Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reduction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Catalytic bias in oxidation–reduction catalysis

Cataytic bias refers to the propensity of a reaction catalyst to effect a different rate acceleration in one direction versus the other in a chemical reaction under non-equilibrium conditions. In biocatalysis, the inherent bias of an enzyme is often advantagous to augment the innate thermodynamics of a reaction to promote efficiency and fidelity in the coordination of catabolic and anabolic pathways. In industrial chemical catalysis a directional cataltyic bias is a sought after property in facilitating the engineering of systems that couple catalysis with harvest and storage of for example fine chemicals or energy compounds. Interestingly, there is little information about catalytic bias in biocatalysis likely in large part due to difficulties in developing tractible assays sensitive enough to study detailed kinetics. For oxidation–reduction reactions, colorimetric redox indicators exist in a range of reduction potentials to provide a mechanism to study both directions of reactions in a fairly facile manner. The current short review attempts to define catalytic bias conceptually and to develop model systems for defining the parameters that control catalytic bias in enzyme catalyzed oxidation–reduction catalysis.

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

Analytical model for drag reduction on liquid-infused structured non-wetting surfaces

Liquid-infused structured non-wetting surfaces provide alternating no-slip and partial slip boundary conditions to the fluid flow, resulting in reduced friction at the interface. In this paper, an analytical model is developed for the evaluation of effective slip and, in turn, friction factor and drag reduction on liquid-infused structured non-wetting surfaces. By considering the entire range of anisotropy and heterogeneity of the surface structures as well as the full range of partial slip offered by the infusion liquid, the present model eliminates empirical fitting or correlations that are inherent in previous studies. Based on the effective slip length, drag reduction and skin friction coefficient values for Newtonian flow between two infinite parallel plates and flow in round tubes are presented. Extension of Moody charts for non-wetting surfaces and design maps of surface meso/micro/nano texturing for achieving desired drag reduction are presented for a broad range of engineering applications. The paper further presents independent validation of the model across experimental and computational data from the literature and brings together several previous studies in a unified manner.

36 MATERIALS SCIENCE↗
DOE OSTI2025

From lignin to market: a technical and economic perspective of reductive depolymerization approaches

Lignin has grown into one of the main candidates to replace fossil-based resources as it is the largest renewable source of aromatic building blocks. The complex structure of polymeric lignin, however, requires depolymerization to simpler building blocks for the chemical industry. One of the most promising depolymerization approaches is reductive depolymerization of which two process configurations are currently studied in pilot scale installations for upscaling to industrial scale: (i) reductive catalytic fractionation (RCF), and (ii) reductive catalytic depolymerization (RCD). Both technical and techno-economic aspects will be covered within this review, discussing the advantages and challenges of both approaches regarding processing, production costs, product output, and applications. In this regard, RCF benefits from its decreased energy and solvent consumption linked with being a one-step process and delivers a product with a high monomer content (∼25–45 wt%). RCD, on the other hand, has the advantage of continuous processing and reduced catalyst fouling and delivers a product that mainly consists of oligomers (<10 wt% monomers). The complete overview of both processes presented here addresses their potential, and can guide future researchers, policy makers and companies to make thoughtful decisions on lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2025

Electrochemical reduction of ammonia-captured CO 2 to CO over a nickel single-atom catalyst

Carbon reactive capture and conversion offers a sustainable route to valuable chemicals and fuels while aiding Green House Gas (GHG) reduction. Direct electrochemical conversion of capture solutions like bicarbonate avoids the energy demands of conventional CO 2 regeneration. Ammonium bicarbonate (NH 4 HCO 3 ) is particularly attractive due to its low decomposition temperature and ability to supply in situ CO 2 from dilute sources without requiring purified CO 2 . Meanwhile, single-atom catalysts (SACs) with nitrogen-coordinated metal sites further enhance CO 2 reduction efficiency using Earth-abundant materials. In this study, we demonstrate a nickel single-atom catalyst (Ni-SAC)-based electrolyzer that utilizes NH 4 HCO 3 as the CO 2 source, achieving significantly improved CO production performance compared to the conventional silver cathodes used in the CO 2 reduction reaction (CO 2 RR) to produce CO. The Ni-SAC cathode exhibited a Faradaic efficiency of 60.1% for CO production at −200 mA cm −2 , while the silver cathode achieved a Faradaic efficiency of only 2%, likely due to ammonium-induced poisoning. Furthermore, the integration of a customized microporous layer onto the electrode significantly increased the Faradaic efficiency from 64% to 83% at −100 mA cm −2 , emphasizing the crucial role of electrode structure optimization in enhancing CO selectivity. These findings demonstrate a sustainable and economically viable strategy for green CO production directly from CO 2 capture solutions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Novel technologies for emission reduction complement conservation agriculture to achieve negative emissions from row-crop production

