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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Energy-efficient scientific computing using chemical reservoirs

The rapid growth of computing demands driven by scientific computing, data analytics, and artificial intelligence (AI) advancements has exposed the limitations of traditional digital processing systems. These systems are nearing physical energy barriers, making significant gains in energy efficiency increasingly unattainable. As we advance toward post-exascale computing, disruptive approaches are critical to overcoming these limitations. Among emerging analog solutions, biochemical computing offers a transformative path for achieving orders-of-magnitude improvements in energy efficiency. By leveraging the natural optimization capabilities of chemical reaction networks (CRNs), biochemical systems have the potential to meet high-performance computing needs through natural scalability. However, numerous challenges remain, including theoretical limitations in mapping computational problems to CRNs and practical barriers in implementing biochemical computing devices. In this paper, we present a framework for chemical computation using biochemical systems and introduce key components of our approach for energy-efficient scientific computing. We showcase the feasibility of this framework by solving a system of ordinary differential equations by emulating a chemical reservoir device, demonstrating its potential for addressing modern computing challenges. This work lays a foundational step toward harnessing the computational power of chemistry to design energy-efficient, scalable, high-performance next-generation computing systems.

Johnson, Connah G. M. [Pacific Northwest National ↗
DOE OSTI2025

ARC-DPA 1-MeV Neutron Fluence Equivalence Model for GaAs

Here, the legacy data used in the production of the American Society for Testing and Materials (ASTM) E722 standard for gallium arsenide (GaAs) were fit with the athermal recombination corrected-displacements per atom (ARC-DPA) model for the development of a novel 1-MeV neutron equivalent fluence metric. Improving on previous work, the coefficients for the ARC-DPA model were optimized using a conjugate gradient method, and the uncertainties in the observed damage in different benchmark neutron fields were sampled to quantify their contribution to the damage metric. The optimized parameters of −0.474 ± 0.03 for b arcdpa and 0.016 ± 0.002 for c arcdpa provided good agreement and indicated that the solution is not sensitive to the corresponding fluence uncertainties. Compared to the current 1-MeV neutron fluence equivalence standard for displacement damage in GaAs, our results indicate that for a thermal reactor neutron environment, displacement damage has been underestimated by around 25% and that the saturation value for the damage efficiency had been higher than previously modeled.

1-MeV equivalent fluence↗
DOE OSTI2025

Conin

SAND2025-07645O Conin is a Python library that supports constrained analysis of probabilistic graphical models (PGMs). It enables constrained inference and learning for hidden Markov models, Bayesian networks, dynamic Bayesian networks, and Markov networks. Conin interfaces with the pgmpy library to specify general probabilistic graphical models with a variety of optimization solvers to support learning and inference. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2024

CHMMPY: A python package for constrained Hidden Markov Models

SAND2025-11909O chmmpy software analyzes multivariate timeseries data to detect patterns. It uses a Hidden Markov Model (HMM) and application-specific constraints that reflect known relationships among hidden states to accomplish this. The chmmpy software provides a generic framework for expressing application-specific constraints and supporting constrained HMM inference using optimization solvers. chmmpy is available on GitHub. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William↗
DOE OSTI2024

Ducted Fuel Injection and Cooled Spray Technologies for Particulate Control in Heavy-Duty Diesel Engines

Heavy-duty diesel engine manufacturers are continually seeking simple, low-cost technologies to reduce emissions. Ducted Fuel Injection (DFI) and Cooled Spray (CS) technologies have emerged as promising solutions, offering the potential for nearly sootless operation. These innovations could significantly decrease harmful Particulate Matter (PM) emissions while enabling further optimization to reduce Nitrogen Oxides (NOx) and increase efficiency. While initial experiments across various engine types have shown promise, uncertainties remain regarding the ideal geometry, scaling properties, and effectiveness of these technologies across different operating conditions. This project aims to address these knowledge gaps through experiments in both optical and metal single-cylinder engines.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

A Unified Beam-Dynamics and Hardware Design Framework for Hybrid Nonlinear-Kicker Injection in NSLS-II

