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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

JGI Plant Transformation Workshop, May 20-21, 2025

Domestic biomass crops such as sorghum, switchgrass, Miscanthus, and poplar can provide United States industries with renewable feedstocks while also supporting low-input farming systems and strengthening supply chains for biofuels, biochemicals and biomaterials. The U.S. leads globally in biomass crop genomics, yet progress in engineering traits is constrained by slow, genotype-dependent transformation methods and lengthy Design-Build-Test-Learn (DBTL) cycles. At a May 2025 workshop, a panel of experts recommended establishing a DOE Plant Transformation Capability (PTC) to overcome these barriers. The PTC would unite two missions: advancing research to achieve genotype-independent, automated methods, and delivering scalable transformation services through a user-facility model. With expected gains of 10–100x in efficiency, including transformation and cost reduction, the PTC would accelerate the path from discovery to engineered plants, expand community access and training, and support downstream applications and workflows including field trials and regulatory navigation. By enabling rapid and predictable crop engineering, the PTC would strengthen U.S. supply chains, enhance industrial competitiveness, and ensure that DOE’s genomic investments deliver national impact.

09 BIOMASS FUELS↗
DOE OSTI2015

A MultiAir®/MultiFuel Approach to Enhancing Engine System Efficiency

FCA US LLC (formally known as Chrysler Group LLC, and hereinafter “Chrysler”) was awarded an American Recovery and Reinvestment Act (ARRA) funded project by the Department of Energy (DOE) titled “A MultiAir®/MultiFuel Approach to Enhancing Engine System Efficiency” (hereinafter “project”). This award was issued after Chrysler submitted a proposal for Funding Opportunity Announcement DE-FOA- 0000079, “Systems Level Technology Development, Integration, and Demonstration for Efficient Class 8 Trucks (SuperTruck) and Advanced Technology Powertrains for Light-Duty Vehicles (ATP-LD).” Chrysler started work on this project on June 01, 2010 and completed testing activities on August 30, 2014. Overall objectives of this project were; Demonstrate a 25% improvement in combined Federal Test Procedure (FTP) City and Highway fuel economy over a 2009 Chrysler minivan; Accelerate the development of highly efficient engine and powertrain systems for light-duty vehicles, while meeting future emissions standards; and Create and retain jobs in accordance with the American Recovery and Reinvestment Act of 2009

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Validation of Advanced Photovoltaic Module Materials and Processes by Combined-Accelerated Stress Testing (C-AST)

Tessolar module technology was developed to allow the incorporation of 5 incremental module material innovations. Combined, these innovations may improve the efficiency and durability of the standard silicon cell module. The innovations evaluated are: electrically conductive adhesive (ECA) replacing soldering of tabbing ribbons, light-capturing ribbon (LCR), silicone encapsulant, 2 mm front glass with backsheet, and a polymer-composite module frame. Tessolar-constructed individually encapsulated cells incorporating the material innovations are used to assemble 60-cell modules. 2 x 2 cell mini-modules of the same materials were produced for combined-accelerated stress testing (C-AST). C-AST results demonstrate that the 2 x 2 cell mini-module of Tessolar construction out-performed mini-modules using both ECA with EVA and standard solder with EVA constructions in power production over 108 cycles of testing.

14 SOLAR ENERGY↗
DOE OSTI2023

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor’s sensitivity (EC 50 ) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC 50 . Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor

Abstract There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.

Kumar, Pankaj↗
DOE OSTI2025

Future Circular Collider Feasibility Study Report

Volume 3 of the FCC Feasibility Report presents studies related to civil engineering, the development of a project implementation scenario, and environmental and sustainability aspects. The report details the iterative improvements made to the civil engineering concepts since 2018, taking into account subsurface conditions, accelerator and experiment requirements, and territorial considerations. It outlines a technically feasible and economically viable civil engineering configuration that serves as the baseline for detailed subsurface investigations, construction design, cost estimation, and project implementation planning. Additionally, the report highlights ongoing subsurface investigations in key areas to support the development of an improved 3D subsurface model of the region. The report describes the development of the project scenario based on the ‘avoid-reduce-compensate’ iterative optimisation approach. The reference scenario balances optimal physics performance with territorial compatibility, implementation risks, and costs. Environmental field investigations covering almost 600 hectares of terrain—including numerous urban, economic, social, and technical aspects—confirmed the project’s technical feasibility and contributed to the preparation of essential input documents for the formal project authorisation phase. The summary also highlights the initiation of public dialogue as part of the authorisation process. The results of a comprehensive socio-economic impact assessment, which included significant environmental effects, are presented. Even under the most conservative and stringent conditions, a positive benefit-cost ratio for the FCC-ee is obtained. Finally, the report provides a summary of the studies conducted to document the current state of the environment.

