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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 55 records · Page 3

Cyclotron Road Partnership (CRADA Final Report)

The Cyclotron Road program was launched in 2015 by LBNL, with support from the DOE Advanced Manufacturing Office (AMO), to accelerate technical innovation in the energy sector. The program brought scientist-entrepreneurs to LBNL to access unique research assets and expertise. In 2016, LBNL partnered with Activate Global, Inc., a 501(c)(3) non-profit, to expand the program and provide enhanced access to capital and business support services. Under this Cooperative Research and Development Agreement (CRADA), LBNL provided technical support and expertise, while Activate engaged with private sector, philanthropic, and government partners to support innovators and research-phase small businesses, aiming to translate high-impact materials and manufacturing technologies from lab to market. The program received funding from various sponsors, including the DOE, DARPA, and the California Energy Commission, and was managed through a collaborative framework that maintained accountability by the participant organization and Berkeley Lab regarding roles and tasks relevant to this collaboration.

99 GENERAL AND MISCELLANEOUS↗

Frontiers in Thermal Transport and Energy Conversion: Proceedings of a Workshop

Thermal transport and energy conversion has remained an active field for at least 200 years, with numerous opportunities for discoveries and new applications. Recently, experiments have advanced researchers’ understanding of basic physics, and how new discoveries might translate into applications in energy, materials, quantum technologies, and other areas. The National Academies convened a workshop on April 11, 2019 to identify and assess the frontier of current research in the field of thermal transport and energy conversion. Discussions involved topics related to thermal transport and quasi-particle hydrodynamics, thermal transport beyond the quasiparticle paradigm, the thermal hall effect from neutral spin excitations in frustrated quantum magnets, quantization of the thermal hall conductivity at small hall angles, and thermal spin transport, including spin-Seebeck and magnon drag effects. These topics were strategically selected with the goal of uncovering key challenges, opportunities, and issues in order to guide future efforts and investments to advance the field. This publication offers a condensed summary of the discussions and presentations from the workshop, which was unclassified and open to the public.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A First Investigation of Agriculture Sector Perspectives on the Opportunities and Barriers for Agrivoltaics

Agrivoltaic systems are a strategic and innovative approach to combine solar photovoltaic (PV)-based renewable energy generation with agricultural production. Recognizing the fundamental importance of farmer adoption in the successful diffusion of the agrivoltaic innovation, this study investigates agriculture sector experts’ perceptions on the opportunities and barriers to dual land-use systems. Using in-depth, semistructured interviews, this study conducts a first study to identify challenges to farmer adoption of agrivoltaics and address them by responding to societal concerns. Results indicate that participants see potential benefits for themselves in combined solar and agriculture technology. The identified barriers to adoption of agrivoltaics, however, include: (i) desired certainty of long-term land productivity, (ii) market potential, (iii) just compensation and (iv) a need for predesigned system flexibility to accommodate different scales, types of operations, and changing farming practices. The identified concerns in this study can be used to refine the technology to increase adoption among farmers and to translate the potential of agrivoltaics to address the competition for land between solar PV and agriculture into changes in solar siting, farming practice, and land-use decision-making.

14 SOLAR ENERGY↗

‘Best’ Coal-Fired Power Plant and Cogeneration Case Studies

This National Energy Technology Laboratory (NETL) work was prepared for the Asia-Pacific Economic Cooperation (APEC) Energy Working Group. As many economies are planning for a lower carbon future, the use of inefficient coal-fired power generation remains significant in many parts of the world. In 2018, 45% of power generation in APEC economies came from coal. The transition to a lower carbon future can be aided by employing the most advanced available technologies in existing and future coal-fired power plants. Higher efficiency translates to lower emissions per unit of power produced and also means less carbon to capture once CO 2 capture technologies are fully commercial and widely deployed. In addition to reducing carbon emissions, the most advanced coal plants also have extremely low emissions of other pollutants like sulfur dioxide, nitrogen oxides, mercury and particulate matter. Some of these advanced plants also address regional water constraints by minimizing the use of fresh water.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Modulating Oxide‐Based Quantum Materials by Ion Implantation

