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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sequential Doping of Ladder-Type Conjugated Polymers for Thermally Stable n-Type Organic Conductors

Doping of organic semiconductors is a powerful tool to optimize the performance of various organic (opto)electronic and bioelectronic devices. Despite recent advances, the low thermal stability of the electronic properties of doped polymers still represents a significant obstacle to implementing these materials into practical applications. Hence, the development of conducting doped polymers with excellent long-term stability at elevated temperatures is highly desirable. Here, we report on the sequential doping of the ladder-type polymer poly(benzimidazobenzophenanthroline) (BBL) with a benzimidazole-based dopant (i.e., N-DMBI). By combining electrical, UV–vis/infrared, X-ray diffraction, and electron paramagnetic resonance measurements, we quantitatively characterized the conductivity, Seebeck coefficient, spin density, and microstructure of the sequentially doped polymer films as a function of the thermal annealing temperature. Importantly, we observed that the electrical conductivity of N-DMBI-doped BBL remains unchanged even after 20 h of heating at 190 °C. This finding is remarkable and of particular interest for organic thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding the Influence of Water-Soluble Compounds from Unpretreated Corn Stover Pellets on Enzymatic Hydrolysis of Cellulose

Aqueous extractives are minor and non-structural compounds in biomass that can be extracted using solvents, while contributing significantly to lignocellulose characteristics. Yet their roles in enzyme-mediated processing of lignocellulosic biomass remain elusive. Here, we examine the composition and features of extractives derived from untreated pelleted corn stover as well as their effects on enzymatic hydrolysis. Unlike the observations described in previous reports, we find that water extractable material improves the enzymatic hydrolysis of extractive-free stover by 67% with a glucose yield increase from 12% to 20% with 6 FPU cellulase per g glucan, whereas the enzyme activities are diminished when using microcrystalline cellulose as a substrate. The different behavior of corn stover and microcrystalline cellulose is likely attributed to the presence of lignin, which may interact with inhibitory compounds such as phenolics, mitigating the detrimental impacts of soluble inhibitors or insoluble lignin or both. These findings advance our fundamental understanding of the intrinsic behavior of extractives and help to optimize the schemes for efficient and cost-competitive enzymatic conversion of lignocellulose.

09 BIOMASS FUELS↗
DOE OSTI2024

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Electron-nuclear decoupling at a spin clock transition

The ability to design quantum systems that decouple from environmental noise sources is highly desirable for development of quantum technologies with optimal coherence. The chemical tunability of electronic states in magnetic molecules combined with advanced electron spin resonance techniques provides excellent opportunities to address this problem. Indeed, so-called clock transitions have been shown to protect molecular spin qubits from magnetic noise, giving rise to significantly enhanced coherence. Here we conduct a spectroscopic and computational investigation of this physics, focusing on the role of the nuclear bath. Away from the clock transition, linear coupling to the nuclear degrees of freedom causes a modulation and decay of electronic coherence, as quantified via electron spin echo signals generated experimentally and in silico. Meanwhile, the effective hyperfine interaction vanishes at the clock transition, resulting in electron-nuclear decoupling and an absence of quantum information leakage to the nuclear bath, providing opportunities to characterize other decoherence sources.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Catalytic conversion of cellulose and its derived sugars to 5-Hydroxymethylfurfural, levulinate esters, and sorbitol: a comprehensive review

Cellulose, an abundant, renewable, and sustainable non-edible carbon source from agriculture and forestry, has attracted great attention for producing diverse value-added chemicals and fuels. However, the rigid 3D structure of cellulose, maintained by an extensive hydrogen bonding network, hinders chemical conversion, requiring effective pretreatment to break down the crystalline structure. High-value cellulose-derived compounds such as 5-hydroxymethylfurfural (5-HMF), levulinate esters, and sorbitol, recognized as critical platform chemicals by the U.S. Department of Energy, are particularly attractive for versatile applications. This review provides a comprehensive overview of methodologies for the chemical synthesis of 5-HMF, levulinate esters, and sorbitol, focusing on direct catalytic conversion of cellulose. It delves into recent advancements in reaction systems and catalysts, highlighting catalytic pathways, selectivity, strategies for process optimization, and computational approaches, while discussing the challenges associated with the catalytic conversion of cellulose into these high-value products and offering potential strategies for enhancing future catalytic processes.

