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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 271 records · Page 15

Material Compatibility of 3D Printed Polymer Composites with Low GWP Refrigerants

The recent development of 3D printing brings numerous opportunities to develop polymer heat exchangers with desired configurations and allows access to the new complex engineering design for better performance. To be used in the HVAC&R system, the compatibility of these materials to refrigerants needs to be thoroughly investigated and understood. This study tested the material compatibility of the printed polymer composites according to the ASHRAE Guideline 38 using metal pressure vessels. These printed parts were tested with R-134A, R-1234YF, R-1234ZE, R-1233ZD(E), and 32-3 MAF POE (10 wt.%) was used as the lubricants. The change in volume, mass, hardness, and mechanical properties was studied in detail. Different compatibility of the composites with refrigerants was observed when the composition of the composite changed. After exposure to refrigerants, the morphological and thermal properties were studied with the scanning electron microscope, thermogravimetric analysis, and differential scanning calorimetry to further reveal the influence of these refrigerants.

Li, Kai↗

EXPERIMENTAL AND MODELING STUDY OF MOLECULAR TRANSPORT PHENOMENA IN COMPLEX LIQUID MIXTURES USING COVALENT ORGANIC FRAMEWORK MEMBRANES

Currently, 10-15% of the world’s energy is consumed by chemical separations, and more than 80% of that is used to purify organic liquids and recover rare earth elements and critical minerals. Membrane nanofiltration presents an energy-efficient, cost-effective, and eco-friendly alternative to current separation technologies. These complex liquid environments require high- performance, chemically-resistant membrane materials. Recently discovered Covalent Organic Frameworks (COFs) possess desirable properties as membrane materials for complex liquid separations. COFs are highly crystalline, chemically and thermally stable, with tunable size and charge. COFs, especially two-dimensional highly crystalline COFs, possess narrow pore-size distribution and controlled porous structures. Two-dimensional COFs are also resistant to swelling, another feature beneficial in complex liquid separations. Molecular interactions in complex liquid systems often dictate final membrane performance, resulting in a discrepancy between designed and apparent COF properties. Understanding and resolving this discrepancy is critical in utilizing COF membranes as a viable alternative to energy-intensive separations. The primary objective of this thesis was to use a commercially available COF TpPa-1 as a platform to investigate how mixed solvent environment affects COF membrane performance via experimental and molecular modeling studies. Specifically, the effects of solution pH, solvent- solvent-solute interactions in mixed solvents, and COF chemistry were carefully examined on apparent TpPa-1 pore size and permeability and targeted solute rejection of COF membranes for neat and mixed solvents. Experimental COF filtration performance was compared and corroborated with modeling predication. Findings from this study will provide guidance for future COF design, synthesis, and desired functional COF membrane performance.

Barnes, Anastasia↗

Final Report for Closing the Loop Between In Situ Stress Complexity and EGS Fracture Complexity

Characterizing in situ stress is essential in Enhanced Geothermal System (EGS) for both risk assessment and operation design. Standard stress measurement techniques such as diagnostic fracture injection tests (DFITs) require creating hydraulic fractures and apply analytical methods such as the G -function analysis to estimate the stress. These classical approaches rely on several assumptions, including but not limited to: (i) the induced fracture is planar and persistent, and (ii) the fracture plane is normal to the minimum horizontal stress. However, these assumptions may not hold in EGS environments like Utah FORGE, where thermo-hydro-mechanical (THM) coupling, wellbore deviation, and rock heterogeneity can alter the local stress condition and consequently lead to fracture complexities in both near-well and far-field regions.

15 GEOTHERMAL ENERGY↗

Molecular concentration field design using closed-form steady-state solutions

Control over spatial concentration fields represents a fundamental challenge in designing synthetic biological systems and programmable soft materials. While nature creates morphogen gradients that orchestrate complex developmental processes, synthetic approaches have largely relied on empirical optimization and computationally intensive simulations. Here, we present an analytical framework for steady-state concentration fields generated by finite-sized localized sources in diffusion–degradation systems and derive closed-form solutions for one-, two-, and three-dimensional geometries. By expressing these solutions in dimensionless form, we show that gradient steepness and spatial structure are organized by the Thiele modulus, which captures the competition between diffusion and degradation length scales. The analysis reveals distinct design regimes: in degradation-dominated systems, gradient shape is governed by exponential decay and becomes dimension-independent, whereas in diffusion-dominated systems, gradient magnitude and extent follow dimension-dependent power-law scaling. Building on these results, we introduce a quantitative design strategy that uses threshold-based criteria to program concentration ranges by tuning physically accessible parameters, most directly the production rate, while holding transport and degradation properties fixed. Comparisons with numerical solutions and reported experimental systems demonstrate consistency with the predicted scaling behavior. Together, this work provides a generalizable and physically transparent framework for designing steady-state concentration fields in synthetic biological and soft matter systems, enabling predictive control of gradient-mediated organization without reliance on extensive numerical optimization.