Ion implantation has emerged as a powerful tool for manipulating and investigating oxide quantum materials, where strong electron correlations give rise to exotic phases and functionalities. This Review examines how controlled ion bombardment enables targeted modulation of structural, electronic, and magnetic properties in complex oxides. Recent advances in ion beam techniques is analyzed that provide unprecedented control over defect profiles, from point defects to extended damage cascades. In application, ion irradiation has demonstrated the ability to tune quantum phenomena including metal‐insulator transitions, magnetism, and superconductivity through selective doping, defect creation, and lattice strain. The ability to write quantum states with nanoscale precision using focused ion beams is opening new paths for quantum device fabrication. Challenges in understanding radiation damage mechanisms in strongly correlated systems is discussed, and identify opportunities for designing quantum functionality through defect‐engineering approaches. The technique's demonstrated capability to write quantum states with nanoscale precision, combined with its compatibility with existing semiconductor processing infrastructure, suggests a clear pathway for translating fundamental discoveries in quantum materials into practical technological applications.

defect engineering↗

An autoinhibited state of 53BP1 revealed by small molecule antagonists and protein engineering

The recruitment of 53BP1 to chromatin, mediated by its recognition of histone H4 dimethylated at lysine 20 (H4K20me2), is important for DNA double-strand break repair. Using a series of small molecule antagonists, we demonstrate a conformational equilibrium between an open and a pre-existing lowly populated closed state of 53BP1 in which the H4K20me2 binding surface is buried at the interface between two interacting 53BP1 molecules. In cells, these antagonists inhibit the chromatin recruitment of wild type 53BP1, but do not affect 53BP1 variants unable to access the closed conformation despite preservation of the H4K20me2 binding site. Thus, this inhibition operates by shifting the conformational equilibrium toward the closed state. Our work therefore identifies an auto-associated form of 53BP1—autoinhibited for chromatin binding—that can be stabilized by small molecule ligands encapsulated between two 53BP1 protomers. Such ligands are valuable research tools to study the function of 53BP1 and have the potential to facilitate the development of new drugs for cancer therapy.

59 BASIC BIOLOGICAL SCIENCES↗

CRISPR-RNAa: targeted activation of translation using dCas13 fusions to translation initiation factors

Abstract Tools for synthetically controlling gene expression are a cornerstone of genetic engineering. CRISPRi and CRISPRa technologies have been applied extensively for programmable modulation of gene transcription, but there are few such tools for targeted modulation of protein translation rates. Here, we employ CRISPR-Cas13 as a programmable activator of translation. We develop a novel variant of the catalytically-deactivated Cas13d enzyme dCasRx by fusing it to translation initiation factor IF3. We demonstrate dCasRx-IF3’s ability to enhance expression 21.3-fold above dCasRx when both are targeted to the start of the 5′ untranslated region of mRNA encoding red fluorescent protein in Escherichia coli. Activation of translation is location-dependent, and we show dCasRx-IF3 represses translation when targeted to the ribosomal binding site, rather than enhancing it. We provide evidence that dCasRx-IF3 targeting enhances mRNA stability relative to dCasRx, providing mechanistic insights into how this new tool functions to enhance gene expression. We also demonstrate targeted upregulation of native LacZ 2.6-fold, showing dCasRx-IF3’s ability to enhance expression of endogenous genes. dCasRx-IF3 requires no additional host modification to influence gene expression. This work outlines a novel approach, CRISPR-RNAa, for post-transcriptional control of translation to activate gene expression.

59 BASIC BIOLOGICAL SCIENCES↗

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Co-design Center for Exascale Machine Learning Technologies (ExaLearn)

We report rapid growth in data, computational methods, and computing power is driving a remarkable revolution in what variously is termed machine learning (ML), statistical learning, computational learning, and artificial intelligence. In addition to highly visible successes in machine-based natural language translation, playing the game Go, and self-driving cars, these new technologies also have profound implications for computational and experimental science and engineering, as well as for the exascale computing systems that the Department of Energy (DOE) is developing to support those disciplines. Not only do these learning technologies open up exciting opportunities for scientific discovery on exascale systems, they also appear poised to have important implications for the design and use of exascale computers themselves, including high-performance computing (HPC) for ML and ML for HPC. The overarching goal of the ExaLearn co-design project is to provide exascale ML software for use by Exascale Computing Project (ECP) applications, other ECP co-design centers, and DOE experimental facilities and leadership class computing facilities.