Huang, Kaixuan [Yancheng Teachers Univ. (China); N↗
DOE OSTI2022

Valorization of bamboo biomass using combinatorial pretreatments

Current studies concerning liquid hot water pretreatment (LHWP) usually focus on cellulose saccharification or hemicellulose conversion, while the appropriate extraction and utilization of LHWP-induced lignin have not been addressed. To valorize whole biomass, here, in this study, a series of LHWP-based combinatorial pretreatments are proposed using advanced solvent systems. The first LHWP stage removed 73.74% of xylan at the optimized pretreatment severity (~4.0), at the same time preserving almost all the cellulose and lignin. As a result, 9.04 g L –1 xylo-oligosaccharides (XOSs) were obtained in the prehydrolyzate, representing 63.31% of the degraded xylan. The LHWP also caused the migration and partial degradation of the lignin which benefits the delignification in the second stage of pretreatment utilizing NaOH, deep eutectic solvent (DES) and 1,4-butanediol (BDO) under relatively mild conditions. The proposed combinatorial pretreatment significantly enhanced glucan conversion. The physiochemical structural properties of the untreated and pretreated substrates were investigated with XRD, FTIR, GPC, SEM, and Simons’ staining to understand the mechanisms of different combinatorial pretreatments for overcoming biomass recalcitrance and facilitating integrated biomass valorization. Finally, the physical and chemical properties of the regenerated lignins were analyzed. The results revealed that lignins from LHWP–NaOH pretreatment preserved most of the native β-O-4 structure (37.1%). Thus it could be used as an ideal method for the catalytic production of aromatic monomers. On the other hand, LHWP–DES pretreatment generated lignins with low molecular weight and high phenolic OH content, which is promising for synthesizing resins and antioxidants. In conclusion, the proposed combinatorial pretreatment established a reliable sequential pretreatment methodology for maximizing the output of bamboo biomass and may fit into different biorefinery configurations for various value-added products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fundamental advantages of multijunction thermoradiative cells

Thermoradiative (TR) cells convert heat to work through emission of thermal radiation. Multijunction thermoradiative cells have received little research interest due to the apparent overlap with energy harvesting limits. Through detailed balance formalism, the present study models both single- and multi-diode TR devices, establishing their performance limits and identifying key factors that influence efficiency. For single-junction TR cells, we derive a relationship for the optimal bandgap and show that higher emitter temperatures increase efficiency. When the receiver is at absolute zero temperature, multijunction TR cells have little advantage over the single-junction cell in terms of the maximum output power density. However, for higher receiver temperatures, the multijunction configuration demonstrates significant improvements in both power and efficiency through the optimization of the chemical potential and bandgap of each diode in the complete ensemble. A 500 K emitter and 300 K receiver TR system can achieve a 21.25% increase in efficiency and a 10% improvement in the power density with multijunction architecture compared to a single junction through chemical potential optimization. These findings suggest that multijunction TR cells offer a promising approach to advancing low-grade heat recovery technologies for efficient heat-to-work conversion.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2015

Advances in refrigeration and heat transfer engineering

This special edition of Science and Technology for the Built Environment (STBE) presents selected high quality papers that were presented at the 15th International Refrigeration and Air Conditioning Conference held at Purdue University during July 14-17 2014. All papers went through the additional review before being finally accepted for publication in this special issue of Science and Technology and the Built Environment. Altogether 20 papers made to this special issue that cover a wide range of topics, including advancements in alternative refrigerants, heat exchangers/heat transfer, nano-fluids, systems design and optimization and modeling approaches. Although CO 2 may perhaps have been the most researched and popular refrigerant in the past decade, R32 is being seriously considered lately as an alternative and environmentally friendly refrigerant for small systems due to its low Global Warming Potential (GWP).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Magnetic configuration scans during divertor operation of Wendelstein 7-X

