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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Coupling AFEX and steam-exploded sugarcane residue pellets with a room temperature CIIII-activation step lowered enzyme dosage requirements for sugar conversion

In this study, the potential integration of steam explosion (StEx) and ammonia fiber expansion (AFEX) with existing sugar/ethanol mills to form decentralized pre-processing depots was explored. Both StEx and AFEX pretreatment facilitated the production of sugarcane bagasse (SCB) and cane leaf matter (CLM) pellets with significantly higher bulk density, mechanical durability, and hydrophobicity relative to their untreated biomass pellet controls. However, ethanol production from standalone StEx and AFEX-treated SCB and CLM pellets required enzyme dosages greater than 21 mg/g glucan to achieve enzymatic hydrolysis sugar yields of 75% and ethanol titres greater than 40 g.L -1 . Coupling AFEX-treated SCB or CLM pellets with a room temperature CIII I -activation step using liquid ammonia lowered enzyme dosage requirements by more than 50% without affecting ethanol titers and production yields (greater than300 L per Mg residual dry matter raw dry biomass (RDM)). In contrast, treating StEx-treated pellets with CIIII-activation using liquid ammonia did not result in similar enzyme dosage reductions, due to pseudo-lignin formation, leading to enzyme deactivation and/or lignin blockage that retarded enzymatic hydrolysis at low enzyme dosages. A gross energy conversion assessment revealed that low enzyme dosage (3-4 mg enzyme/g RDM) ethanol and electricity co-production from AFEX and CIII I -activated SCB and CLM can recover up to 73% of the energy in the untreated biomass, compared to 54% recovered by StEx and CIII I -activation. The results from this work suggest that StEx or AFEX based pre-processing depots can produce dense and mechanically durable biomass pellets. The AFEX-treated pellets can be easily upgraded using a room temperature CIII I -activation step at the biorefinery to significantly reduce bioconversion enzymes.

42 ENGINEERING↗
DOE OSTI2022

Generalized optimization-based synthesis of membrane systems for multicomponent gas mixture separation

Synthesizing a membrane system to separate multicomponent gas mixture is challenging due to the combinatorial number of feasible configurations and the difficulties in describing the multicomponent permeators. Here we present a mixed-integer nonlinear programming (MINLP) model for synthesizing membrane systems for multicomponent gas mixture separation. The approach employs a richly connected superstructure to represent numerous potential system configurations, and different physics-based surrogate permeator models, such as countercurrent flow or crossflow, to be used in each stage. Moreover, to describe realistic systems, pressure drop equations can be included. We also present solution methods to accelerate the solution process. Through a case study of natural gas sweetening, we demonstrate that the proposed approach is able to obtain good solutions using an off-the-shelf global optimization solver. Finally, we expand the conventional membrane system synthesis problem by introducing feed variability in our model through a case study of an integrated reactor-separation system.

42 ENGINEERING↗
DOE OSTI2026

Bioelectrocatalytic conversion of CO₂ to PHA bioplastics using engineered methylotrophs

The sustainable generation of biodegradable plastics represents an opportunity to capture atmospheric CO 2 while reducing plastic waste accumulation in the environment. This study implements an integrated platform for bioelectrocatalytic CO 2 conversion to medium-chain-length polyhydroxyalkanoates (mcl-PHAs). Immobilizing cobalt phthalocyanine electrocatalysts on a covalent-organic framework in a gas recirculation electrolyzer enabled CO 2 -to-methanol conversion with a carbon conversion efficiency of 98%. Integration of polymer biosynthesis pathways enabled Methylotuvimicrobium alcaliphilum 20Z R to produce ~20% mcl-PHA of the dry cell weight with a CO 2 -to-bioproducts carbon conversion efficiency of 50%. This cell line was adapted to high sodium bicarbonate media, eliminating costly intermediate separation steps while improving economic potential. Transcriptomic analysis revealed sulfate transporters and peptidoglycan biosynthesis as key pathways involved in sodium bicarbonate halotolerance. Altogether, this research presents a foundation for integrating divergent chemical and biological processes into a transformative electrobiomanufacturing platform, addressing the need for alternative pipelines for generating valuable plastics and chemicals.