Benedikt, M. [European Organization for Nuclear Re↗
DOE OSTI2026

Nanoscale ultrafast lattice modulation with a free-electron laser

Ultrafast optical laser-based techniques have enabled the probing of atomistic processes at their intrinsic temporal scales with femto- and attosecond resolution. However, the long wavelengths of optical lasers have prevented their interrogation and manipulation with nanoscale spatial specificity. Advances in hard X-ray free-electron lasers have enabled progress in developing X-ray transient-grating spectroscopy, a technique that aims to coherently control elementary excitations with nanoscale X-ray standing waves. Thus far, the realization of this technique at the nanoscale has been a challenge. Here we demonstrate X-ray transient-grating spectroscopy with spatial periods of the order of 10 nm via the subfemtosecond synchronization of two hard X-ray pump pulses at a precisely controlled crossing angle. This creates a thermal grating and preferentially excites coherent longitudinal acoustic phonon modes with the transient-grating wavevector. On probing with a third, variably delayed, X-ray pulse with the same photon energy, time-and-wavevector-resolved measurements of the modulation of the induced scattering intensity provide evidence of ballistic thermal transport at nanometre scales. Finally, these results highlight the potential of X-ray transient gratings as a powerful platform for studying nanoscale transport in condensed matter and the coherent control of nanoscale dynamics.

nonlinear optics↗
DOE OSTI2024

Using Generative AI to implement the discrepancy checker for a Nearly Autonomous Management and Control System for Advanced Reactors

Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Summary Report of Cable Aging and Performance Data for Fiscal Year 2014

As part of the Light Water Reactor Sustainability Program, science - based engineering approaches were employed to address cable degradation behavior under a range of exposure environments. Experiments were conducted with the goal to provide best guidance for aged material states, remaining life and expected performance under specific conditions for a range of cable materials. Generic engineering tests, which focus on rapid accelerated aging and tensile elongation, were combined with complementary methods from polymer degradation science. Sandia's approach, building on previous years' efforts, enabled the generation of some of the necessary data supporting the development of improved lifetime predictions models, which incorporate known material behaviors and feedback from field - returned 'aged' cable materials. Oxidation rate measurements have provided access to material behavior under low dose rate thermal conditions, where slow degradation is not apparent in mechanical property changes. Such data have shown aging kinetics consistent with established radiation - thermal degradation models.

Celina, Mathias C.↗
DOE OSTI2025

Realizing the Materials-Designed-To-Environments Promise of Additive Manufacturing Through a Fundamentally Different Approach to Optimization of Nonlinear Solid Mechanics Structures

Additive Manufacturing (AM) is expected to play a large role in the labs-wide goals of accelerating innovation and leading in modern engineering. More specifically, AM is seen as a key enabling technology for increasing the agility of nuclear deterrence and other national security applications involving complex coupled environments. However, the impact of AM on these initiatives has not been as wide-ranging as hoped because – despite its unique qualities – the focus has mostly been on detailed qualification to force AM components into pre-existing performance envelopes. This paradigm fundamentally precludes the novel possibilities afforded by the geometric and material flexibility of AM. In particular, the engineering of small-scale features to undergo buckling and contact can cause large geometric and symmetry changes which provide responsiveness to different environments. Despite almost a decade of observing such behavior, there exists no way to systematically design for AM to exploit it. Our goal for this project was to connect material design to multi-environment component performance by reconceptualizing how to design for AM to exploit the buckling and contact of small-scale features.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Earthquake-induced impact of base-isolated buildings: theory, numerical modeling, and design solutions

Earthquake shaking more intense than that used to size the horizontal clearance between a base–isolated building and near–rigid perimeter moat wall will result in hard impact, producing high–frequency, high–amplitude acceleration response in the structure and supported equipment. Herein this paper provides a design solution for the damaging effects of hard impact by installing a compliant engineered element in the load path between the base–isolated building and the moat wall, resulting in soft impact and a much smaller acceleration response. The engineered element assumed herein is a commercial–off–the–shelf marine fender with mechanical properties determined by physical testing. The attachment of a flexible engineered element, with well–defined stiffness and damping, to a near–rigid moat wall, simplifies the numerical modeling of the building–moat wall system and eliminates the need to bound the lateral stiffness of the wall for impact calculations. The simple model of the engineered element can be implemented in commercial finite element codes. Theory is developed for two–sided impact of a single–degree–of–freedom oscillator. Analytical solutions are derived for the shifted first–mode frequency of the impacted oscillator and for its free–vibration response. The shifted first–mode frequency is a function of the composite lateral stiffness of the isolator–engineered element assembly and its earthquake–induced displacement. Local peaks in the spectral response of the impacted oscillator form at odd integer multiples of the shifted first–mode frequency. The analytical solutions can be used to verify, in part, the numerical model used for impact analysis.