Wendelstein 7-X (W7-X) (Greifswald, Germany) is an advanced stellarator, which uses the modular coil concept to realize a magnetic configuration optimized for fusion-relevant plasma properties. The magnet system of the machine allows a variation of the rotational transform (iota) at the boundary. In the latest W7-X operational phase a dedicated configuration scan has been performed varying the rotational transform between magnetic configurations with iota = 5/4 and iota = 5/5 at the boundary. This paper presents an overview of the experiments and of the main results with respect to confinement and stability. The main observation is an increase of the plasma energy in several intermediate configurations of the scan when the 5/5-islands are close to the plasma boundary but still inside the last-closed-flux-surface. In addition, these configurations showed marked MHD-activity with a crashing behavior related to the 5/5-islands. The corresponding mode amplitude was correlated with the size of the internal 5/5 islands.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Optimization of a phase-space beam position and size monitor for low-emittance light sources

The recently developed vertical phase-space beam position and size monitor (ps-BPM) system has proven to be able to measure the electron-source position, angle, size and divergence simultaneously in the vertical plane at a single location of a beamline. The optimization of the ps-BPM system is performed by ray-tracing simulation to maximize the instrument sensitivity and resolution. The contribution of each element is studied, including the monochromator, the K -edge filter, the detector and the source-to-detector distance. An optimized system is proposed for diffraction-limited storage rings, such as the Advanced Photon Source Upgrade project. The simulation results show that the ps-BPM system can precisely monitor the source position and angle at high speed. Precise measurements of the source size and divergence will require adequate resolution with relatively longer integration time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

SU-D-207A-04: Use of Gradient Echo Plural Contrast Imaging (GEPCI) in MR-Guided Radiation Therapy: A Feasibility Study Targeting Brain Treatment

Purpose: To implement the Gradient Echo Plural Contrast Imaging(GEPCI) technique in MRI-simulation for radiation therapy and assess the feasibility of using GEPCI images with advanced inhomogeneity correction in MRI-guided radiotherapy for brain treatment. Methods: An optimized multigradient-echo GRE sequence (TR=50ms;TE1=4ms;delta-TE=4ms;flip angle=300,11 Echoes) was developed to generate both structural (T1w and T2*w) and functional MRIs (field and susceptibility maps) from a single acquisition. One healthy subject (Subject1) and one post-surgical brain cancer patient (Subject2) were scanned on a Philips Ingenia 1.5T MRI used for radiation therapy simulation. Another healthy subject (Subject3) was scanned on a 0.35T MRI-guided radiotherapy (MR-IGRT) system (ViewRay). A voxel spread function (VSF) was used to correct the B0 inhomogeneities caused by surgical cavities and edema for Subject2. GEPCI images and standard radiotherapy planning MRIs for this patient were compared focusing the delineation of radiotherapy target region. Results: GEPCI brain images were successfully derived from all three subjects with scan times of <7 minutes. The images derived for Subjects1&2 demonstrated that GEPCI can be applied and combined into radiotherapy MRI simulation. Despite low field, T1-weighted and R2* images were successfully reconstructed for Subject3 and were satisfactory for contour and target delineation. The R2* distribution of grey matter (center=12,FWHM=4.5) and white matter (center=14.6, FWHM=2) demonstrated the feasibility for tissue segmentation and quantification. The voxel spread function(VSF) corrected surgical site related inhomogeneities for Subject2. R2* and quantitative susceptibility map(QSM) images for Subject2 can be used to quantitatively assess the brain structure response to radiation over the treatment course. Conclusion: We implemented the GEPCI technique in MRI-simulation and in MR-IGRT system for radiation therapy. The images demonstrated that it is feasible to adopt this technique in radiotherapy for structural delineation. The preliminary data also enable the opportunity for quantitative assessment of radiation response of the target region and normal tissue.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Performance Impact and Trade-Offs for Tuning Key Architectural Parameters on CPU+GPU Systems

In this work, we performed an initial design space exploration of an accelerated processing unit (APU)—a hybrid CPU+GPU architecture that integrates both compute units (CUs) and memory into a unified system. This integration aims to reduce data movement, enhance memory locality, and improve energy efficiency by enabling the CPU and GPU to share memory directly. This effort focused on the interplay of key design components—cache line size, the number of CUs, and main memory technology—and the trade-offs of each configuration were analyzed. This paper highlights the various configurations’ impact on memory accesses, data reuse, and power utilization. The results provide valuable insights that can be leveraged to optimize APU architectures for high-performance and energy-efficient computing and thus create a balanced architecture. This optimization can be achieved by adopting dynamic cache management, runtime CU scaling, and advanced memory integration, highlighting the potential of APUs to address critical challenges in compute, data movement, and memory power consumption.

