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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Inducible flippase-mediated metabolic engineering of Rhodosporidium toruloides for enhanced 3-hydroxypropionic acid production from corn stover hydrolysate

Rhodosporidium toruloides has gained increasing interests as a promising non-model host organism to produce a wide range of bioproducts from lignocellulosic biomass. Increasing the bioproduct titers, rates, and yields remains a challenge, largely due to a lack of robust and well-characterized genetic tools in this host. Here we developed an inducible flippase (FLP) and flippase recognition target (FRT) system that enables genetic manipulations without the need for additional selection markers. Synthetic inducible promoters were established, enabling regulation of FLP expression and efficient antibiotic marker removal. Leveraging this system, we engineered a strain to optimize 3-hydroxypropionic acid (3HP) production. Over four rounds of iterative genomic editing to resolve pathway bottlenecks, we achieved a 3HP titer of 69.4 g/L in fed-batch fermentation - the highest level reported in yeast from lignocellulosic hydrolysates. The engineered high 3HP producing strain offers a robust platform for sustainable bio-based chemical production from lignocellulosic feedstocks.

3-hydroxypropionic acid↗
DOE OSTI2022

Advances and perspectives on mass transfer and enzymatic hydrolysis in the enzyme-mediated lignocellulosic biorefinery: A review

We report enzymatic hydrolysis is a critical process for the cellulase-mediated lignocellulosic biorefinery to produce sugar syrups that can be converted into a whole range of biofuels and biochemicals. Such a process operating at high-solid loadings (i.e., scarcely any free water or roughly ≥ 15% solids, w/w) is considered more economically feasible, as it can generate a high sugar concentration at low operation and capital costs. However, this approach remains restricted and incurs “high-solid effects”, ultimately causing the lower hydrolysis yields with increasing solid loadings. The lack of available water leads to a highly viscous system with impaired mixing that exhibits strong transfer resistance and reaction limitation imposed on enzyme action. Evidently, high-solid enzymatic hydrolysis involves multi-scale mass transfer and multi-phase enzyme reaction, and thus requires a synergistic perspective of transfer and biotransformation to assess the interactions among water, biomass components, and cellulase enzymes. Porous particle characteristics of biomass and its interface properties determine the water form and distribution state surrounding the particles, which are summarized in this review aiming to identify the water-driven multi-scale/multi-phase bioprocesses. Further aided by the cognition of rheological behavior of biomass slurry, solute transfer theories, and enzyme kinetics, the coupling effects of flow-transfer-reaction are revealed under high-solid conditions. Based on the above basic features, this review lucidly explains the causes of high-solid hydrolysis hindrances, highlights the mismatched issues between transfer and reaction, and more importantly, presents the advanced strategies for transfer and reaction enhancements from the viewpoint of process optimization, reactor design, as well as enzyme/auxiliary additive customization.

45 multi-scale, multi-phase, enzymatic reaction↗
DOE OSTI2023

Correlated particle transport enables biological free energy transduction

Studies of biological transport frequently neglect the explicit statistical correlations among particle site occupancies (i.e., they use a mean-field approximation). Neglecting correlations sometimes captures biological function, even for out-of-equilibrium and interacting systems. Here, we show that neglecting correlations fails to describe free energy transduction, mistakenly predicting an abundance of slippage and energy dissipation, even for networks that are near reversible and lack interactions among particle sites. Interestingly, linear charge transport chains are well described without including correlations, even for networks that are driven and include site-site interactions typical of biological electron transfer chains. We examine three specific bioenergetic networks: a linear electron transfer chain (as found in bacterial nanowires), a near-reversible electron bifurcation network (as in complex III of respiration and other recently discovered structures), and a redox-coupled proton pump (as in complex IV of respiration).

bacterial nanowires↗
DOE OSTI2024

Generative $β$-hairpin design using a residue-based physicochemical property landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the -hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial -hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

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

Insight into molecular basis and dynamics of full-length CRaf kinase in cellular signaling mechanisms

