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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 685 records · Page 38

Strategies for design and synthesis of porous liquids toward carbon capture and separation

Porous liquids (PLs) represent a promising category of sorbents in carbon capture and separation capable of integrating the advantages of flowing liquid and porous solid systems. Well-defined pores were engineered into liquid sorbents via liquifying molecules with stiff interior voids, dissolving rigid porous hosts in flowing liquids, or dispersing porous frameworks in high steric hindrance solvents, producing type I, II, or III PLs, respectively. Unique features of PLs have triggered broad interest in exploring their applications in carbon capture and separation, in which diverse design strategies, synthesis approaches, and enhanced performance have been reported. Here, in this minireview, recent progress in the design, synthesis, and structural engineering of PLs and efforts towards the optimization of their carbon capture and separation behavior will be summarized, including the comparison between PLs with varied types. Porosity engineering into liquid sorbents provides opportunities to resolve challenging issues in conventional sorption and separation systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Green chemistry design in polymers derived from lignin: review and perspective

The use of lignin for material and chemical applications has gained interest in recent times due to the environmental focus on using biomass for renewable materials as well as the motivation to valorize lignin as part of an integrated biorefinery. While a wealth of publications can be found for lignin-derived materials, and several reviews can be found on the topic, there are no reviews that outline and critically assess the sustainability of these protocols based on the criterion of the 12 Principles of Green Chemistry. This review assesses the literature for lignin- derived polymers over the past 20 years and highlights attempts to use biobased accompanying reagents, green solvents or solvent-less protocols, reports that replace traditionally toxic precursors (e.g. diisocyanates for polyurethanes), use mild conditions, valorize additional waste streams and prepare materials particularly biodegradable or recyclable. Here, the following work is a comprehensive and critical assessment of the green and sustainable nature of the state-of-the art of lignin-derived polymers (polyurethane, polyester, epoxy, phenolic resin, and others) utilizing actual biomass in the synthetic protocol. Each section of this review highlights and assesses published protocols that use a particularly green approach in one or more steps of the synthetic sequence. While many reports still contain traditional petroleum-derived and toxic methods along with more sustainable methods, the outline of all such green methods is able to create a landscape amidst lignin-derived polymer synthesis that points the way toward safer and more environmentally friendly materials.

36 MATERIALS SCIENCE↗

Tracking ion intercalation into layered Ti 3 C 2 MXene films across length scales

Enhancing the energy stored and power delivered by layered materials relies strongly on improved understanding of the intricate interplay of electrolyte ions, solvents, and electrode interactions as well as the role of confinement. Here we report a highly integrated study with multiscale theory/modelling and experiments to track the intercalation of aqueous Li + , Na + , K + , Cs + , and Mg 2+ ions into Ti 3 C 2 MXene. The integrated analysis of experiments assisted by theory/modelling allows for a deep understanding of energy storage processes highlighting the importance of the dynamics of cations, their positionings between MXene sheets, their effects on mechanical properties and capacitive energy storage. Computational simulations and operando calorimetry measurements prove the processes involving cation dehydration and H+ rehydration, showing a good correlation for heat variations between experiments and theory. Operando liquid AFM mapped energy dissipation of ions appears non-uniformly across the MXene surface, indicating heterogeneities of ions inside the MXene and confirming partially the ion behaviour obtained in theory. We directly demonstrate that the average distance between the cation and MXene surface follows a modified two-sided Helmholtz model when plotted versus the open circuit potential capacitance, revealing a different electrical double layer mechanism in confinement. This new fundamental understanding lays the foundation for improved functional devices utilizing electrodes and membranes made of two-dimensional materials.

36 MATERIALS SCIENCE↗

ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field

We have implemented the Martini force field within Lawrence Livermore National Laboratory’s molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition to the Martini force field being ported to the GPU, the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core. A benchmark study is performed with several test cases, comparing ddcMD and GROMACS Martini simulations. The average performance of ddcMD for a protein–lipid simulation system of 136k particles achieves 1.04 µs/day on one NVIDIA V100 GPU and aggregates 6.19 µs/day on one Summit node with six GPUs. The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shared governance in the plant holobiont and implications for one health