Kim, Dong Woo [Johns Hopkins University, Baltimore↗

Fundamental Studies of the Vibrational, Electronic, and Photophysical Properties of Tetrapyrrolic Architectures

The ability to capture and utilize light in the near-ultraviolet (NUV), visible and near-infrared (NIR-I and NIR-II) spectral regions (i.e., 320–400, 400–700, 700–1000, 1000–1700 nm) is essential for any solar-energy conversion scheme. Nature employs chlorophylls and bacteriochlorophylls in light-harvesting architectures to absorb light in the blue and red/NIR regions. Accessory pigments (carotenoids, bilins) augment absorption of the (bacterio)chlorophylls in the green region. The harvested energy is funneled to a reaction center protein, where charge separation occurs. Subsequent migration of the electron and the hole stabilizes and stores the energy from light via redox chemistry. The long-term objective of the Bocian/Holten&Kirmaier/Lindsey research program under this DOE grant has been to develop tetrapyrrole-based molecular architectures that absorb sunlight, funnel energy and separate charge with high efficiency. Integral to the program has been iterative cycles of design, synthesis and characterization that provided deep insights into the relationships between chemical composition, electronic structure, and key static and dynamic properties (vibrational, redox, photophysical, energy/charge transfer) of tetrapyrrolic systems. Such architectures included monomers, dyads, larger arrays, and complexes with accessory components. The objective was to develop molecular designs and guiding principles to enhance current and future energy-conversion schemes. Molecular arrays targeted to address one or more fundamental questions concerning light harvesting and energy/charge transfer were constructed from analogues of the naturally occurring hemes, chlorophylls and bacteriochlorophylls. Diverse, tunable synthetic building blocks were prepared that spanned the three respective tetrapyrrole families, which are the porphyrins, chlorins and bacteriochlorins. Thus, the research focused on porphyrins as well as synthetic surrogates for chlorophylls (chlorins, 13 1 -oxophorbines and chlorin-imides) and bacteriochlorophylls (bacteriochlorins, bacterio-13 1 -oxophorbines and bacteriochlorin-imides), generically termed hydroporphyrins. Although the three tetrapyrrole classes (porphyrins, chlorins and bacteriochlorins) absorb light strongly in the violet-blue spectral region, the long-wavelength absorption band typically lies in the green-orange, red, and NIR regions, respectively, with increasing intensity. Understanding the spectra, electronic structure, and energy/charge-transfer properties of such tetrapyrrolic macrocycles is of central importance for the rational design of molecular architectures for solar-energy conversion. Our integrated program of molecular design and synthesis coupled with a variety of spectroscopic, electrochemical, and computational studies have probed from first principles how structural and electronic properties of tetrapyrrolic macrocycles dictate spectral properties as well as the rates of ground-state hole/electron transfer and excited-state energy flow in multicomponent architectures. Individual molecules and multicomponent architectures were designed to test ideas of fundamental importance, often requiring the development of new synthetic methodology. The members of the collaborative team had almost daily discussions by phone and/or e-mail concerning design of molecules, flow of compounds between the labs, planning of physical characterization studies, discussing results and analysis and integrating into design of next generation architectures, and the preparation of manuscripts. Furthermore, students and postdocs in the different labs routinely communicated with one another to facilitate the advancement of the research activities. In short, a highly integrated and collaborative research program was well established among the groups. The research effort involved molecular design and synthesis of synthetic molecular architectures by the Lindsey group integrated with physicochemical and photophysical characterization by the Bocian group and the Holten&Kirmaier group (Figure 2). The Bocian group carried out electrochemical, electron paramagnetic resonance (EPR), resonance Raman (RR), and Fourier-transform infrared (FT-IR) studies, as well as density functional theory (DFT) calculations and the time-dependent extension (TDDFT) to gain insight into excited-state properties. The Holten&Kirmaier group carried out static and time-resolved absorption and fluorescence spectroscopy studies and simulated absorption spectra using molecular orbital (MO) energies from DFT as input to the four-orbital model to complement the TDDFT calculations. The combined measurements provided understanding of the vibrational/electronic properties of the individual molecules and the changes that occur upon incorporation into multicomponent architectures. This information underpinned elucidating the mechanisms and timescales of ground-state hole/electron transfer and excited-state energy and charge transfer.