Nonlinear kickers (NLKs) enable off-axis injection in ultralow-emittance storage rings by providing a strong kick to the injected beam while remaining nearly transparent to the stored beam. In hybrid schemes, a conventional four-kicker bump defines the injected trajectory, and the NLK reduces the first-turn action under constrained beam offset and optics conditions. Effective operation additionally requires stable and reproducible first-turn injection trajectories. We develop a compact action–angle framework that expresses NLK dynamics in terms of Courant–Snyder invariants and yields an analytical bound on achievable action reduction. This formulation provides direct design rules for NLK placement, phase advance, injected-beam offset, and kicker field profile. Within this framework, we identify the 8-wire NLK as a practical baseline and extend its design by relaxing the square-geometry constraint, enabling inward shifting of the off-axis field peak while preserving on-axis field and gradient cancellation. Application to the NSLS-II lattice shows how aperture, pulsed-power, and mechanical constraints combine to determine a coupled design solution. Multi-turn tracking confirms that candidate NLK locations maintain sufficient stay-clear (aperture-clearance) margin, while the optimized wire geometry reduces the required current and Lorentz force load. The results establish a unified approach for NLK-assisted injection design and provide a practical pathway for upgrades in diffraction-limited storage rings.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Characterization of Deformational Isomerization Potential and Interconversion Dynamics with Ultrafast X-ray Solution Scattering

Dimeric complexes composed of d 8 square planar metal centers and rigid bridging ligands provide model systems to understand the interplay between attractive dispersion forces and steric strain in order to assist the development of reliable methods to model metal dimer complexes more broadly. [Ir 2 (dimen) 4 ] 2+ (dimen = para-diisocyanomenthane) presents a unique case study for such phenomena, as distortions of the optimal structure of a ligand with limited conformational flexibility counteract the attractive dispersive forces from the metal and ligand to yield a complex with two ground state deformational isomers. Here, in this work, we use ultrafast X-ray solution scattering (XSS) and optical transient absorption spectroscopy (OTAS) to reveal the nature of the equilibrium distribution and the exchange rate between the deformational isomers. The two ground state isomers have spectrally distinct electronic excitations that enable the selective excitation of one isomer or the other using a femtosecond duration pulse of visible light. We then track the dynamics of the nonequilibrium depletion of the electronic ground state population—often termed the ground state hole—with ultrafast XSS and OTAS, revealing a restoration of the ground state equilibrium in 2.3 ps. This combined experimental and theoretical study provides a critical test of various density functional approximations in the description of bridged d 8 –d 8 metal complexes. The results show that density functional theory calculations can reproduce the primary experimental observations if dispersion interactions are added, and a hybrid functional, which includes exact exchange, is used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

GIS Supported Optimal Site Selection for Coastal Structure Integrated Wave Energy Converters: Preprint

There is an urgent need for adaptative engineering towards more resilient coastal communities, and Coastal Structure Integrated Wave Energy Converters (CSI-WECs) are a promising solution. CSI-WECs are wave energy converters (WECs) that are built into coastal protection structures, such as breakwaters. These devices provide the dual benefits of coastal protection and local energy production, and unlike other WECs, maximizing energy production is not always the main objective. CSI-WECs are located near the shore, where the wave resource is lower, thus site selection for these devices differs from the typical offshore WECs. Other attributes of a site that may be more important than wave power include existing coastal structures, port proximity, electric transmission line proximity, and location of disadvantaged communities. Geospatial information systems (GIS) interfaces can be used to easily visualize geospatial data that represents these difference kinds of criteria important for the determination of optimal marine energy sites. Multi-Criteria Decision Analysis (MCDA) is a geospatial analysis method that allows for the evaluation of multiple, usually overlapping, criteria. This project applies GIS-based MCDA methods to two distinct case studies in Puerto Rico and California for CSI-WEC site selection. The two study sites contrast in terms of wave resource, coastal hazards, and local energy needs. This research demonstrates the utility of applying an MCDA framework within GIS to facilitate efficient site selection for devices with unique characteristics in different use cases.