42 ENGINEERING↗
DOE OSTI2016

Developing Materials Processing to Performance Modeling Capabilities and the Need for Exascale Computing Architectures (and Beyond)

Additive Manufacturing techniques are presenting the Department of Energy and the NNSA Laboratories with new opportunities to consider novel component production and repair processes, and to manufacture materials with tailored response and optimized performance characteristics. Additive Manufacturing technologies already are being applied to primary NNSA mission areas, including Nuclear Weapons. These mission areas are adapting to these new manufacturing methods, because of potential advantages, such as smaller manufacturing footprints, reduced needs for specialized tooling, an ability to embed sensing, novel part repair options, an ability to accommodate complex geometries, and lighter weight materials. To realize the full potential of Additive Manufacturing as a game-changing technology for the NNSA’s national security missions; however, significant progress must be made in several key technical areas. In addition to advances in engineering design, process optimization and automation, and accelerated feedstock design and manufacture, significant progress must be made in modeling and simulation. First and foremost, a more mature understanding of the process-structure-property-performance relationships must be developed. Because Additive Manufacturing processes change the nature of a material’s structure below the engineering scale, new models are required to predict materials response across the spectrum of relevant length scales, from the atomistic to the continuum. New diagnostics will be required to characterize materials response across these scales. And not just models, but advanced algorithms, next-generation codes, and advanced computer architectures will be required to complement the associated modeling activities. Based on preliminary work in each of these areas, a strong argument for the need for Exascale computing architectures can be made, if a legitimate predictive capability is to be developed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Method of making an aero-derivative gas turbine engine

A method of making an aero-derivative gas turbine engine (100) is provided. A combustor outer casing (68) is removed from an existing aero gas turbine engine (60). An annular combustor (84) is removed from the existing aero gas turbine engine. A first row of turbine vanes (38) is removed from the existing aero gas turbine engine. A can annular combustor assembly (122) is installed within the existing aero gas turbine engine. The can annular combustor assembly is configured to accelerate and orient combustion gasses directly onto a first row of turbine blades of the existing aero gas turbine engine. A can annular combustor assembly outer casing (108) is installed to produce the aero-derivative gas turbine engine (100). The can annular combustor assembly is installed within an axial span (85) of the existing aero gas turbine engine vacated by the annular combustor and the first row of turbine vanes.

42 ENGINEERING↗
DOE OSTI2025

Time-resolved momentum imaging of UV photodynamics in structural isomers of iodopropane probed by site-selective XUV ionization

The photodynamics of 1- and 2-iodopropane (1 and 2-IP) were studied in a time-resolved scheme incorporating ultraviolet (UV) excitation and extreme ultraviolet (XUV) probing, which initiates photoionization selectively from the I 4d core orbital. UV absorption in the A-band of both isomers leads to prompt C–I bond fission, with significant disposal of internal energy into the propyl radical product. Site-selective ionization enables a range of charge transfer (CT) processes between the nascent highly charged iodine ions and neutral propyl radicals, dependent on the interfragment distance at the instant of ionization. Subtle differences in the dynamics of these CT processes between the two isomers are observed. In 1-IP, the kinetic energies of iodine ions produced by UV photodissociation and subsequent XUV multiple ionization increased notably over the first few hundred femtoseconds, which could be understood in terms of differing gradients along the photodissociation coordinates of the neutral and polycationic states involved in the pump and probe steps, respectively. Led by a recent report of HI elimination in UV photoexcited 2-IP [Todt et al., Phys. Chem. Chem. Phys., 22(46), 27338 (2020)], we also model the most likely signatures of this process in the present experiment, and can identify signal in the 2-IP data (that is absent or significantly weaker in the data from the unbranched 1-IP isomer) that is consistent with such a process occurring on ultrafast timescales.

Allum, Felix [Deutsches Elektronen-Synchrotron (DE↗
DOE OSTI2018

Co-Optimization of Fuels & Engines: FY17 Year in Review

The U.S. Department of Energy (DOE) Co-Optima initiative is accelerating the introduction of efficient, clean, affordable, and scalable high-performance fuels and engines. This effort is simultaneously tackling fuel and engine research and development (R&D) to maximize light-, medium-, and heavy-duty vehicle fuel economy and performance, while mapping lower-cost pathways to reduce emissions, leveraging diverse domestic fuel resources, boosting U.S. economic productivity, and enhancing national energy security. Co-Optima brings together DOE’s Office of Energy Efficiency & Renewable Energy (EERE), nine national laboratories, 13 universities, and numerous industry and government stakeholders in a collaboration exploring solutions with potential for near-term improvements to the types of fuels and engines found in most vehicles currently on the road, as well as to the development of revolutionary new combustion technologies. This report is an overview of the research activities and accomplishments of the Co-Optima initiative during the 2017 Fiscal Year.

02 PETROLEUM↗
DOE OSTI2019

Co-Optimization of Fuels & Engines: FY18 Year in Review

The U.S. Department of Energy (DOE) Co-Optima initiative is accelerating the introduction of efficient, clean, affordable, and scalable high-performance fuels and engines. This first-of-its-kind effort is simultaneously tackling fuel and engine research and development (R&D) to maximize light-, medium-, and heavy-duty vehicle fuel economy and performance, while mapping lower-cost pathways to reduce emissions, leveraging diverse domestic fuel resources, boosting U.S. economic productivity, and enhancing national energy security. Co-Optima brings together DOE’s Office of Energy Efficiency & Renewable Energy (EERE), nine national laboratories, 13 universities, and numerous industry and government stakeholders in a collaboration exploring solutions with potential for near-term improvements to the types of fuels and engines found in most vehicles currently on the road, as well as potential for the development of revolutionary new engine technologies. An overview is provided of the research activities and accomplishments of the Co-Optima initiative during the 2018 Fiscal Year.

02 PETROLEUM↗