14 SOLAR ENERGY↗

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗

Dependable classical-quantum computing systems engineering

Increasing evidence suggests quantum computing (QC) complements traditional High-Performance Computing (HPC) by leveraging its unique capabilities, leading to the emergence of a new, hybrid paradigm, QHPC. However, this integration introduces new challenges, with dependability–defined by reproducibility, resiliency, and security and privacy–emerging as a central concern for building trustworthy systems that provide an advantage to the users. This paper proposes a framework for dependable QHPC system design, organized around these three pillars. We identify integration challenges, anticipate roadblocks, and highlight productive synergies across QC, HPC, cloud platforms, and network security. Drawing from both classical computing principles and quantum-specific insights, we present a roadmap for co-design that supports robust hybrid architectures. Our approach offers concrete metrics for assessing dependability, provides design guidance for engineers working at the QC-HPC interface, and surfaces new engineering questions around complexity, scale, and fault tolerance. Ultimately, designing for dependability is key to realizing practical, scalable QHPC systems and accelerating the broader quantum ecosystem capable of translating quantum promises into actual application delivery.

HPC↗

Vibronic coupling in light-harvesting complex II revisited

A growing body of work has pointed to vibronic mixing as a crucial design principle for efficient energy and charge transfer in natural and artificial systems.= Notable among these studies was the recent observation of vibronically promoted ultrafast energy flow in the major antenna complex of green plants and algae light-harvesting complex II (LHCII)—the most abundant membrane protein on the Earth—via the emerging experimental technique two-dimensional electronic-vibrational (2DEV) spectroscopy. This spectroscopy, which correlates electronic and nuclear degrees-of-freedom, shows promise for providing mechanistic insight into vibronic coupling; however, explicit theoretical input is necessary to extract such a detail. In a separate paper, we have developed a heterodimer model that describes various forms of vibronic coupling—which were speculated to be present in LHCII—resulting from diagonal electron–phonon coupling giving Franck–Condon (FC) activity and the nuclear dependence of the electronic transition dipole moment giving Herzberg–Teller (HT) activity. Here, we draw connections between this theoretical work and recent experimental studies in order to demonstrate how HT activity is leveraged in the function of LHCII.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Human Factors Design for Particle Accelerator Control Room Interfaces

Fermilab, the birthplace of many scientific discoveries in physics and particle accelerator sciences, is in the midst of a widescale modernization effort. The Accelerator Control Operations Research Network (ACORN project’s goal is to modernize the accelerator control system by replacing end-of-life power supplies and enhance future operations of the Fermilab accelerator complex with megawatt particle beams. Within ACORN, opportunities for process improvement concerning software development, human-system interface design, and task performance are also being considered. Human factors researchers from Idaho National Laboratory in collaboration with usability experts from Fermilab, are currently investigating human-centered design improvements for the accelerator control system. For example, substantial tribal knowledge and memory recall are required to effectively operate the accelerator system. This contributes to high cognitive workload and potential burnout of accelerator operators. Developing guidance for consistent visual and functional design enables a more intuitive interaction and relieves operators of cognitive burden. Additionally, developing more intuitive and integrated interfaces can also lead to improved accelerator efficacy by empowering operators with greater understanding and control of the systems. The challenge in developing such interfaces is in designing for a wide variety of user goals, system specifications, and level of experience in users. The challenges need to be met while e also considering the maintainability of the control system. The purpose of this paper is to detail the human factors process and design within the ACORN project, describe results gathered thus far, and discuss the larger implications for this work.

43 PARTICLE ACCELERATORS↗

Exploiting Chemistry and Molecular Systems for Quantum Information Science

The power of chemistry to prepare new compositions of matter has driven the quest for new approaches to solve problems having global societal impact, such as renewable energy, healthcare, and information science. In the latter case, the intrinsic quantum nature of molecules offers intriguing new possibilities to advance the emerging field of Quantum Information Science (QIS). In this Perspective, we discuss how chemical systems and reactions can impact quantum computing, communication, and sensing. Hierarchical molecular design and synthesis, from small molecules to supramolecular assemblies, combined with new spectroscopic probes of quantum coherence and theoretical modeling of complex systems, offer a broad range of possibilities to realize practical QIS applications.

quantum computing, Spectrocopy, computational chem↗

Feasibility study of a compact neutron resonance transmission analysis instrument

