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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Substitution Reactions in the Pyrolysis of Acetone Revealed through a Modeling, Experiment, Theory Paradigm

The development of high-fidelity mechanisms for chemically reactive systems is a challenging process that requires the compilation of rate descriptions for a large and somewhat ill-defined set of reactions. The present unified combination of modeling, experiment, and theory provides a paradigm for improving such mechanism development efforts. Here we combine broadband rotational spectroscopy with detailed chemical modeling based on rate constants obtained from automated ab initio transition state theory-based master equation calculations and high-level thermochemical parametrizations. Broadband rotational spectroscopy offers quantitative and isomer-specific detection by which branching ratios of polar reaction products may be obtained. Using this technique, we observe and characterize products arising from H atom substitution reactions in the flash pyrolysis of acetone (CH 3 C(O)CH 3 ) at a nominal temperature of 1800 K. The major product observed is ketene (CH 2 CO). Minor products identified include acetaldehyde (CH 3 CHO), propyne (CH 3 CCH), propene (CH 2 CHCH 3 ), and water (HDO). Literature mechanisms for the pyrolysis of acetone do not adequately describe the minor products. The inclusion of a variety of substitution reactions, with rate constants and thermochemistry obtained from automated ab initio kinetics predictions and Active Thermochemical Tables analyses, demonstrates an important role for such processes. Furthermore, the pathway to acetaldehyde is shown to be a direct result of substitution of acetone's methyl group by a free H atom, while propene formation arises from OH substitution in the enol form of acetone by a free H atom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantifying disorder one atom at a time using an interpretable graph neural network paradigm

Abstract Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric for local disorder, called SODAS. This metric encodes the diversity of the local atomic configurations as a continuous spectrum between the solid and liquid phases, quantified against a distribution of thermal perturbations. We apply this methodology to four prototypical examples with varying levels of disorder: (1) grain boundaries, (2) solid-liquid interfaces, (3) polycrystalline microstructures, and (4) tensile failure/fracture. We also compare SODAS to several commonly used methods. Using elemental aluminum as a case study, we show how our paradigm can track the spatio-temporal evolution of interfaces, incorporating a mathematically defined description of the spatial boundary between order and disorder. We further show how to extract physics-preserved gradients from our continuous disorder fields, which may be used to understand and predict materials performance and failure. Overall, our framework provides a simple and generalizable pathway to quantify the relationship between complex local atomic structure and coarse-grained materials phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Weakly solvating electrolytes: a solvation-centric paradigm for rechargeable metal batteries

Electrolyte design has long followed a solvation-first paradigm that prioritizes solvents capable of maximizing salt dissociation and ionic conductivity, while treating interfacial degradation and rheological limitations as secondary constraints. Although this approach has enabled significant progress in lithium-ion and sodium-ion batteries, it inherently favors solvent-dominated solvation structures that destabilize reactive metal interfaces. Weakly solvating electrolytes (WSEs) offer a fundamentally different strategy. By using solvents with intrinsically low donor strength and minimal electrostatic affinity for cations, WSEs suppress cation–solvent coordination and promote anion-rich solvation shells without relying on salt superconcentration. This shift lowers desolvation barriers, redirects interfacial decomposition pathways, and supports the formation of inorganic-rich, stable interphases. In this review, we discuss the molecular and solvation criteria that distinguish WSEs from conventional and concentrated or locally concentrated electrolyte systems, examine their implementation across different chemistries, and identify unresolved design challenges. WSEs are presented not as a niche formulation, but as a solvation-centric framework for rethinking electrolyte function in metal battery technologies.

Karbak, Mehdi [Pacific Northwest National Laborato↗
DOE OSTI2022

Deceptive Infusion of Data: A Novel Data Masking Paradigm for High-Valued Systems

This work addresses how analysts of a high-valued system (e.g., nuclear reactor, aircraft turbine designs) can extract findable, accessible, interoperable, and reusable scientific data for public dissemination to artificial intelligence and machine-learning (AI/ML) researchers in a manner that cannot be reverse-engineered, potentially compromising sensitive or proprietary information. State-of-the-art methods address this problem through data masking techniques, which allow access to a subset of the information while obfuscating private and potentially identifying information (e.g., personally identifying medical data). These methods are unsuitable for industrial engineering processes, where AI/ML tools need explicit access to all the data available to draw the best inference about the system to help optimize its performance and identify its vulnerabilities, etc. Our novel deceptive infusion of data paradigm provides a solution to this conundrum by developing a mathematical approach capable of concealing the identity of the system while providing full access to all the features employed by AI/ML tools to ensure their optimal performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

