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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Reconfigurable Electrical Networks within a Conductive Hydrogel Composite

Soft materials that exhibit compliance, programmability, and reconfigurability can have a transformative impact as electronic skin for applications in wearable electronics/soft robotics. There has been significant progress in soft conductive materials; however, achieving electrically controlled and reversible changes in conductivity and circuit connectivity remains challenging. To overcome this limitation, a soft material architecture with reconfigurable conductive networks of silver flakes embedded within a hydrogel matrix is presented. The conductive networks can be reversibly created/disconnected through various stimuli, including current, humidity, or temperature. Such stimuli affect electrical connectivity of the hydrogel by controlling its water content, which can be modulated by evaporation under ambient conditions (passive dehydration), evaporation through electrical Joule heating (active dehydration), or absorption of additional water (rehydration). The resulting change in electrical conductivity is reversible and repeatable, endowing the composite with on-demand reconfigurable conductivity. To highlight this material's unique properties, it is shown that conductive traces can be reconfigured after severe damage and revert to lower conductivity after rehydration. Additionally, a quadruped robot is demonstrated that can respond to stimuli by changing direction following exposure to excess water, thereby achieving reprogrammable locomotion behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

3D Printing of Transparent Silicone Elastomers

Here in this paper, inks for transparent elastomers that are formulated by matching the refractive index of silica and polysiloxanes are described. The transparent inks transmit up to ≈90% of 700 nm light through 1 cm and remain transparent when solidified. The inks and solidified materials exhibit a thermochromic effect. This thermochromic effect can be controlled by the refractive index mismatch. Transparency may increase or decrease as temperature increases, depending on the refractive index mismatch of the base polysiloxane and silica. It is found that the rheological properties of the ink depend on the distribution of silica particles, which is dictated by silica functionality, weight content, and processing. Siloxane precursors that vary in chemical functionality are introduced to tailor the mechanical properties of the printed elastomers, which obtain stretchability >65% along with a tensile modulus of 1.9 MPa. After optimizing siloxane chemistry and ink processing, the authors are able to print transparent elastomers. Potential applications are demonstrated for printed structures by printing encapsulation structures for light-emitting diodes, semitransparent dye-filled structures, a microfluidic mixing device, and a multimaterial structure that exhibits temperature-dependent camouflage.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tunable Metamaterials for Impact Mitigation

Traditional methods of shielding fragile goods and human tissues from impact energy rely on isotropic foam materials. The mechanical properties of these foams are inferior to an emerging class of metamaterials called plate lattices, which have predominantly been fabricated in simple 2.5-dimensional geometries using conventional methods that constrain the feasible design space. Here in this work, additive manufacturing is used to relax these constraints and realize plate lattice metamaterials with nontrivial, locally varying geometry. The limitations of traditional computer-aided design tools are circumvented and allow the simulation of complex buckling and collapse behaviors without a manual meshing step. By validating these simulations against experimental data from tests on fabricated samples, sweeping exploration of the plate lattice design space is enabled. Numerical and experimental tests demonstrate plate lattices absorb up to six times more impact energy at equivalent densities relative to foams and shield objects from impacts ten times more energetic while transmitting equivalent peak stresses. In contrast to previous investigations of plate lattice metamaterials, designs with nonuniform geometric prebuckling in the out-of-plane direction is explored and showed that these designs exhibit 10% higher energy absorption efficiency on average and 25% higher in the highest-performing design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models

Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically in the Midwestern United States, remain poorly understood. This study aims to characterize the abiotic tolerances of these populations, estimate suitable areas, identify regions at risk of abiotic suitability change, and highlight the utility of ecological niche models (ENMs) in germplasm conservation. The Maxent algorithm was used to construct a series of ENMs. Validation metrics and MOP (Mobility-oriented Parity) analysis were used to assess extrapolation risk and model performance. We also projected the final projected under current and future climate scenarios (2021–2040 and 2061–2080) to assess how abiotic suitability changes with time. Climate change scenarios indicated an expansion of suitable habitat, with priority areas for germplasm collection in Indiana, Illinois, Kansas, Missouri, and Nebraska. This study demonstrates the application of ENMs for characterizing feral Cannabis populations and highlights their value in germplasm conservation and breeding efforts. Populations of feral C. sativa in the Midwest are of high interest, and future research should focus on utilizing tools to aid the collection of materials for the characterization of genetic diversity and adaptation to a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Search for light mediators in the low-energy data of the CONNIE reactor neutrino experiment

