, thereby reducing conservatism. In this study, a comparative analysis of results from diverse detailed neutronic-TH coupled core approaches is developed. To address a realistic application case, the comparison is made for a reported critical configuration from the Open Pool Australian Lightwater research reactor (OPAL) at Hot Full Power (HFP) and low burnup. Both cell-core and stochastic methodologies for neutronics are evaluated, whereas two different subchannel codes are considered for TH. In conclusion, the convergence of the coupled schemes, and the consistency of the main parameters are discussed, showing the compatibility of the alternative methods and their ability to offer critical insights not captured by standard practices.
Our research focuses on designing all-reflective phase retarders (RPRs) to generate and maintain circularly polarized (CP) light for NSF OPAL and other multipetawatt laser facilities. Assuming that the input polarization is either s- or p-polarized, RPRs need to be used in an out-of-plane configuration. Here, we will discuss the impact of transporting and focusing optics on CP light.