Raf kinases play key roles in signal transduction in cells for regulating proliferation, differentiation, and survival. Despite decades of research into functions and dynamics of Raf kinases with respect to other cytosolic proteins, understanding Raf kinases is limited by the lack of their full-length structures at the atomic resolution. Here, we present the first model of the full-length CRaf kinase obtained from artificial intelligence/machine learning algorithms with a converging ensemble of structures simulated by large-scale temperature replica exchange simulations. Our model is validated by comparing simulated structures with the latest cryo-EM structure detailing close contacts among three key domains and regions of the CRaf. Our simulations identify potentially new epitopes of intramolecule interactions within the CRaf and reveal a dynamical nature of CRaf kinases, in which the three domains can move back and forth relative to each other for regulatory dynamics. The dynamic conformations are then used in a docking algorithm to shed insight into the paradoxical effect caused by vemurafenib in comparison with a paradox breaker PLX7904. In this study, we propose a model of Raf-heterodimer/KRas-dimer as a signalosome based on the dynamics of the full-length CRaf.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Association of residential energy efficiency retrofits with indoor environmental quality, comfort, and health: A review of empirical data

This paper reviews empirical data from evaluations of the influence of residential energy efficiency retrofits on indoor environmental quality conditions and self-reported thermal comfort and health. The data were extracted from 36 studies described in 44 papers plus two reports. Nearly all reviewed studies were performed in Europe or United States. Most studies evaluated retrofits of homes with low-income occupants. Indoor radon and formaldehyde concentrations tended to increase after retrofits that did not add whole-house mechanical ventilation. Study-average indoor concentrations of nitrogen dioxide and volatile organic compounds other than formaldehyde increased and decreased with approximately equal frequency. Average indoor temperatures during winter typically increased after retrofits, usually by less than 1.5 °C. Dampness and mold, usually based on occupant's reports, almost always decreased after retrofits. Subjectively reported thermal comfort, thermal discomfort, non-asthma respiratory symptoms, general health, and mental health nearly always improved after retrofits. For asthma symptoms, the evidence of improvement slightly outweighed the evidence of worsening. There was insufficient evidence to determine whether changes in thermal comfort and health outcomes varied depending on the type of energy efficiency retrofit. The published research has numerous limitations including a lack of data from retrofits in warm-humid climates and minimal data on changes in objective health outcomes. Suggestions for future research are provided.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

The impacts of building characteristics, social psychological and cultural factors on indoor environment quality productivity belief

Indoor environmental quality (IEQ) plays a key role in determining occupants' productivity at work; however, analyses of the interconnected factors among building physical, attitudinal, social and demographic components in one study are lacking. To fill this research gap, this study investigates these interconnected factors' influence on occupants’ IEQ-productivity belief, defined as a personal, subjective evaluation of the linkage between the impacts of five IEQ aspects (the quality of indoor temperature, air, natural and electric lighting, and acoustics) and productivity. A cross-sectional survey data was collected in university offices from six countries (Brazil, Italy, Poland, Switzerland, Taiwan and the U.S.). Results of multiple linear regression models indicate that IEQ satisfaction is the strongest positive predictor of the IEQ-productivity belief and this relationship is stronger in private offices. Country of residence is the second primary predictor. Several attitudinal-behavioral factors, including thermal comfort, perceived ease of controlling indoor environmental features, and attitudes toward sharing controls are all positively associated with IEQ-productivity belief. Interestingly, the level of control accessibility to light switches has the strongest impact as opposed to other controls. On the other hand, group norms and conformity intention are not significant predictors. Regarding demographics, men are more likely than women to perceive the IEQs to have positive impacts on their productivity, without considering other variables in the regression model; however, women are more likely than men to consider all IEQs as having positive impacts on productivity, after considering other variables. Furthermore, our findings provide suggestions for prioritizing wellness in the workplace since the early design stage.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Impact of WELL certification on occupant satisfaction and perceived health, well-being, and productivity: A multi-office pre- versus post-occupancy evaluation