The CONNIE experiment is located at a distance of 30 m from the core of a commercial nuclear reactor, and has collected a 3.7 kg-day exposure using a CCD detector array sensitive to an~1 keV threshold for the study of coherent neutrino-nucleus elastic scattering. Here we demonstrate the potential of this low-energy neutrino experiment as a probe for physics Beyond the Standard Model, by using the recently published results to constrain two simplified extensions of the Standard Model with light mediators. We compare the new limits with those obtained for the same models using neutrinos from the Spallation Neutron Source. Our new constraints represent the best limits for these simplified models among the experiments searching for CE$ν$NS for a light vector mediator with mass $ {M}_{Z^{\prime }} $< 10 MeV, and for a light scalar mediator with mass M$_{\phi}$< 30 MeV. These results constitute the first use of the CONNIE data as a probe for physics Beyond the Standard Model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Search for coherent elastic neutrino-nucleus scattering at a nuclear reactor with CONNIE 2019 data

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) is taking data at the Angra 2 nuclear reactor with the aim of detecting the coherent elastic scattering of reactor antineutrinos with silicon nuclei using charge-coupled devices (CCDs). In 2019 the experiment operated with a hardware binning applied to the readout stage, leading to lower levels of readout noise and improving the detection threshold down to 50 eV. The results of the analysis of 2019 data are reported here, corresponding to the detector array of 8 CCDs with a fiducial mass of 36.2 g and a total exposure of 2.2 kg-days. The difference between the reactor-on and reactor-off spectra shows no excess at low energies and yields upper limits at 95% confidence level for the neutrino interaction rates. In the lowest-energy range, 50 − 180 eV, the expected limit stands at 34 (39) times the standard model prediction, while the observed limit is 66 (75) times the standard model prediction with Sarkis (Chavarria) quenching factors.[graphic not available: see fulltext]

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process

Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/Solid Mechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. Next, the resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of fluorescent dopants on the vat photopolymerization of acrylate-based plastic scintillators for application in neutron/gamma pulse shape discrimination

Plastic scintillators, a class of solid-state materials used for radiation detection, were additively manufactured with vat photopolymerization. The photopolymer resins consisted of a primary dopant and a secondary dopant dissolved in a bisphenol A ethoxylate diacrylate-based matrix. The absorptive dopants significantly influence important print parameters, for example, secondary dopants decrease the light penetration depth by a factor > 12×. The primary dopant 2,5-diphenyloxazole had minimal impact on the printing process even when loaded at 25 % by mass of the resin. Working curve measurements, which relate energy dose to cure depth, were performed as a function of feature size to further assess the influence of dopants. Photopatterns smaller than 150 µm width had apparent increases in critical energy dose compared to larger photopatterns, while all resins maintained printed features in line gratings with 50 µm of separation. Printed scintillator monoliths were compared to scintillators cast by traditional molding, demonstrating that the layer-by-layer printing process does not decrease scintillation response. In conclusion, a maximum light output of 31 % of a benchmark plastic scintillator (EJ-200) and successful pulse shape discrimination were achieved with 20 % by mass 2,5-diphenyloxazole as the primary dopant and 0.1 % by mass 9,9-dimethyl-2,7-distyrylfluorene as the secondary dopant in printed scintillator samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Probing the surface of promoted CuO-Cr 2 O 3 -Fe 2 O 3 catalysts during CO 2 activation

The influence of basic oxide promoters on copper-chromium-iron oxide catalysts was investigated to determine the nature of surface oxygen species and structure-activity relationship for the reverse water-gas shift reaction. The catalysts were characterized with in situ XRD, in situ Raman, in situ XPS, in situ HS-LEIS and H 2 -TPR. Two surface oxygen sites with different reduction characteristics were found to be present. The overall CO 2 activation rate was found to correlate with both the number and reducibility of the more active oxygen species that were likely associated with the Cu-FeO x interfacial regions for enhanced hydrogen spillover. While addition of K 2 O somewhat preserved the interfacial regions and facilitated the reduction kinetics of surface oxygen, both Na 2 O and CaO significantly suppressed the availability of metallic Cu as well as the Cu-FeO x interfaces, leading to decreased reactivity. These findings provide a direction to promote the copper-iron catalysts by creating more metal-metal oxide interfacial sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effect of redox promoters (CeO x and CuO x ) and surface sulfates on the selective catalytic reduction (SCR) of NO with NH 3 by supported V 2 O 5 -WO 3 /TiO 2 catalysts