CIGS photovoltaics: reviewing an evolving paradigm

Copper indium selenide chalcopyrite-structure alloys with gallium (CIGS) are unique among the highest performing photovoltaic (PV) semiconductor technologies. They are structurally disordered, nonstoichiometric materials that have been engineered to achieve remarkably low bulk nonradiative recombination levels. Nevertheless, their performance can be further improved. This review adopts a fundamental thermodynamic perspective to comparatively assess the root causes of present limitations on CIGS PV performance. The topics of selectivity and passivation of contacts to CIGS and its multinary alloys are covered, highlighting pathways to maximizing the electrochemical potential between those contacts under illumination. Further, an overview of absorber growth methods and resulting properties is also provided. We recommend that CIGS researchers consider strategies that have been successfully implemented in the more mature wafer-based GaAs and Si PV device technologies, based on the paradigm of an idealized PV device design using an isotropic absorber with minimal nonradiative recombination, maximal light trapping, and both electron-selective and hole-selective passivated contacts. We foresee that CIGS technology will reach the 25% efficiency level within the next few years through enhanced collection and reduced recombination. To significantly impact power-generation applications, cost-effective, manufacturable solutions are also essential.

14 SOLAR ENERGY↗
DOE OSTI2024

Paradigm for approaching the forbidden phase transition in the one-dimensional Ising model at fixed finite temperature: Single chain in a magnetic field

In a previous paper, the forbidden spontaneous phase transition in the one-dimensional Ising model was found to be approachable arbitrarily closely in decorated ladders by ultra-narrow phase crossover (UNPC) at a given finite temperature T 0 with the crossover width 2δT reduced exponentially, which resemble a genuine first-order transition with large latent heat. Here, I reveal that the forbidden phase transition can be approached at fixed T 0 as well in decorated single-chain Ising models in the presence of a magnetic field, in which T 0 is determined by the interactions involving only the decorated parts and the magnetic field, while 2δT is independently, exponentially reduced (δT = 0 means a genuine transition) by restoring the ferromagnetic interaction between the ordinary spins on the chain backbone-which was neglected in the previous studies of pseudo-transition-thus manifesting that this asymptoticity to the forbidden transition is essentially the buildup of coherence in preformed crossover of local states. Furthermore, I show that the UNPC can be realized even in the absence of the conventional geometric frustration because the magnetic field itself can induce previously unnoticed hidden spin frustration. In conclusion, these findings make the doors wide open to the engineering and utilization of UNPC as a new paradigm for exploring exotic phenomena and 1D device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Paradigm for approaching the forbidden spontaneous phase transition in the one-dimensional Ising model at a fixed finite temperature

The Ising model describes collective behaviors such as phase transitions and critical phenomena in various physical, biological, economical, and social systems. It is well known that spontaneous phase transition at finite temperature does not exist in the Ising model with short-range interactions in one dimension. Yet, little is known about whether this forbidden phase transition can be approached arbitrarily closely—at fixed finite temperature. Here I use symmetry analysis of the transfer matrix to reveal the existence of spontaneous ultranarrow phase crossover (UNPC) at finite temperature in one class of one-dimensional Ising models on decorated two-leg ladders, in which the crossover temperature T 0 is determined solely by on-rung interactions and decorations, while the crossover width 2 δ T is independently, exponentially reduced ( δ T = 0 means a genuine phase transition) by on-leg interactions and decorations. These findings establish a simple ideal paradigm for realizing an infinite number of one-dimensional Ising systems with spontaneous UNPC at desirable T 0 , which would be characterized in routine laboratory measurements as a genuine first-order phase transition with large latent heat thanks to the ultranarrow δ T (say less than one nanokelvin), paving a way to push the limit in our understanding of phase transitions and the dynamical actions of frustration arbitrarily close to the forbidden regime. Published by the American Physical Society 2024

1-dimensional systems↗
DOE OSTI2025

Fusion Intelligence: A Paradigm for Merging Natural and Artificial Intelligence

Here, this article presents fusion intelligence (FI), a bio-inspired paradigm that synergistically integrates the intrinsic capabilities of intelligent biological organisms with the advanced potential of artificial intelligence (AI)-driven systems. FI harnesses the unique intelligence, sensing, actuation, and mobility attributes of living organisms, such as honeybees, blending these with the sophisticated data-driven problem-solving functionalities of AI. By bridging the gap between natural intelligence (NI) and AI, FI can transform how humans interact with and harness the capabilities of both natural and artificial systems. This article presents the model of FI and its application to solve practical problems, discusses the challenges and future directions of FI research, emphasizing a generalized approach to solve complex problems, where AI can observe/control NI in a closed-loop system. We demonstrate the potential for FI to enhance the performance of an agricultural IoT system via a simulated case study, which achieves 50% improvement in the efficacy of insect pollination (entomophily).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Quantum Programming Paradigms and Description Languages