The WELL Building Standard (WELL) is currently one of the most comprehensive building certification programs that aim to enhance the health and well-being of building occupants. However, there is a lack of systematic evaluation of the effectiveness of WELL in achieving its goal. This study investigates the impact of WELL certification on occupant satisfaction with the workplace and occupant perceived health, well-being, and productivity. More than 1300 pre- and post-occupancy survey responses provided by the nearly same cohort of occupants from six companies in North America were quantitatively analyzed. The results showed that transitioning to WELL certified offices from non-WELL certified offices had a positive impact on occupant satisfaction with the workplace and occupant perceived health, well-being, and productivity, with increases in means from pre-to post-occupancy being highly statistically significant. The majority of the studied occupant satisfaction parameters as well as occupant perceived mental health had large effect sizes. While they improved from pre-to post-occupancy, the analysis revealed small effect sizes for occupant perceived physical health and self-assessed productivity. The majority of the effect sizes for the perceived well-being parameters were large and medium. In addition to analyzing the survey responses in aggregate, the responses were examined at the individual company level to confirm the by-company and aggregate findings aligned.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Smart thermostat data-driven U.S. residential occupancy schedules and development of a U.S. residential occupancy schedule simulator

Occupancy schedule is one of the key inputs in Building Energy Modeling (BEM) to reflect the interaction between buildings and occupants. Over the past decades, standardized occupancy schedules, developed mainly by engineering rule-of-thumb, have been widely used in BEM due to its simplicity and lack of real measured occupancy data. However, the BEM community has recognized their association with uncertainty and reliability in simulation results from BEM. This study introduces representative occupancy schedules in the U.S. residential buildings, derived from a large smart thermostat dataset and time-series K-means clustering, and an open-source tool to generate a stochastic residential occupancy schedule. Over 90,000 residential occupancy schedules were estimated from the ecobee Donate Your Data dataset. Then, the representative occupancy schedules were identified through clustering. This study further investigated the impacts of three parameters (day, house type, and state) on residential occupancy schedules. Then, a tool, the Residential Occupancy Schedule Simulator (ROSS), is developed using the representative occupancy schedules derived in this study. Details of this tool are presented in this paper. In conclusion, the derived representative occupancy schedules and the ROSS tool can help improve the energy modeling of residential buildings.

42 ENGINEERING↗
DOE OSTI2023

Comparing simulated demand flexibility against actual performance in commercial office buildings

Commercial building energy benchmarking has been used as a mechanism to evaluate energy use of a single building over time, relative to other similar buildings, or to simulations of a reference building conforming to various energy standards. Lack of empirical demand flexibility data and consistent flexibility metrics has limited the ability to compare demand flexibility performance with estimated demand flexibility in buildings. In this study, we collected demand response performance data for a total of 831 demand response events from 192 sites as a first step to build such a building demand flexibility dataset, and propose a standard core data schema to consolidate field data from different sources. We also performed parametric simulations of a control strategy called “global temperature adjustment” using commercial office prototype building models. We then compared the simulated demand flexibility performance against the actual data for offices with global temperature adjustment strategy implemented. During demand response events with an average outside air temperature of 34 °C (range 23 °C–42 °C), the measured demand decrease intensity of the demand flexibility metrics were 6.1 watts per square meter (W/m 2 ), 10.0 W/m 2 , 11.1 W/m 2 , 7.1 W/m 2 , and 4.7 W/m 2 for small, small–medium, medium, medium–large, and large office buildings, respectively. Compared to the measured data in medium- and large-size buildings, the simulated demand decrease intensity was 0.7 W/m 2 (17%) lower on average. The discrepancy between simulated and measured peak demand intensities fell within one standard deviation of the mean measured data. Here, the comparison results validate the credibility of simulations in capturing real building data for assessing the technical potential of building demand flexibility.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5% and 0.5% for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4% and 7.0% for the detailed medium office building model and high-rise building model, respectively. Here this study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Mapping use cases and dataset needs for benchmarking buildings data