Neutron Resonance Transmission Analysis (NRTA) uses resonant absorption of neutrons to infer the absolute isotopic composition of a target object, enabling applications in a broad range of fields such as archaeology, enrichment analysis of nuclear fuel, and arms control treaty verification. In the past, NRTA involved large user facilities and complex detector systems. However, recent advances in the intensity of compact neutron sources have made compact neutron imaging designs increasingly feasible. This work describes the Monte Carlo (MC) based design of a compact epithermal NRTA radiographic instrument which uses a moderated, compact deuterium-tritium (DT) neutron source and an epithermal neutron detector. Such an instrument would have a wide range of applications, and would be especially impactful for such scenarios as nuclear inspection and arms control verification exercises, where system complexity and mobility may be of critical importance. The MC simulations presented in this work demonstrate accurate time-of-flight (TOF) reconstructions for transmitted neutron energies, capable of differentiating isotopic compositions of nuclear material with high levels of accuracy. A new generation of miniaturized and increasingly more intense neutron sources will allow this technique to achieve measurements with greater precision and speed, with significant impact on a variety of engineering and societal problems.

47 OTHER INSTRUMENTATION↗

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Perspectives on novel refractory amorphous high-entropy alloys in extreme environments

Two new refractory amorphous high-entropy alloys (RAHEAs) within the W–Ta–Cr–V and W–Ta–Cr–V–Hf systems were herein synthesized using magnetron-sputtering and tested under high-temperature annealing and displacing irradiation using in situ Transmission Electron Microscopy. While the 14W-41Ta-26Cr-19V in at.% RAHEA (defined as WTaCrV RAHEA) was found to be unstable under such tests, additions of Hf in this system composing a new quinary 24W-40Ta-18Cr-5V-13Hf in at.% RAHEA (defined as WTaCrVHf RAHEA) was found to be a route to achieve stability both under annealing and irradiation. A new effect of nanoprecipitate reassembling observed to take place within the WTaCrVHf RAHEA under irradiation indicates that a duplex microstructure composed of an amorphous matrix with crystalline nanometer-sized precipitates enhances the radiation response of the system. Further, it is demonstrated that tunable chemical complexity arises as a new alloy design strategy to foster the use of novel RAHEAs within extreme environments. New perspectives for the alloy design and application of chemically-complex amorphous metallic alloys in extreme environments are presented with focus on their thermodynamic phase stability when subjected to high-temperature annealing and displacing irradiation.

36 MATERIALS SCIENCE↗

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗

AI-Constrained Bottom-Up Ecohydrology and Improved Prediction of Seasonal, Interannual, and Decadal Flood and Drought Risks

Focal Areas: (2) Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system composed of a hierarchy of models (3)Insight gleaned from complex data (both observed & simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI

54 ENVIRONMENTAL SCIENCES↗

Improve wildfire predictability driven by extreme water cycle with interpretable physically-guided ML/AI

Focal Area(s): Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models (Primary); insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics or knowledge-guided AI (Secondary). Science Challenge: Wildfires modify land surface characteristics, such as vegetation composition, soil and litter carbon stocks, and surface albedo, with significant consequences for the regional carbon cycle. For example, tropical regions (i.e., African and South America) are particularly vulnerable to wildfire, account for more than 80% of the global burned area, and emit ~1.4 PgC y -1 into the atmosphere together with other dust and aerosols that strongly affect regional climate.

54 ENVIRONMENTAL SCIENCES↗

Demonstration of a Continuous Motion Direct Air Capture System

Global Thermostat (GT) has developed a process that addresses the primary technical challenges associated with direct air capture (DAC): the ability to process enormous volumetric flowrates of air and provide the energy for regeneration at acceptable cost. However, at current, there is opportunity for improvement in overall capture costs and especially in capital costs. While GT has advanced its base technology to TRL levels supporting commercial deployments, its research strategy includes alternative technology embodiments that enable substantial reductions in the cost per tonne of CO 2 removed. The objective of this project is to advance the most promising of these embodiments, where a DAC plant is operated in a continuous fashion rather than a discrete stepwise fashion (GT’s commercial scale technology approach). The Continuous Motion Direct Air Capture (cDAC) System’s advantages over the GT baseline stepwise DAC platform have been proposed primarily as a reduction in the complexity required for starting and stopping a movement system, relaxing requirements for other components designed for a rapid switching application, and a flattening of the sharp instantaneous fluid flowrates into steady-state mass & energy flows to enable smoother operation and easier heat integration. These advantages can lead to shorter cycle times, greater plant reliability, and lower capital expense. The primary objective of this project is the design, construction, commissioning, and operation of a field-test unit (FTU) at a scale in the range of ~200 tons CO 2 per year. Data generated from the operation campaign would then be used in a prescreening techno-economic analysis (TEA) and life cycle analysis (LCA), allowing this process to be compared to other carbon capture technologies.

42 ENGINEERING↗