Here, this article offers perspective on quantum computing programming languages, as well as their emerging runtimes and algorithmic modalities. With the scientific high-performance computing (HPC) community as a target audience, we describe the current state of the art in the field, and outline programming paradigms for scientific workflows. One take-home message is that there is significant work required to first refine the notion of the quantum processing unit in order to integrate in the HPC environments. Programming for today’s quantum computers is making significant strides toward modern HPC-compatible workflows, but key challenges still face the field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Multi-objective Optimization Paradigm for Toroidal Inductors with Spatially Tuned Permeability

Spatially tuning core permeability of an electromagnetic device enables superior performance. A permeability profile can be heuristically selected to improve the flux distribution in a device with a given geometry, but in order to fully leverage the capacity of spatial dependent permeability engineering, the geometry and the permeability should be optimized simultaneously. The work herein presented sets forth a multi-physics design optimization paradigm that includes the permeability profile tuning in the context of an inductor design. This approach enables the determination of Pareto optimal fronts consisting of a set of optimal solutions against competing objectives (e.g. mass and loss) under imposed constraints. To this end, analytical solutions of the heat transfer and electromagnetic formulations are derived for toroidal inductors. The software implemented in Matlab 2018b is available online as an attachment to this paper.

42 ENGINEERING↗
DOE OSTI2020

Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring

The laboratory identification of antibacterial resistance is a cornerstone of infectious disease medicine. In vitro antimicrobial susceptibility testing has long been based on the growth response of organisms in pure culture to a defined concentration of antimicrobial agents. By comparing individual isolates to wild type susceptibility patterns, strains with acquired resistance can be identified. Acquired resistance can also be detected genetically. After many decades of research, the inventory of genes underlying antimicrobial resistance (AMR) is well known for several pathogenic genera including zoonotic enteric organisms such as Salmonella and Campylobacter and continues to grow substantially for others. With the decline in costs for large scale DNA sequencing, it is now practicable to characterize bacteria using whole genome sequencing (WGS), including the carriage of resistance genes in individual microorganisms and those present in complex biological samples. With genomics we can generate comprehensive, detailed information on the bacterium, the mechanisms of antibiotic resistance, clues to its source, and the nature of mobile DNA elements by which resistance spreads. These developments point to a new paradigm for antimicrobial resistance detection and tracking for both clinical and public health purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Paradigm for universal quantum information processing with integrated acousto-optic frequency beamsplitters

Frequency-bin encoding offers tremendous potential in quantum photonic information processing, in which a single waveguide can support hundreds of lightpaths in a naturally phase-stable fashion. This stability, however, comes at a cost: arbitrary unitary operations can be realized by cascaded electro-optic phase modulators and pulse shapers, but require nontrivial numerical optimization for design and have thus far been limited to discrete tabletop components. In this article, we propose, formalize, and computationally evaluate a new paradigm for universal frequency-bin quantum information processing using acousto-optic scattering processes between distinct transverse modes. We show that controllable phase matching in intermodal processes enables 2 × 2 frequency beamsplitters and transverse-mode-dependent phase shifters, which together comprise cascadable FRequency-transverse-mODe Operations (FRODOs) that can synthesize any unitary via analytical decomposition procedures. Modeling the performance of both random gates and discrete Fourier transforms, we demonstrate the feasibility of high-fidelity quantum operations with existing integrated photonics technology, highlighting prospects of parallelizable operations achieving 100% bandwidth utilization. Our approach is realizable with CMOS technology, opening the door to scalable on-chip quantum information processing in the frequency domain.

Lukens, Joseph M. [Purdue Univ., West Lafayette, I↗
DOE OSTI2021

A science paradigm shift is needed for Earth and Environmental Systems Sciences (EESS) to integrate Knowledge-Guided Artificial Intelligence (KGAI) and lead new EESS-KGAI theories

The focal area of this white paper is learning from complex data through the use of AI techniques and AI-derived model components. Specifically, we advocate for research programs to develop knowledge-guided AI (KGAI) in the Earth and Environmental Systems sciences (EESS) as a basic research paradigm that is separate from (but supports) any specific Earth system model, modeling components, and modeling workflows, and even separates from specific hypothesis-driven questions about individual Earth system processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modular HF Isolated MV String Inverters Enable a New Paradigm for Large PV Farms