97 MATHEMATICS AND COMPUTING↗

Dual incorporation of non-canonical amino acids enables production of post-translationally modified selenoproteins

Post-translational modifications (PTMs) can occur on almost all amino acids in eukaryotes as a key mechanism for regulating protein function. The ability to study the role of these modifications in various biological processes requires techniques to modify proteins site-specifically. One strategy for this is genetic code expansion (GCE) in bacteria. The low frequency of post-translational modifications in bacteria makes it a preferred host to study whether the presence of a post-translational modification influences a protein’s function. Genetic code expansion employs orthogonal translation systems engineered to incorporate a modified amino acid at a designated protein position. Selenoproteins, proteins containing selenocysteine, are also known to be post-translationally modified. Selenoproteins have essential roles in oxidative stress, immune response, cell maintenance, and skeletal muscle regeneration. Their complicated biosynthesis mechanism has been a hurdle in our understanding of selenoprotein functions. As technologies for selenocysteine insertion have recently improved, we wanted to create a genetic system that would allow the study of post-translational modifications in selenoproteins. By combining genetic code expansion techniques and selenocysteine insertion technologies, we were able to recode stop codons for insertion of N ε -acetyl- l -lysine and selenocysteine, respectively, into multiple proteins. The specificity of these amino acids for their assigned position and the simplicity of reverting the modified amino acid via mutagenesis of the codon sequence demonstrates the capacity of this method to study selenoproteins and the role of their post-translational modifications. Moreover, the evidence that Sec insertion technology can be combined with genetic code expansion tools further expands the chemical biology applications.

59 BASIC BIOLOGICAL SCIENCES↗

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

Protecting honey bees through microbiome engineering

Honey bees are indispensable insects. Their pollination services support modern agriculture and natural ecosystems. Managed honey bee colonies face increasing threats to their survival, ranging from environmental stressors that include agrochemicals to infestations of arthropod pests and infections with microbial pathogens. Like humans, honey bees have a native gut microbiome that supports their health. However, the bee gut microbiome has a simpler composition than the gut microbiome of mammals, and its main constituent bacterial species can be easily cultured outside of the host. Furthermore, this experimental tractability and the need for new methods for protecting hive health have made honey bees a testbed for synthetic microbiomes augmented with probiotic bacteria and engineered DNA. Here, we discuss the natural benefits of bee gut bacteria, recent progress in genetically modifying these bacteria, and how symbiont-mediated RNA interference and other microbiome engineering approaches can boost bee immunity and suppress bee pathogens and parasites. Finally, we discuss how emerging methods for microbiome engineering and biocontainment could be applied to honey bees and used to address challenges in translating these proof-of-principle achievements into safe and effective technologies for field applications at scale.

Biological and medical sciences↗

Remote Sensing and Fluxes Upscaling for Real-world Impact (Workshop Report)

The "Remote Sensing and Fluxes Upscaling for Real-world Impact" workshop, held on July 9-10, 2024, at Lawrence Berkeley National Lab, was a collaborative effort led by the AmeriFlux Management Project, NEON, and the Carbon Dew Community of Practice. The event brought together over 200 registrants and approximately 100 attendees each day, including leading experts, researchers, and practitioners. The primary focus was on bridging the gap between cutting-edge research and practical applications in environmental monitoring by integrating remote sensing and flux data. Key themes included the importance of site-level measurements for validating remote sensing products, providing nature-based climate solutions, and addressing challenges such as instrument costs and the need for standardized methods. At the regional scale, discussions centered on addressing spatial heterogeneity and using high-resolution remote sensing and machine learning methods to enhance data interpretation. Global scale challenges included data consistency, gap filling, and accurate emission source identification, with opportunities for international collaboration and standardized practices to improve global carbon budget assessments. The workshop emphasized the critical need for integrating data across local, regional, and global scales through explicit scale-matching and developed a workflow for scaling flux data using "straight shot" and "explicit nesting" approaches. The event highlighted the importance of connecting scientific research with real-world applications in carbon, energy, and water management, ensuring that advancements translate into tangible societal benefits. These insights will guide future research, technology transfer, and collaboration, maximizing the potential of environmental fluxes to address real-world challenges.

97 MATHEMATICS AND COMPUTING↗

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains. In scientific domains, real-time near-sensor processing can drastically improve experimental design and accelerate scientific discoveries. To support domain scientists, we have developed hls4ml, an open-source software-hardware codesign workflow to interpret and translate machine learning algorithms for implementation with both FPGA and ASIC technologies. We expand on previous hls4ml work by extending capabilities and techniques towards low-power implementations and increased usability: new Python APIs, quantization-aware pruning, end-to-end FPGA workflows, long pipeline kernels for low power, and new device backends include an ASIC workflow. Taken together, these and continued efforts in hls4ml will arm a new generation of domain scientists with accessible, efficient, and powerful tools for machine-learning-accelerated discovery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Always look on the bright side of life: Taking a different perspective on cybersecurity performance