Abstract The holobiont Holobiont theory is more than 80 years old, while the importance of microbial communities for plant holobionts was already identified by Lorenz Hiltner more than a century ago. Both concepts are strongly supported by results from the new field of microbiome research. Here, we present ecological and genetic features of the plant holobiont that underpin principles of a shared governance between hosts and microbes and summarize the relevance of plant holobionts in the context of global change. Moreover, we uncover knowledge gaps that arise when integrating plant holobionts in the broader perspective of the holobiome as well as one and planetary health concepts. Action is needed to consider interacting holobionts at the holobiome scale, for prediction and control of microbiome function to improve human and environmental health outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

The challenges of detecting and attributing ocean acidification impacts on marine ecosystems

Abstract A substantial body of research now exists demonstrating sensitivities of marine organisms to ocean acidification (OA) in laboratory settings. However, corresponding in situ observations of marine species or ecosystem changes that can be unequivocally attributed to anthropogenic OA are limited. Challenges remain in detecting and attributing OA effects in nature, in part because multiple environmental changes are co-occurring with OA, all of which have the potential to influence marine ecosystem responses. Furthermore, the change in ocean pH since the industrial revolution is small relative to the natural variability within many systems, making it difficult to detect, and in some cases, has yet to cross physiological thresholds. The small number of studies that clearly document OA impacts in nature cannot be interpreted as a lack of larger-scale attributable impacts at the present time or in the future but highlights the need for innovative research approaches and analyses. We summarize the general findings in four relatively well-studied marine groups (seagrasses, pteropods, oysters, and coral reefs) and integrate overarching themes to highlight the challenges involved in detecting and attributing the effects of OA in natural environments. We then discuss four potential strategies to better evaluate and attribute OA impacts on species and ecosystems. First, we highlight the need for work quantifying the anthropogenic input of CO2 in coastal and open-ocean waters to understand how this increase in CO2 interacts with other physical and chemical factors to drive organismal conditions. Second, understanding OA-induced changes in population-level demography, potentially increased sensitivities in certain life stages, and how these effects scale to ecosystem-level processes (e.g. community metabolism) will improve our ability to attribute impacts to OA among co-varying parameters. Third, there is a great need to understand the potential modulation of OA impacts through the interplay of ecology and evolution (eco–evo dynamics). Lastly, further research efforts designed to detect, quantify, and project the effects of OA on marine organisms and ecosystems utilizing a comparative approach with long-term data sets will also provide critical information for informing the management of marine ecosystems.

Fisheries↗

Ab initio leading order effective potentials for elastic nucleon-nucleus scattering

Calculating microscopic effective interactions (optical potentials) for elastic nucleon-nucleus scattering has already in the past led to a large body of work. For first-order calculations a nucleon-nucleon ( NN ) interaction and a one-body density of the nucleus were taken as input to rigorous calculations of microscopic full-folding calculations. Based on the spectator expansion of the multiple scattering series we employ a chiral next-to-next-to-leading order (NNLO) nucleon-nucleon interaction on the same footing in the structure as well as in the reaction calculation to obtai n an in leading-order consistent effective potential for nucleon-nucleus elastic scattering, which includes the spin of the struck target nucleon. The first order effective folding potential is computed by first deriving a nonlocal scalar density as well as a spin-projected momentum distribution. Those are then integrated with the off-shell Wolfenstein amplitudes $A$, $C$, and $M $. The resulting nonlocal potential serves as input to a momentum-space Lippmann-Schwinger equation, whose solutions are summed to obtain the nucleon-nucleus scattering observables. As a result, we calculate elastic scattering observables for $^4$He, $^6$He, $^8$He, $^{12}$C, and $^{16}$O in the energy r egime between 100 and 200~MeV projectile kinetic energy, and compare to available data. We also explore the extension down to about 70 MeV, and study the effect of ignoring the spin of the struck nucleon in the In our calculations we contrast elastic scattering off closed-shell and open-shell nuclei. We find that fo r closed-shell nuclei the approximation of ignoring the spin of the struck target nucleon is excellent. We only see effects of the spin of the struck target nucleon when considering $^6$He and $^8$He, which are nuclei with a $N/Z$ ratio larger than 1.