A perennial challenge in buildings research is the lack of high-quality datasets that can be relied upon for a wide array of tasks, including model calibration and improving energy efficiency and load flexibility. Instrumenting a building for data collection is resource intensive, so it is important to be methodical in the approach and ensure that resulting data are flexible and useful for a broad range of analyses. This study aims to fill the gaps in characterizing potential use cases for buildings datasets and mapping them to dataset needs using a well-defined data infrastructure. Here, we have developed a systematic mapping strategy between buildings dataset needs and use cases to help streamline the processes of efficiently targeting datasets, designing building sensing systems, and determining buildings research use cases. We selected 14 prospective use cases and 11 refined buildings data categories for developing the preliminary dataset-needs-to-use-cases mapping matrix (‘DN-UC mapping matrix’) with generic ‘Tags’—a detailed sub-level of data categories extracted by justifying the needs of an aspect of the datasets to use cases. We present two example applications of the developed mapping matrix to demonstrate use of the mapping matrix and its effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Energy efficiency and thermal resilience analysis for row houses using representative building energy models

Row houses, a prevalent medium-density urban archetype, were popularized during industrial era to accommodate the working class in the U.S. cities. Today, many of these structures are deteriorating, exacerbating the energy cost for residents with limited economic resources. Moreover, many households that lack Air Conditioning (AC) are vulnerable to extreme summer heat, an issue expected to worsen in the future. Energy-efficient retrofits can help mitigate these challenges. However, current literature provides limited insight into how existing building energy codes impact the energy efficiency and thermal resilience of row houses in current and future weather scenarios. This study provides a detailed method to address this gap by employing calibrated representative energy models of row houses as a baseline, and evaluating the annual energy savings and summertime thermal safety improvements from code compliant retrofits under current and future typical weather conditions. Using Baltimore City as a case study, results show that under current weather, retrofitting row houses yields significant energy savings along with notable thermal resilience improvements. The end unit row house realizes higher energy savings, whereas the interior unit experiences greater thermal resilience improvement after retrofitting. In future, retrofitted row houses can still save energy, but residents will face numerous hours of fatal indoor temperatures without AC in summer. Additionally, findings reveal stark zone-wise variations in thermal safety, and elevated humidity risks in certain zones post-retrofit, emphasizing the need for zonal retrofit strategies and better natural ventilation strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Cool rooms for indoor heat resilience: Evaluating affordable cooling strategies in heat-stressed California homes

Extreme heat conditions pose significant indoor survivability challenges for resource-constrained communities, which often lack access to cooling, have poorly insulated homes, and face compounding socioeconomic vulnerabilities. Moreover, concurrent power outages worsen health risks and heat-related illnesses. It is therefore crucial to develop innovative and affordable cooling approaches to protect vulnerable populations. This study assesses the efficacy of “cool rooms”– a designated space within a home equipped with passive and low-power active cooling measures to maintain safe indoor temperatures during extreme heat events and power disruptions. Using a physics-based building energy modeling approach, we evaluate the efficacy of various retrofit packages in maintaining thermal safety within the cool room under recent extreme heat conditions. The results indicate that passive measures can reduce 64% of hours with unmet standard effective temperatures, while the combination of passive and low-power active measures with built-in batteries further cuts this to 86%. Nevertheless, these strategies remain insufficient to maintain indoor thermal safety during extended outages. In contrast, integrating a solar-powered mini-split heat pump, whose technical potential was evaluated in this study, reduces indoor air temperatures below the 28 °C overheating threshold and significantly improves indoor habitability. The localized cool room strategy also offers potential for grid resilience by reducing peak electricity demand by up to 70% compared to whole house cooling during heat waves. The findings can inform the development of actionable heat mitigation plans and retrofit policies for residential communities with relatively low adoption of air conditioning such as warm marine climates.

Cool room↗
DOE OSTI2024

Design and evaluation of alphabetic and numeric input methods for virtual reality

In today’s virtual reality (VR), users have various ways to influence their VR experience, including alphanumeric input. While typing characters and numbers is straightforward on desktop computers, it presents challenges and opportunities in head-mounted display VR due to specific interaction methods and a lack of real-world visual stimuli. Addressing these open questions, our work implements and evaluates ten approaches to alphabetic and numeric inputs in VR. Here, we describe the design motivation behind these input methods and evaluate them in a user study with 40 participants divided into groups for alphabetic and numeric keyboards. This comparison investigates each method’s performance and user interactions. Our findings suggest that different input methods significantly impact words per minute and error rates, and that certain keyboard designs may receive better subjective evaluations despite poorer objective performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Fast multiscale contrast independent preconditioners for linear elastic topology optimization problems