CO2 utilization↗
DOE OSTI2021

Energy efficient supercritical water desalination using a high-temperature heat pump: A zero liquid discharge desalination

Supercritical water desalination (SCWD) is zero liquid discharge technology that can potentially control the solubility of different electrolytes. However, SCWD is an energy-intensive process and requires high-quality thermal heat (> 450 °C). This study proposes the integration of a high-temperature heat pump to reduce the SCWD energy requirement. The integrated system energy consumption improves by 36% for 3.5% feed concentration and 14% for 20% feed, and the distillate cost reduces by 15% and 10%. Another benefit of the proposed integration is the system can be operated using only electricity as a heat source, as is the case with commonly used high-recovery thermal desalination technology. The integrated SCWD-heat pump system shows superior performance compared to the commercially used brine concentrator and crystallizer system. It is approximately 20% more energy-efficient for 25% feed concentration and 8% cheaper. Hence, the integrated SCWD-heat pump has the potential to outperform the pre-existing high-recovery desalination technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Interactions of Wind Energy Project Siting, Wind Resource Potential, and the Evolution of the U.S. Power System

The interactions of wind energy project siting, resource potential, and power system evolution are critical to understand given interest in high renewable energy systems, particularly as wind costs have fallen and grid operators implement solutions to manage variable generation. This study applies an integrative approach that combines spatially-explicit resource potential analysis with high spatial resolution U.S. electricity system modeling. Multiple wind supply curves, representing variations in siting regimes that account for interactions with built infrastructure, regulatory, physical, and social land use factors, are evaluated to determine how siting could influence prospective wind development. Different siting regimes lead to variations in future wind capacity, with the greatest impacts observed under scenarios with high demand for clean energy. With the tightest emissions limit modeled, 2050 onshore wind capacity varied by +7% (49 GW) in the least-restrictive siting regime to a decrease of 37% (270 GW) under the most-constrained case. More-stringent siting restrictions lead to higher electricity prices and emissions that should be weighed with local impacts. Under restrictive siting regimes, wind deployment is also sensitive to transmission availability and wind plant design. Overall, the findings highlight the importance of local land use considerations in regional and national power system planning.

17 WIND ENERGY↗
DOE OSTI2025

Towards the next generation of Geospatial Artificial Intelligence

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote sensing, urban computing, Earth system science, cartography, and geospatial semantics. Finally, we highlight several unique future research directions of GeoAI which are classified into two groups: GeoAI method development challenges and GeoAI Ethics challenges. Topics include heterogeneity-aware GeoAI, knowledge-guided GeoAI, spatial representation learning, geo-foundation models, fairness-aware GeoAI, privacy-aware GeoAI, as well as interpretable and explainable GeoAI. We hope our review of GeoAI’s past, present, and future is comprehensive and can enlighten the next generation of GeoAI research.

58 GEOSCIENCES↗
DOE OSTI2025

Upconversion of non-recycled MSW paper fractions into biochar via slow pyrolysis and life cycle analysis: Pathways to net negative GHG emission

This study presents an integrated and sustainable approach to valorizing non-recycled municipal solid waste (MSW), a heterogeneous and underutilized waste stream destined for landfilling, by converting it into valuable biochar resources. Specifically, we investigated the upcycling of nonrecycled paper waste based on compositional analysis into four major fractions: high cellulose, high lignin, high contamination, and high ash content papers. These fractions were then homogenized and subjected to slow pyrolysis. The high cellulose fraction (36.1 %) was the most abundant, and contained 66.7 % cellulose, while the high lignin fraction showed the highest lignin (12.1 %) and carbon content (44 %), resulting in highest energy value of 17.4 MJ kg −1 . Biochar yields ranged from 25.6 % to 35.6 %, with the high ash fraction producing the highest yield and alkalinity (pH ≈ 11.2) due to its higher mineral content. Elemental analysis revealed enhanced carbon content up to 76.9 % and reduced oxygen and hydrogen, confirming effective carbonization. The high lignin-derived biochar showed the highest aromatic carbon content (82.8 %) and greater structural stability, while contaminated and ash-rich fractions exhibited dense, low-porosity surfaces due to the presence of contaminants and minerals. Spectroscopic analysis revealed degradation of carbohydrates, disappearance of cellulose peaks and formation of aromatic and mineral derived phases. The scaled life cycle process yielded a global warming potential (GWP) of 119.3 kg CO 2 -eq per ton of dry paper waste, offset by soil carbon sequestration of − 556.41 kg CO 2 -eq, resulting in a net impact of − 427.36 kg CO 2 -eq. This represents a net carbon removal exceeding by ~186 % the emissions associated with landfilling paper waste with electricity generation.