6 ≤ A ≤ 19↗

A Radiation-Hard 8-Channel 15-Bit 40-MSPS ADC for the ATLAS Liquid Argon Calorimeter Readout

The custom design of a radiation-hardened, 8-channel, 40-MSPS, 15-bit resolution, 14.2-bit dynamic range, 11.4-ENOB ADC data acquisition ASIC fabricated in a commercial 65-nm triple-well CMOS technology is presented. The ADC is developed for and integrates seamlessly into the readout system for the ATLAS liquid argon (LAr) calorimeter in the high-luminosity large hadron collider (HLLHC) upgrade at CERN, which will require a total of 364 936 ADC channels. A three-stage MDAC+SAR pipelined ADC architecture was designed to meet the physics requirements and scientific goals of the ATLAS experiment. The ADC is a fully self-contained data acquisition system that includes foreground calibration, digital data processing, digital control, and supporting circuitry. The measured performance shows the ADC achieves a competitive dynamic range and SNDR, and it meets or exceeds the ATLAS analog requirements. Radiation tolerance and scalability design considerations were implemented at the device-, circuit-, and system-level. Radiation-hardening-by-design techniques used include redundancy for digital circuits, the use of MiM capacitors, and a hybrid RC-DAC for the ADC core. The ADC ASIC was demonstrated to be robust against the effects of the intense radiation expected in the HL-LHC experimental environment.

DAQ↗

The essential Rhodobacter sphaeroides CenKR two-component system regulates cell division and envelope biosynthesis

Bacterial two-component systems (TCSs) often function through the detection of an extracytoplasmic stimulus and the transduction of a signal by a transmembrane sensory histidine kinase. This kinase then initiates a series of reversible phosphorylation modifications to regulate the activity of a cognate, cytoplasmic response regulator as a transcription factor. Several TCSs have been implicated in the regulation of cell cycle dynamics, cell envelope integrity, or cell wall development in Escherichia coli and other well-studied Gram-negative model organisms. However, many α-proteobacteria lack homologs to these regulators, so an understanding of how α-proteobacteria orchestrate extracytoplasmic events is lacking. In this work we identify an essential TCS, CenKR ( C ell en velope K inase and R egulator), in the α-proteobacterium Rhodobacter sphaeroides and show that modulation of its activity results in major morphological changes. Using genetic and biochemical approaches, we dissect the requirements for the phosphotransfer event between CenK and CenR, use this information to manipulate the activity of this TCS in vivo , and identify genes that are directly and indirectly controlled by CenKR in Rb . sphaeroides . Combining ChIP-seq and RNA-seq, we show that the CenKR TCS plays a direct role in maintenance of the cell envelope, regulates the expression of subunits of the Tol-Pal outer membrane division complex, and indirectly modulates the expression of peptidoglycan biosynthetic genes. CenKR represents the first TCS reported to directly control the expression of Tol-Pal machinery genes in Gram-negative bacteria, and we predict that homologs of this TCS serve a similar function in other closely related organisms. We propose that Rb . sphaeroides genes of unknown function that are directly regulated by CenKR play unknown roles in cell envelope biosynthesis, assembly, and/or remodeling in this and other α-proteobacteria.

Lakey, Bryan D. (ORCID:0000000332795242)↗

Open string stub as an auxiliary string field

Witten’s open string field theory with a generalized version of stubs is reformulated as a cubic string field theory using an auxiliary string field. The gauge symmetries and equations of motion as well as the associative algebra of the resulting theory are investigated. Integrating out either the original or auxiliary field is shown to recover the conventional cubic theory. Our analysis demonstrates that deformations due to the stubs can be described as a homotopy transfer purely in the context of strong deformation retract. We also discuss to what extent the vertex regions resulting from stubs provide a model for the elementary interactions of closed string field theory.

Physics↗

Bryan Mound Abandoned Cavern 3 Stability Analysis - 2021 Review

The U.S. Strategic Petroleum Reserve is moving towards employing an expanded enhanced monitoring program. In doing so it has become apparent that there is a need for a better project wide understanding of the current state of Bryan Mound abandoned Cavern 3 stability. Cavern 3 has been inaccessible since 1988 when it was plugged and abandoned and thus this comprehensive report is structured by focusing on 1) a summarization of what can be discerned from historical records prior to 1988 and 2) a presentation and discussion of our current understanding of Cavern 3 based solely on surface monitoring and geomechanical analyses. Historical literature state the cavern was deemed unsuitable for oil storage, as it could not be definitively determined if fluid pressure could be maintained in the borehole. Current surface monitoring indicates the largest surface subsidence rates are occurring above Cavern 3. The subsidence rates are linear with no evidence of acceleration. Cavern collapse could occur if there is insufficient pressure holding up the roof. Next steps are to implement a microseismic system that will lend to a better understanding of cavern stability, as well as provide an improved early warning system for loss of integrity.