The goal of this work is to present a fast and viable approach for the numerical solution of the high-contrast state problems arising in topology optimization. The optimization process is iterative, and the gradients are obtained by an adjoint analysis, which requires the numerical solution of large high-contrast linear elastic problems with features spanning several length scales. The size of the discretized problems forces the utilization of iterative linear solvers with solution time dependent on the quality of the preconditioner. The lack of clear separation between the scales, as well as the high-contrast, imposes severe challenges on the standard preconditioning techniques. Thus, here we propose new methods for the high-contrast elasticity equation with performance independent of the high-contrast and the multi-scale structure of the elasticity problem. The solvers are based on two-levels domain decomposition techniques with a carefully constructed coarse level to deal with the high-contrast and multi-scale nature of the problem. The construction utilizes spectral equivalence between scalar diffusion and each displacement block of the elasticity problems and, in contrast to previous solutions proposed in the literature, is able to select the appropriate dimension of the coarse space automatically. The new methods inherit the advantages of domain decomposition techniques, such as easy parallelization and scalability. Finally, the presented numerical experiments demonstrate the excellent performance of the proposed methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Nitrogen-doped graphene-wrapped Cu 2 S as a superior anode in sodium-ion batteries

Sodium-ion batteries (SIBs) have been attracting an ever-growing research interest, mainly ascribed to their cost-effectiveness. However, SIBs have been significantly hindered by lack of a suitable anode. Herein, an exceptional Cu 2 S-based composite anode is developed via a facile ball-milling method, in which Cu 2 S particles are wrapped by nitrogen-doped graphene sheets (Cu 2 S@NG). This Cu 2 S@NG composite anode enables extremely long cycling life, ultra-stable cyclability with high capacity, and excellent rate capability. The superior performance of the Cu 2 S@NG composite is owing to its intriguing core-shell structure and the exceptional properties of both the Cu 2 S and NG. In this study, it is found that the NG shell yields multiple merits in improving the performance of Cu 2 S: (i) mitigating the loss of active materials, (ii) constituting a stable interface, (iii) providing improved electrical conductivity and good ionic transfer, and (iv) enhancing mechanical integrity. Additionally, the vital effects of different voltage windows and a surface coating via atomic layer deposition on further enhancing performance are clarified. Significantly, the electrochemical mechanism of Cu 2 S during sodiation/desodiation is unveiled using advanced synchrotron-based in-situ X-ray diffraction and X-ray adsorption spectroscopy. This work represents a great advance in seeking high-performance anodes in SIBs.

25 ENERGY STORAGE↗
DOE OSTI2020

Direct observation on supersonic microprojectile penetration of carbon fiber composites with ultrafast synchrotron X-ray phase contrast imaging

High-speed penetration into carbon fiber composites is of fundamental importance to materials science and impact engineering, but research along this line suffers considerably from the lack of direct experimental observations. Here we investigate such penetration dynamics of a unidirectional carbon fiber reinforced epoxy (UCFRE) composite, with a combination of in situ, ultrafast, synchrotron phase contrast imaging and finite element (FE) analysis. The experiments yield the first direct observation on projectile trajectories and fiber-scale deformation and damage in the UCFRE composites during supersonic microprojectile penetration, for different fiber orientations (0 degrees - 90 degrees from the impact direction) and projectile velocities (600 - 850 m.s -1 ), at unprecedented temporal (~ 100 ps) and spatial (5 μm) resolutions. The maximum penetration depth decreases with increasing fiber orientation angles, as a result of anisotropic damage evolution in the composite sample. Strain localizations are prone to develop along a direction perpendicular to the fiber orientation, while the damage or cavity region, along the fiber direction. FE modeling with a three-dimensional Hashin criterion yields consistent projectile trajectory and cavity morphology with the experimental results. Finally, with increasing fiber orientation angles, damage analyses show a transition in the damage mode from fiber compression to matrix compression damage, in line with the increasing maximum penetration depth.

36 MATERIALS SCIENCE↗