coastal protection↗
DOE OSTI2025

Understanding plasma turbulence through exact coherent structures

Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a generalized framework to analyze plasma turbulence that utilizes periodic orbit theory. In periodic orbit theory, doubly periodic solutions (coherent structures) of the governing equation(s) serve as building blocks of the considered turbulent dynamics. To illustrate the concept and method, the particularly simple Kuramoto–Sivashinsky (referred to here as LMRT for the original authors: LaQuey, Mahajan, Rutherford, and Tang) trapped-ion mode toy model is used. By applying numerical optimization techniques to the LMRT equation, we extract coherent spacetime patterns that represent the library of allowable fundamental structures of the equation. These structures provide a framework to systematically describe turbulence as a composition of recurrent solutions, revealing an underlying order within chaotic plasma motion. Although illustrated here using the simplified LMRT model for clarity, this framework provides a general strategy that can be extended to more complex and realistic models of plasma turbulence, including gyrokinetic systems. This offers a new method for predicting and potentially controlling transport processes in fusion plasmas by providing a bridge between nonlinear dynamical systems theory and plasma physics in the form of a generalized framework with which to analyze and understand spatially extended nonlinear partial differential equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Microwave-assisted pyrolysis of hydrocarbons using iron-based alumina catalysts obtained via solution combustion synthesis

The demand for hydrogen is growing which makes the development of clean and efficient H2 synthesis technologies imperative. Microwave-assisted, thermocatalytic, dehydrogenation of hydrocarbons has demonstrated the ability to generate H2 with high yield and selectivity, leaving behind valuable solid carbon byproducts. However, this microwave-assisted process is unoptimized which prevents it from being utilized in industry. A critical component of optimization is the development of a catalyst that is catalytically active, a good microwave absorber, and can be regenerated for repeated dehydrogenation cycles. Previous studies that focused on plastic waste decomposition have used iron-based alumina (FeAlxOy) made via solution combustion synthesis (SCS). Unexplored is the effect of tuning SCS parameters on dehydrogenation performance, the use of these materials in hydrocarbon decomposition to H2, and the regeneration of these catalysts. This dissertation has three objectives: (1) characterize the relationship between SCS parameters and the material properties of FeAlxOy, (2) determine how differences in the material properties of FeAlxOy influence their performance as catalysts during microwave-assisted pyrolysis of fossil fuels, and (3) investigate the Boudouard reaction to regenerate the FeAlxOy post-dehydrogenation.

Chanoi, Zachary Aidan↗
DOE OSTI2024

Stochastic minibatch approach to the ptychographic iterative engine

The ptychographic iterative engine (PIE) is a widely used algorithm that enables phase retrieval at nanometer-scale resolution over a wide range of imaging experiment configurations. By analyzing diffraction intensities from multiple scanning locations where a probing wavefield interacts with a sample, the algorithm solves a difficult optimization problem with constraints derived from the experimental geometry as well as sample properties. The effectiveness at which this optimization problem is solved is highly dependent on the ordering in which we use the measured diffraction intensities in the algorithm, and random ordering is widely used due to the limited ability to escape from stagnation in poor-quality local solutions. In this study, we introduce an extension to the PIE algorithm that uses ideas popularized in recent machine learning training methods, in this case minibatch stochastic gradient descent. Our results demonstrate that these new techniques significantly improve the convergence properties of the PIE numerical optimization problem.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

An optimization approach for cryogenic distillation-based protium removal systems in magnetic fusion energy fuel cycles

Tritium inventory reduction for fusion power plants is central to the successful adoption of fusion energy. The advent of direct internal recycling in deuterium-tritium fusion fuel cycle design has led to significant reduction in startup tritium inventory estimates for fusion power plants but requires an isotope rebalancing and protium removal (IRPR) system to ensure acceptable isotopic fuel composition. Cryogenic distillation is a potential solution for near-term deployment in an IRPR system due to its demonstrated performance in similar operating regimes. Using protium removal in the fuel cycle as the primary performance metric, this paper presents an optimization methodology for a single-column continuous cryogenic distillation-based IRPR system for a 500 MW fus magnetic fusion device. Distillation column optimization was performed using the CryOgenic Distillation For Isotopic Separation of Hydrogen (CODFISH) code developed at Savannah River National Laboratory. The distillation column design presented maximizes direct recycling of hydrogen isotopes from the fusion chamber exhaust to the fueling system while minimizing IRPR system steady-state tritium inventory. The optimized IRPR distillation column presented achieves direct recycling of 60 % of the hydrogen isotopes in the fusion chamber exhaust with an estimated steady-state system tritium inventory <30 g. In conclusion, the optimized IRPR distillation column operation was then used to estimate the design requirements for a detritation column to treat the IRPR system effluent stream.