A series of TiO 2 -supported MO x catalysts (M=V, W, Ce, Cu and S) were investigated for their SCR activity. In situ Raman spectroscopy indicated that the supported MO x phases were completely dispersed as surface sites on the TiO 2 support. In situ IR revealed that surface VO x , WO x and SO x sites anchored at both CeO x /CuO x and TiO 2 sites. The number of surface Lewis acid sites decreased with the addition of basic (CeO x /CuO x ) and acidic (VO x /WO x ) sites in all catalysts, and acidic SO x in the unpromoted and Ce-promoted catalysts. The surface VO x , WO x and SO x sites introduced surface Brønsted acid sites. The redox promoters increased the NO conversion, but SO x impregnation inhibited their effect due to acid (SO x )-base (CeO x /CuO x ) interactions. Finally, the SCR reaction was shown to efficiently proceed via either surface NH 3 * or NH 4 +* species, resolving the long-standing dispute on the involvement of these species in the SCR reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The effect of non-redox promoters (AlO x , PO x , SiO x and ZrO x ) and surface sulfates on supported V 2 O 5 -WO 3 /TiO 2 catalysts in selective catalytic reduction of NO with NH 3

The SCR activity of MO x (M=Al, P, Si, Zr) promoted V 2 O 5 -WO 3 /TiO 2 was investigated before and after sulfation. In situ IR spectroscopy indicated that the VO x active sites preferentially anchor on promoter generated surface hydroxyl. In situ Raman spectroscopy confirmed that all oxides are completely dispersed on the TiO 2 surface. In situ NH 3 -IR spectroscopy showed that the oxides can increase the Lewis (AlO x and ZrO x ) and Brønsted (PO x , SiO x , VO x , WO x and SO x ) acid site concentrations. The SiO x and ZrO x promoters had little effect on NO conversion, while the AlO x and PO x promoters and surface sulfation generally inhibited it. The SiO x promoted catalyst was highly SCR active despite lacking Lewis acid sites, indicating that they are not vital for SCR. Finally, the N 2 O formation activity of the catalyst was inhibited by surface sulfation and the promoters, correlating with the promoter and SO x induced increase in the Brønsted acid sites’ strength.

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

Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies

The rapid progression in artificial intelligence has facilitated the emergence of large language models like ChatGPT, offering potential applications extending into specialized engineering modeling, especially physics-based building energy modeling. This paper investigates the innovative integration of large language models with building energy modeling software, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review is first conducted to reveal a growing trend of incorporating large language models in engineering modeling, albeit limited research on their application in building energy modeling. We underscore the potential of large language models in addressing building energy modeling challenges and outline potential applications including simulation input generation, simulation output analysis and visualization, conducting error analysis, co-simulation, simulation knowledge extraction and training, and simulation optimization. Three case studies reveal the transformative potential of large language models in automating and optimizing building energy modeling tasks, underscoring the pivotal role of artificial intelligence in advancing sustainable building practices and energy efficiency. The case studies demonstrate that selecting the right large language model techniques is essential to enhance performance and reduce engineering efforts. The findings advocate a multidisciplinary approach in future artificial intelligence research, with implications extending beyond building energy modeling to other specialized engineering modeling.

building energy modeling↗
DOE OSTI2025

Automatic building energy model development and debugging using large language models agentic workflow

Building energy modeling (BEM) is a complex process that demands significant time and expertise, limiting its broader application in building design and operations. While Large Language Models (LLMs) agentic workflow have facilitated complex engineering processes, their application in BEM has not been specifically explored. This paper investigates the feasibility of automating BEM using LLM agentic workflow. Here, we developed a generic LLM-planning-based workflow that takes a building description as input and generates an error-free EnergyPlus building energy model. Our robust workflow includes four core agents: 1) Building Description Pre-Processing, 2) IDF Object Information Extraction, 3) Single IDF Object Generator Suite, and 4) IDF Debugging Agent. These agents divide the complex tasks into manageable sub-steps, enabling LLMs to generate accurate and reliable results at each stage. The case study demonstrates the successful translation of a building description into an error-free EnergyPlus model for the iUnit modular building at the National Renewable Energy Laboratory. The effectiveness of our workflow surpasses: 1) naive prompt engineering, 2) other LLM-based workflows, and 3) manual modeling, in terms of accuracy, reliability, and time efficiency. The paper concludes with a discussion on the interplay between foundational models and LLM agent planning design, advocating for the use of fine-tuned, specialized models to advance this field.

97 MATHEMATICS AND COMPUTING↗