09 BIOMASS FUELS↗
DOE OSTI2021

Colloidal synthesis and charge carrier dynamics of Cs 4 Cd 1-x Cu x Sb 2 Cl 12 (0 ≤ x ≤ 1) layered double perovskite nanocrystals

The toxicity and instability of lead-based metal halide perovskites are the two main obstacles that prevent perovskite materials from implementation in applications. Recently, layered double perovskites (LDPs) emerge as a new family of perovskite materials which provide a new route to solve these problems by lead-component replacement and reduction of crystal structure dimensionality. However, LDP nanocrystals (NCs) have been rarely studied, limiting the further property exploration and application realization. In this work, we report the colloidal synthesis of a series of Cs 4 Cd 1-x Cu x Sb 2 Cl 12 (0 ≤ x ≤ 1) LDP NCs by tuning the stoichiometry of metal precursors. The composition-structure-property relationships of the resulting LDP NCs are studied through materials characterizations, density functional theory calculations, and transient-absorption spectroscopy. In addition, we demonstrate that high-performance high-speed photodetectors can be fabricated using the colloidal LDP NCs through solution-processing. This work premises further expansion of such LDP-based materials for both fundamental studies and application integrations.

25 ENERGY STORAGE↗
DOE OSTI2024

Flexible operation of nuclear hybrid energy systems for load following and water desalination

Nuclear hybrid energy systems (NHES) have the potential to provide dependable and emission-free electricity to the grid while also increasing the flexibility and reliability of the electrical grid. Molten salt reactor (MSR) technology can provide consistent, carbon-free electricity while also increasing efficiency, security, and sustainability and reducing nuclear waste. This study investigates the integration of Molten Salt Reactors (MSR) and conventional Pressurized Water Reactors (PWR) with desalination technologies: Direct Contact Membrane Distillation (DCMD), Multi-Stage Flash Distillation (MSFD), and Reverse Osmosis (RO). Dynamic first-principles models were developed and tested using real grid data from the New York Independent System Operator. The results demonstrate that nuclear power is capable of flexibly responding to changing grid demand while simultaneously producing clean water, particularly during periods of low electricity demand. The MSR-RO system was found to be the most efficient in electricity generation and water production, and all hybrid systems reduced CO2 emissions by 356,000 to 682,000 tons annually. Economic analysis reveals that nuclear desalination technologies are cost-competitive with conventional systems, especially when paired with RO. Finally, these findings confirm the technical feasibility and environmental benefits of nuclear hybrid systems for sustainable electricity and water production.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

In-situ synthesized N-doped ZnO for enhanced CO 2 sensing: Experiments and DFT calculations

Chemiresistive CO 2 sensing is attractive due to low cost and ease of chip-level integration. Our previous studies (Yong Xia, 2021) showed the well-developed ZnO material fabricated by in-situ annealing exhibited good CO 2 sensing performance. Here, we have expanded on those studies, including CO 2 cyclic tests under both dry air and N 2 background whereby a much higher response to CO 2 in N 2 background was observed. In this study, detailed density functional theory calculations were conducted to understand the behavior. The results indicated nitrogen doping is mainly responsible for the observed response. In the presence of pre-adsorbed O 2 , N-doped ZnO can no longer interact with CO 2 , which agrees well with the observation of higher response in N 2 background. Furthermore, density of states analysis showed N sp 2 hybridized orbital and N 2p orbital of the N dopant mixed with sp 2 hybridized orbital of C atom and 2p orbitals of C/O atoms in CO 2 to form σ and π bonds, respectively. However, they mixed with O 2s/2p orbitals of O atom in O 2 when pre-adsorbed O 2 was present, hindering CO 2 interaction with N-doped ZnO, and resulting in limited response in air. The illustrated mechanism does not only further the understanding of metal oxide-based CO 2 sensing, but also guide the design of new functional materials for CO 2 sensing or capture.

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

Modeling charging infrastructure impact on the electric vehicle market in China

The plug-in electric vehicle (PEV) is deemed as a critical technological revolution, and the governments are imposing various vehicle policies to promote its development. Meanwhile, the market success of PEVs depends on many aspects. The study reported herein integrates one’s use of charging infrastructure at home, public place and workplace into the market dynamics analysis tool, New Energy and Oil Consumption Credits (NEOCC) model, to systematically assess the charging infrastructure (home parking ratio, public charging opportunity, and charging costs) impact on PEV ownership costs and analyze how the PEV market shares may be affected by the attributes of the charging infrastructure. Compared to the charging infrastructure, the impact of battery costs is incontrovertibly decisive on PEV market shares, the charging infrastructure is still non-negligible in the PEV market dynamics. The simulation results find that the public charging infrastructure has more effectiveness on promoting the PEV sales in the PEV emerging market than it does in the PEV mature market. However, the improvement of charging infrastructure does not necessarily lead to a larger PEV market if the charging infrastructure incentives do not coordinate well with other PEV policies. Besides, the increase of public charging opportunities has limited motivations on the growth of public PEV fleets, which are highly correlated to the number of public fast charging stations or outlets. It also finds that more home parking spaces can stimulate more sales of personal plug-in hybrid electric vehicles instead of personal battery electric vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Thermal-Strain-Enabled Enhanced Emission from UV Laser-Induced Defect Levels near the Surface of Multilayer MoS 2