02 PETROLEUM↗

Cloud Droplet Measurement System for the ARM Tethered Balloon System (TBS) Field Campaign Report

The Mesa Photonics' cloud droplet measurement system (CDMS) performs in situ measurement of droplet size distribution and droplet number density in clouds. These characteristics are important cloud microphysical properties that are critical input parameters for atmospheric models and are also useful for proper calibration and validation of performance of other atmospheric measurement instrumentation. This small campaign was the first project (out of two) that involved integration of the CDMS into the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s tethered balloon system (TBS) and its initial testing at the ARM Southern Great Plains (SGP) atmospheric observatory. The follow-up campaign (AFC07016) involved testing of the CDMS under relevant conditions at the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska and making in situ measurements in clouds. The goal of this small field campaign was to deploy the CDMS on the ARM TBS, demonstrate its integrity and compatibility with the TBS, and test the wireless telecommunication system in preparation for subsequent in-cloud measurements at ARM’s North Slope of Alaska (NSA) observatory at Utqiagvik (formerly Barrow). The specific technical objectives included: (1) Integration of the Mesa Photonics' CDMS into the ARM TBS, (2) testing of the wireless telecommunication system of the CDMS, (3) evaluating the data acquisition software and image processing algorithms especially under high-background-illumination conditions, and (4) testing the ruggedness of the instrument's optical alignment and other performance characteristics. All objectives have been successfully met. The mounting hardware was designed and built mostly at Sandia National Laboratories (SNL), which allowed reliable mounting of the CDMS on the TBS and co-locating the CDMS with other instruments. The field tests were performed by the principal investigator (PI) in collaboration with the TBS operational crew led by D. Dexheimer. The field testing demonstrated good compatibility of the CDMS with the TBS. During the TBS flights, the crew did not experience any operational issues with the CDMS. The instrument demonstrated reliable operational characteristics, including sufficient battery life and good thermal management. The wireless telecommunication system has been successfully tested at TBS flight altitudes of up to 1000 m. During all flights, the CDMS raw data were wirelessly transmitted to the ground station and processed in real time. The ruggedness of the instrument's optical alignment was evaluated by performing calibration of the CDMS (using Mesa Photonics' fixed-size monodisperse droplet generator) before and after the campaign. The calibration was stable within the instrument's measurement precision. In summary, the campaign demonstrated good compatibility of the Mesa Photonics' CDMS with the ARM TBS. The flight tests confirmed the mechanical integrity of the CDMS and stability of its optical layout, as well as reliability of the wireless telecommunication system. Successful completion of this campaign provided a solid basis for the next campaign (AFC07016, November 2020), that involved testing of the CDMS during in-cloud TBS flights at AMF3 at Oliktok Point.

54 ENVIRONMENTAL SCIENCES↗

2025 Workshop on Envisioning Frontiers in AI and Computing for Biological Research: Position Papers

This workshop aims to identify key research directions for transforming biology using artificial intelligence (AI), machine learning (ML) and computational methods to facilitate the discovery of new behaviors, mechanisms, and designs of biological processes relevant to DOE missions, underpinning a broader U.S. bioeconomy. By developing novel AI/ML technologies to analyze and interpret complex biological data, researchers can organize and simulate biological processes at various scales as well as advance predictive understanding and manipulation of biological systems. This integration of computation, experimentation, and next-generation experimental technologies can lead to discoveries in new biological behaviors and mechanisms relevant to DOE missions. The focus is on how advanced computational and mathematical methods can impact this mission by exploring digital twins, foundation models, automated laboratory experiments, modeling of complex living systems, and data-driven approaches for the biodesign of plants and microbial systems. While data management is important, it is not the primary focus of this workshop, which will assess the current state, trends, and AI/ML challenges at the interface between biology and computational science to identify opportunities for high-impact research at their intersection. The goal is to define research needs and opportunities that align with biological sciences, computational sciences, and applied mathematics research.