CryOgenic distillation↗
DOE OSTI2024

Solving the Grid Optimization Competition Challenge 3 Problem

The Grid Optimization Competition Challenge 3 Problem posed a multiperiod security-constrained unit commitment problem with base-case AC power flow. The problem formulation includes binary unit commitment decisions, nonlinear AC power flow and balance, dispatchable loads, and linearized contingency real power flow, among other features. This talk will present a modified consensus ADMM algorithm, which splits the problem into mixed-integer linear and nonlinear components, as a heuristic solution method for this large-scale mixed integer nonlinear program. We will present some computational results from the competition for our implementation and reflect on the challenges of participating the grid optimization competition.

AC power flow↗
DOE OSTI2025

From bench to biofactory: high-throughput technologies and automated workflows to accelerate biomanufacturing

Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remains to be investigated to optimize these biobased processes for a robust bioeconomy. Here, we review the current state of the art, some key challenges and possible solutions. We see a critical role of automation, high-throughput technologies, self-driving and cloud labs, and data management to enable Artificial Intelligence/Machine Learning and mechanistic models to overcome the design space challenges and accelerate the development of novel bio-based solutions. Accurate models will expedite the development and scale-up of engineered microbes for a range of final products from many starting materials.

Petzold, Christopher J↗
DOE OSTI2025

Optimization of Delignified Wood Rods for Interfacial Solar Evaporation

Interfacial solar evaporation using three-dimensional evaporator materials has shown promise to achieve high evaporation rates exceeding the photothermal limit for water treatment and resource recovery processes. However, challenges remain in optimizing the material geometry to balance the vertical capillary uptake of water and the rate of evaporation to achieve both stable and high evaporation rates. Delignified wood can serve as a highly porous and hydrophilic substrate material to achieve high evaporation rates. In this work, we designed a suspended biochar-coated delignified wood rod evaporator and investigated the influence of its geometric parameters on its evaporation performance. The height of the evaporator exposed to air for evaporation was observed to be an important parameter in governing the evaporation rate, as shorter evaporators limited the available surface area for evaporation, but taller evaporators could not achieve sufficient rates of capillary uptake to maintain stable evaporation rates over 24 h under 1-sun illumination (1 kW m –2 ). In conclusion, the exposed height of the evaporator was optimized to achieve an average hourly evaporation rate of 3.05 ± 0.23 kg m –2 h –1 , which could be maintained in saline solutions containing up to 5 wt % NaCl.

Coating materials↗
DOE OSTI2025

Hydrogen Generation and Serpentinization of Olivine Under Flow Conditions

Serpentinization of olivine is often studied in the laboratory under batch conditions. Olivine conversion in situ with enhanced natural hydrogen production will likely be implemented via injection of aqueous solutions. Hence, transport is relevant to the extent of olivine reaction and, potentially, the morphology of precipitates formed. To test conditions for optimal H 2 generation and outcomes, serpentinization was induced by injecting pH = 12.5 brine at 0.015 cm 3 /min (0.5 pore volumes per day) into an olivine sand pack (250 to <355 μm grain size) at 245°C generating, at minimum 76 and 89 mol% H 2 at 35 and 57 d, respectively. Grain-coating serpentine with radiating needles cemented the reacted sand grains. Importantly, pore space was maintained between the dissolving grains and the serpentine precipitates. Hence, reactivity continued as a result of fluid access to mineral surfaces, the large grain size, and the continuous injection of undersaturated alkaline fluids.

08 HYDROGEN↗
DOE OSTI2024

Image processing tools for petabyte-scale light sheet microscopy data

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson–Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

97 MATHEMATICS AND COMPUTING↗