Monolayer two-dimensional (2D) materials have been intensively studied while research on multilayers is still in its infancy. Here, we induce defects inside bulk MoS 2 through thermal annealing and near the surface of multilayer MoS 2 using 375 nm laser irradiation, and investigate their photoluminescence (PL) and fluorescence lifetime imaging (FLIM). Enhanced emission is limited within a certain MoS 2 thickness. The observed enhanced emission is evidenced by a threshold behavior in super-linear PL intensity increase, strong polarization effects, and increased lifetime of defect peak. The laser power threshold for enhanced emission is much smaller in defects near the surface than that inside the bulk of multilayer MoS 2 . The mechanical strain from a wrinkle of the sample further lowers the laser power threshold for enhanced emission. By exciting with a 639 nm laser that is close to the fundamental gap between the conduction band minimum and the valence band maximum, the lifetime of defect enhanced emission increased by 5 times. Furthermore, one of the competing indirect bandgap emissions disappears, and the defect emission peak dominates the PL spectrum in the wrinkle area with a strain. Furthermore, the discovered principle can be applied to future studies on the integration of enhanced emission and single photon emission involving selectively depopulating the conduction band of the host crystal to defect levels for quantum emitters.

2D materials↗
DOE OSTI2021

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer–particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental–theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Here, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Evaluating the Effects of Anode Porous Transport Layer on the Performance and Durability of Anion Exchange Membrane Electrolyzers

As anion exchange membrane systems have emerged as a competitive low temperature electrolysis technology, research has expanded to other components and device integration. In this study, nickel (Ni) and stainless steel (SS)-based porous transport layers (PTLs) are investigated in membrane electrode assemblies (MEAs). Compared to MEAs using Ni, the SS PTL shows higher performance due to less kinetics and residual loss and possibly due to a combination of iron mobility improving oxygen evolution reactivity and electron conduction pathways, as well as higher porosity increasing site access. Voltage decay rates of approximately 144 and 115 μV/h, respectively, for the Ni and SS PTLs are found, although the long-term durability and lifetime implications are convoluted. Voltage breakdown analysis confirms that both PTLs saw significant increases in residual loss possibly due to catalyst/PTL property changes that affected electronic, ionic, and mass transport pathways. For the Ni PTL, a higher proportion of the losses were due to cell kinetics; comparatively, more of the SS PTL losses were due to increases in the high frequency resistance. The experimental findings presented here provide insights on the impact of the PTL materials and their properties.

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

Automated Strain Construction for Biosynthetic Pathway Screening in Yeast

Automation accelerates the Design-Build-Test-Learn (DBTL) cycle for synthetic biology; however, most strain construction pipelines lack robotic integration. Here, in this study, we present the workflow design and source code for a modular, integrated protocol that automates the Build step in Saccharomyces cerevisiae. We programmed the Hamilton Microlab VANTAGE to integrate off-deck hardware via its central robotic arm, enabling automated steps that increased throughput to 2,000 transformations per week. We developed a user interface with the Hamilton VENUS software to support on-demand parameter customization. As a proof of concept, we screened a gene library in an engineered yeast strain producing verazine, a key intermediate in the biosynthesis of steroidal alkaloids. Our pipeline rapidly identified pathway bottlenecks and genes that enhanced verazine production by 2.0- to 5-fold. This technical note provides resources for synthetic biologists designing yeast workflows for biofoundries to screen libraries for pathway discovery/optimization, combinatorial biosynthesis, and protein engineering.

automation↗
DOE OSTI2021

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine learning assisted prediction of the Young’s modulus of compositionally complex alloys

We identify compositionally complex alloys (CCAs) that offer exceptional mechanical properties for elevated temperature applications by employing machine learning (ML) in conjunction with rapid synthesis and testing of alloys for validation to accelerate alloy design. The advantages of this approach are scalability, rapidity, and reasonably accurate predictions. ML tools were implemented to predict Young’s modulus of refractory-based CCAs by employing different ML models. Our results, in conjunction with experimental validation, suggest that average valence electron concentration, the difference in atomic radius, a geometrical parameter λ and melting temperature of the alloys are the key features that determine the Young’s modulus of CCAs and refractory-based CCAs. The Gradient Boosting model provided the best predictive capabilities (mean absolute error of 6.15 GPa) among the models studied. Our approach integrates high-quality validation data from experiments, literature data for training machine-learning models, and feature selection based on physical insights. It opens a new avenue to optimize the desired materials property for different engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework

Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. Finally, the heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.

99 GENERAL AND MISCELLANEOUS↗