59 BASIC BIOLOGICAL SCIENCES↗

CSAC observations from 2025 CHEDAR review [Slides]

Overall, the CSAC is impressed by the strong start of CHEDAR, a multi-institutional center with broader scope than its predecessor. The CSAC was impressed and energized by discussions with center students and staff; the enthusiasm for science is universal and the sense of the contribution in context to the NNSA mission is mostly understood. The Center is well positioned to build on a strong start and (1) enhance integration of code-development targeted to, and numerical design in on-going experimental campaigns, (2) focus and better tell the story of the astrophysical connection for on-going experimental campaigns, and (3) expand and deepen ties between Center students (and faculty) and the NNSA National Laboratories. Overall, the CSAC was encouraged and energized by the materials presented. Now, the Center has to recognize the need to continue growing strategically. There is abundant access to experimental facilities – is that a challenge to focused effort? The PIs will need to balance the pace of experimental campaigns and analysis and simulation so that informed progress and focused investigation can develop in each campaign. There was a clear need to connect simulations to the goals of experimental campaigns – what is the best way to cultivate that connection? Are there adequate resources in the near term to develop code capability? What is the balance between close personal mentorship and collaboration across the separate institutions that compose the Center? The CSAC feels confident that the team leading CHEDAR will find creative solution to these challenges.

47 OTHER INSTRUMENTATION↗

Robust Decentralized Secondary Control Scheme for Inverter-based Power Networks

Inverter-dominated microgrids are quickly becoming a key building block of future power systems. They rely on centralized controllers that can provide reliability and resiliency in extreme events. Nonetheless, communication failures due to cyber-physical attacks or natural disasters can make autonomous operation of islanded microgrids challenging. This paper examines a unified decentralized secondary control scheme that is robust to inverter clock synchronization errors and can be seamlessly applied to grid-following or grid-forming control architectures. The proposed scheme overcomes the well-known stability problem that arises from parallel operation of local integral controllers. Theoretical guarantees for stability are provided along with criteria to appropriately tune the secondary control gains to achieve good frequency regulation performance while ensuring fair power sharing. The efficacy of our approach is demonstrated through simulations on a 5-bus microgrid with four grid-forming inverters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Flexible Magnetic Polymer Composite Substrate with Ba 1.5 Sr 1.5 Z Hexaferrite Particles of VHF/Low UHF Patch Antennas for UAVs and Medical Implant Devices

Our goal is to fabricate flexible magnetic polymer composites as antenna substrates for very high frequency (VHF)/low ultra high frequency (UHF) antennas for unmanned aerial vehicles (UAVs) and medical devices. Magnetodielectric materials, which have permeability (μ) similar to permittivity (ε), have attracted great attention, because they facilitate miniaturization of microwave devices while keeping or enhancing electromagnetic characteristics. Mechanically millled Ba 1.5 Sr 1.5 Co 2 Fe 24 O 41 (Ba 1.5 Sr 1.5 Z) hexaferrite particles were used to increase permeability in the interesting frequency band. The microwave properties of Ba 1.5 Sr 1.5 Z composites were predicted and measured. Hansen’s zero-order analysis of antenna bandwidth and electromagnetic field simulation showed that the hexaferrite-based flexible composite could enhance a bandwidth and achieve the miniaturization of antennas as well. The magnetic antenna substrates can be a good solution to integrate antennas into the UAVs whose dimensions are comparable to or larger than communication wavelength.

36 MATERIALS SCIENCE↗

HPC at NREL: FY 2019

Brochure featuring Fiscal Year 2019 accomplishments at the NREL High-Performance Computing User Facility and Data Center at the Energy Systems Integration Facility, including information on the facility's HPC systems as well as highlights from several modeling and simulation projects across the spectrum of energy efficiency and renewable energy technologies.

97 MATHEMATICS AND COMPUTING↗

Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models

Recent progress in scientific machine learning (SciML) has opened up the possibility of training novel neural network architectures that solve complex partial differential equations (PDEs). Several (nearly data free) approaches have been recently reported that successfully solve PDEs, with examples including deep feed forward networks, generative networks, and deep encoder-decoder networks. However, practical adoption of these approaches is limited by the difficulty in training these models, especially to make predictions at large output resolutions (≥1024×1024). Here we report on a software framework for data parallel distributed deep learning that resolves the twin challenges of training these large SciML models - training in reasonable time as well as distributing the storage requirements. Our framework provides several out of the box functionality including (a) loss integrity independent of number of processes, (b) synchronized batch normalization, and (c) distributed higher-order optimization methods. We show excellent scalability of this framework on both cloud as well as HPC clusters, and report on the interplay between bandwidth, network topology and bare metal vs cloud. We deploy this approach to train generative models of sizes hitherto not possible, showing that neural PDE solvers can be viably trained for practical applications. We also demonstrate that distributed higher-order optimization methods are 2-3× faster than stochastic gradient-based methods and provide minimal convergence drift with higher batch-size.

PDEs↗