This presentation will introduce participants to key mental models on how to think about and understand safety from two of the leading voices in the discipline – Dr. Erik Hollnagel and Dr. Todd Conklin – and from there we ask the simple question of “how can we apply this to cybersecurity?” At the completion of this presentation attendees will be able to describe Dr. Hollnagel’s Safety-II approach and Dr. Conkiln’s definition of safety as “not the absence of accidents but the presence of effective defenses.” They will be able to explain how these ideas translate to the cybersecurity world broadly, and more specifically to operational technology cybersecurity where physical safety consequences are coupled to control system performance. Finally, participants will be able to identify how selected principles from Weick and Sutcliffe’s high reliability organization theory can help operationalize these key mental models around safety, for improved organizational cybersecurity over the long run.

99 GENERAL AND MISCELLANEOUS↗

Energy Technology Innovation Partnership Project (Bilingual)

The U.S. Department of Energy's (DOE) Energy Technology Innovation Partnership Project (ETIPP) helps coastal, remote, and island communities increase the affordability, reliability, and security of their energy systems through energy planning and deep-dive technical assistance. This is a English and Spanish translation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Scale effects on core design, fuel costs, and spent fuel volume of pressurized water reactors

The desire to improve the economic competitiveness and deployment pace of nuclear energy through modularization, manufacturing, and series production had led to the development of smaller size reactors. As the standard 17x17 fuel technology is mainly maintained in the pressurized water reactors (PWRs) category, this translates into a lower number of fuel assemblies in the core and sometimes a reduced fuel height. To assess the impact of such scale change in core design on fuel cycle cost and spent fuel volume, a scoping analysis tool is developed based on infinite lattice calculations, leakage, fuel management reduced models, and levelized unit cost of electricity (LCOE) estimate. As such, cost dynamics driven by fuel specific power, burnup, core leakage, feed, cycle length, fuel assembly height as well as uranium market data are captured with consistent set of assumptions and analysis methods. A selection of 5 reactor designs representative of leading PWR developers is assessed and compared. Pursuing higher specific powers and optimal burnups are highlighted as the main fuel cost reduction drivers, nevertheless, practical limitations and opportunities must be evaluated to establish the feasibility of such enhanced fuel operation. In consequence, a detailed core design is performed using SIMULATE3 code for 5 PWR variations including natural and forced coolant circulation modes, two reactor scales, power densities of 73, 112, and 123 kW/l and higher discharge burnups. Design and optimization are performed at the lattice level, for the reflector, and at the core loading level. Satisfactory steady-state operation including power distribution, coolant operating limits, and reactivity requirements are analyzed and reported in this paper. The fuel economics of the detailed core designs confirm the scoping analysis findings. Despite the unlocked power uprates in small PWRs, the achievable burnup for a given fuel specific power requires more enrichment and shorter fuel height results in higher fabrication costs per mass of fuel, which makes scaling down core size a more expensive endeavor on the fuel cycle front. Spent fuel volumes are reported for the PWRs designed in this paper. Furthermore, these volumes are driven by the core average discharge burnup regardless of the scale in consideration. Additional cost and core performance aspects related to heavy reflector gains, fuel-reflector substitution, and disposal cost policy in the U.S. are examined.

42 ENGINEERING↗

Trait drift in microalgae and applications for strain improvement

Microalgae are increasingly used to generate a wide range of commercial products, and there is growing evidence that microalgae-based products can be produced sustainably. However, industrial production of microalgal biomass is not as developed as other biomanufacturing platform technologies. In addition, results of bench-scale research often fail to translate to large-scale or mass production systems. This disconnect may result from trait drift and evolution occurring, through time, in response to unique drivers in each environment, such as cultivation regimes, weather, and pests. Moreover, outdoor and indoor cultivation of microalgae has the potential to impose negative selection pressures, which makes the maintenance of desired traits a challenge. In this context, this review sheds the light on our current understanding of trait drift and evolution in microalgae. Here, we delineate the basics of phenotype plasticity and evolution, with a focus on how microalgae respond under various conditions. In addition, we review techniques that exploit phenotypic plasticity and evolution for strain improvement in view of industrial commercial applications, highlighting associated advantages and shortcomings. Finally, we suggest future research directions and recommendations to overcome unwanted trait drift and evolution in microalgae cultivation.

59 BASIC BIOLOGICAL SCIENCES↗