The “Modular HF Isolated MV String Inverters Enable a New Paradigm for Large PV Farms” project focuses on exploring alternative power converter and system-level plant configurations to achieve the lowest cost and highest energy output for a given solar plus storage (e.g., PV + battery) plant, including the use of medium voltage (MV) collection while taking into account detailed models of all elements. To realize this objective, four approaches were utilized (i) employ a novel Medium Voltage String Inverter (MVSI) topology (soft switching solid state transformer – S4T) to convert 1000 Vdc to 4.16 kVac; (ii) plant collection using standard, low-cost overhead MV distribution network; (iii) enable energy storage integration without additional converter cost to achieve dispatchability of the PV resource; and (iv) provide advanced functionality (autonomous operation, track ISO signals for dynamic balancing and ancillary services, and PV farm operation as a virtual grid resource). Subsequently and in alignment with the previously mentioned approaches, the project was structured in five efforts (i) S4T MVSI simulation and design; (ii) system analysis and storage optimization; (iii) financial analysis; (iv) power converter prototype build and test; and (v) regulatory and commercial impact study. The outcomes provided by each effort can be summarized as follows (i) Project explored the use of MV AC distribution architecture for hybrid PV+storage utility-scale PV farms; (ii) Detailed loss and LCOE analysis for AC and DC side BESS architecture, including multiple converter topologies, as well as for proposed MVSI/MDCT systems; (iii) MVSI was built and holds promise but needs lower-cost high-voltage Si-C devices, which does not seem possible in the near term; (iv) MDCT provides a simpler modular building block – validated through HIL and farm level modeling, simulation and experimental validation; (v) 300 kVA MDCT prototype built and tested, technology is being commercialized; and (vi) Regulatory model of utility building PV plants, where PV panels are treated as DC generation (IPP), seems viable and can allow improved grid integration.

14 SOLAR ENERGY↗
DOE OSTI2023

Parallel Time Integration: An Approaching Paradigm Shift for Scientific Computing

This note argues that parallel-in-time methods will be necessary for doing high-fidelity time-dependent simulations in the future. A “proof” is given to support the argument and to provide a framework for debate. The effect of a parallel-in-time paradigm on scientific computing practice is also discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A New Paradigm for Observing and Modeling of Air-Sea Interactions to Advance Earth System Prediction

The protection of people, property, and environmental resources from extreme weather, seasonal patterns, and climate change drives the need for predictions of weather, ocean, and climate patterns that have skill and value at timescales longer than traditional 1-10-day forecasts, including outlooks spanning weeks to decades. Advancing Earth System Prediction (ESP) skill at this range of timescales requires improved observations, understanding, and modeling of the processes in the ocean boundary layer, the atmospheric boundary layer, and their interface. A new way of referring to this coupled system is the Air-Sea Transition Zone (ASTZ). The report that follows is framed by the paradigm that the ASTZ is a single entity that regulates the flow of energy and matter between the ocean and the atmosphere. The ASTZ is thus the medium through which the ocean and atmosphere respond to and influence one another across their often disparate scales of variability. ASTZ modeling, observing, and understanding needs are particularly acute because very few measurements exist over oceans, and even fewer span the entire ASTZ, even though oceans cover 70% of Earth’s surface and are the source of most of the rain and snow that falls on both the land and the oceans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Neutrino physics beyond the current paradigm

An exciting program of international neutrino experiments aims to complete our understanding of three-neutrino mixing in the Standard Model (SM), which has had great success in describing world neutrino data. However, there exist a number of short-baseline neutrino anomalies that do not fit into this simple picture and could be pointing us instead to phenomena beyond the Standard Model (BSM). Neutrinos and neutrino experiments are excellent laboratories to search for BSM physics for a number a reasons. First, neutrinos mass itself is evidence of BSM physics as it implies the addition of new fields to the SM. In addition, neutrino properties are not well-constrained and allow sizable, new interactions. Finally, accelerator- and reactor-based short-baseline neutrino experiments bring high luminosity sources of photons, nuclear, and meson decays near large, sensitive detectors and can therefore probe a variety of dark sector models. In this talk, I will give an overview of worldwide accelerator- and reactor-based short-baseline neutrino experiments and their efforts to search for physics beyond the current paradigm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling under uncertainty, and its application to accelerating the discovery of new materials

In this report we summarize the work conducted by PI Perdikaris and his group under this Early Career project DE–SC0019116 during the period of 09/01/2018 – 08/31/2023. The central aim of the work was to introduce a new paradigm for scientific data analysis that can seamlessly synthesize rigorous mathematical modeling with data of variable fidelity (e.g., measurements at multiple scales/resolutions or predictions of variable fidelity models) and multiple modalities (e.g., images, time–series, or scattered measurements). The setting we are interested in involves complex systems that are partially observed and whose dynamical behavior could be hard to model or totally unknown. The inherent uncertainty associated with this setting necessitates a departure from the classical deterministic realm of modeling and scientific computation, and, consequently, our main building blocks can no longer be crisp deterministic numbers and governing laws, but instead we must operate with probabilistic models.

97 MATHEMATICS AND COMPUTING↗