Asifuzzaman, Kazi [ORNL] (ORCID:0000000240044791)↗
DOE OSTI2023

A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

Kusmec, Aaron (ORCID:000000032295385X)↗
DOE OSTI2016

Development of Advanced High Uranium Density Fuels for Light Water Reactors

This work conducts basic materials research (fabrication, radiation resistance, thermal conductivity, and corrosion response) on U3Si2 and UN, two high uranium density fuel forms that have a high potential for success as advanced light water reactor (LWR) fuels. The outcome of this proposed work will serve as the basis for the development of advance LWR fuels, and utilization of such fuel forms can lead to the optimization of the fuel performance related plant operating limits such as power density, power ramp rate and cycle length.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

OpenSNAPI: Toward a Unified API for SmartNICs

The end of Moore’s Law and Dennard Scaling has produced a renaissance in the field of computer architecture. Unable to continue leveraging silicon-level processor improvements to further enhance performance and scalability, system architects have been forced to explore other options. In this new era of heterogeneous architectures and hardware/software codesign, a new class of devices known as “accelerators” has emerged. Independently designed for optimized execution of distinct workloads, these devices have proven critical to the continued advancement of application performance. SmartNICs, accelerator devices integrated with a network controller, have conventionally been utilized to offload low-level networking functionality. However, newer SmartNIC variants, which incorporate a system-on-chip (SoC) with traditional designs, are challenging this precedent. Leveraging significantly augmented resources, these new devices offer increased versatility and the potential to more effectively complement a given architecture’s CPU. In this talk, we introduce the motivation underlying acceleration, explore the fundamentals of SmartNICs, and discuss traditional use cases. We also detail our initial efforts to investigate the feasibility and benefits of SmartNICs as general-purpose accelerators. We present the OpenSNAPI project created to define a uniform application programming interface (API) for this emerging class of devices. Finally, we provide a brief tutorial regarding development of SmartNIC-accelerated applications on Los Alamos National Laboratory’s SmartNIC-enabled platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development of Efficient Process for Manufacturing of Thermoplastic Composites with Tailored Properties (CRADA 511)

This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and ESI North America Inc. (“ESI” or “Participant”) to apply computation and data analytics to the challenge of light weighting with a focus on the battery enclosures of electric vehicles (EVs). EVs use heavy batteries to increase range and power. A complex-shaped battery enclosure is required to meet a host of challenging performance requirements. The ability to virtually develop composite parts such as battery enclosure with tailored properties to meet required performance will be highly valuable to the automotive industry. However, efficient simulation of composite-manufacturing processes remains a challenging issue since simulation involves multiscale models in space and time, highly non-linear and anisotropic behavior, strongly coupled multi-physics, and complex geometries. This work will advance the state of the art by reducing the computational burden of composite optimization by using simulation data from a limited number of configurations off-line and then developing a reduced order model (ROM) using data analytics and machine learning (ML). Develop a data driven approach to link features of the material and manufacturing processes to the mechanical properties of thermoplastic composite parts.

42 ENGINEERING↗
DOE OSTI2022

Demonstration of Improved CHP Systems utilizing Improved Gas Turbine and sCO2 Cycles Using Additive Manufacturing (AM) Components

This project seeks to integrate a sCO2 bottoming cycle with a 5.3 MW gas turbine to develop a CHP system that is able to transition rapidly between 50% and 100% load by engaging or bypassing the bottoming cycle while maintaining electrical system efficiency above 30% at all times. The project team will engineer an optimized design of the power systems. The needed new key components, such as advanced heat exchangers and a steam injection system for the gas turbine, will be developed and their performance demonstrated in rig tests. The feasibility of the whole integrated CHP system will be validated through a cyber-physical approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