Plants remove carbon dioxide from the atmosphere through photosynthesis. Because agriculture’s productivity is based on this process, a combination of technologies to reduce emissions and enhance soil carbon storage can allow this sector to achieve net negative emissions while maintaining high productivity. Unfortunately, current row-crop agricultural practice generates about 5% of greenhouse gas emissions in the United States and European Union. Here, to reduce these emissions, significant effort has been focused on changing farm management practices to maximize soil carbon. In contrast, the potential to reduce emissions has largely been neglected. Through a combination of innovations in digital agriculture, crop and microbial genetics, and electrification, we estimate that a 71% (1,744 kg CO 2 e/ha) reduction in greenhouse gas emissions from row crop agriculture is possible within the next 15 y. Importantly, emission reduction can lower the barrier to broad adoption by proceeding through multiple stages with meaningful improvements that gradually facilitate the transition to net negative practices. Emerging voluntary and regulatory ecosystems services markets will incentivize progress along this transition pathway and guide public and private investments toward technology development. In the difficult quest for net negative emissions, all tools, including emission reduction and soil carbon storage, must be developed to allow agriculture to maintain its critical societal function of provisioning society while, at the same time, generating environmental benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2021

Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems

This work combines the Hierarchical Model (HiMod) reduction technique with a standard Proper Orthogonal Decomposition (POD) to solve parametrized partial differential equations for the modeling of advection-diffusion-reaction phenomena in elongated domains (e.g., pipes). This combination leads to what we define as HiPOD model reduction, which merges the reliability of HiMod reduction with the computational efficiency of POD. Two HiPOD techniques are presented and assessed by an extensive numerical verification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Knowledge Spillovers and Cost Reductions in Solar Soft Costs

Despite the commonly acknowledged importance of knowledge spillovers in reducing solar soft costs, we are only beginning to answer a fundamental question: who learns what (knowledge acquisition), from whom (knowledge production), and how (spillover mechanisms)? Until recently, this important topic has been largely unexplored in the case of solar soft costs. Thus, this project set out to identify how knowledge spillovers affect soft costs in the U.S. photovoltaic (PV) installation industry, specifically how important spillovers are, what types of knowledge are most likely to spillover, and how networks of actors affect spillovers. Our findings offer insights for designing solutions that address problems associated with knowledge spillovers and that leverage spillovers to reduce solar soft costs. Recognizing the ambiguity in the definition of soft costs, i.e., “non-hardware costs,” and variability in soft cost categories, we developed the Solar Soft Cost Ontology (SSCO) to systematically identify key concepts related to soft costs, network actors, learning processes, and the relationships between them. This ontology served as a foundational organizational structure for the methodology of the remaining tasks: case studies, surveys, pricing analysis, patent analysis, network analysis, and project integration across tasks. While there is substantial learning among installers that is reducing the soft costs for PV installations, most of that learning is retained by firms rather than spread across the industry. The positive relationship between experience accumulation and cost reductions is typically explained as learning by doing (LBD), but we find that LBD effects are mediated by other learning mechanisms, including learning by searching and learning by interacting. Knowledge spillovers have significant potential to reduce solar PV soft costs, but successful knowledge spillover pathways are complex and non-trivial. There are a wide variety of ways to construct an installation business, thus categories of firms that can effectively cross-learn directly are small and what knowledge is relevant to whom is challenging and costly for firms to assess. This fragmentation limits the critical mass needed for spillover related soft cost reductions. Knowledge does not flow directly between installers. Indirect knowledge transfer pathways are critical: distributors, software providers, collaboratives, and hiring. Furthermore, diverse, more integrated knowledge networks tend to promote successful learning by organizations and across the system as a whole. Accordingly, we find the need to supporting the whole ecosystem using an integrated policy and programmatic approach to support installers, distributors, complementary sector, and facilitators. Overall, a deliberate policy-mix design is needed to reduce the solar PV deployment barrier in terms of installation cost reductions, because deployment policies could potentially interact with policies that facilitate network-building and technological innovation. A combination of deployment policies, innovation-support policies, and network-facilitating policies could potentially lead to a more desired market outcome through achieving higher joint learning rates from firms’ cumulative experiences developed in a more integrated production and deployment ecosystem.

14 SOLAR ENERGY↗
DOE OSTI2022

Surface Chemistry and Heterogeneous Processes in Solar-Driven Pyridine-Catalyzed CO 2 Reduction

The objective of our studies was to advance our fundamental understanding of the surface chemistry and heterogeneous processes that occur in solar-driven pyridine-catalyzed CO 2 reduction. Solar-driven CO 2 reduction to produce fuels offers tremendous promise but commercial deployment is impeded by the lack of suitable catalysts that simultaneously provide high efficiency and product selectivity. Pyridine (C 5 H 5 N) has been reported as an effective, selective co-catalyst in the conversion of CO 2 to methanol (CH 3 OH) in photoelectrochemical cells employing gallium phosphide (GaP) photocathodes. However, despite considerable electrochemical characterization and a large number of theoretical considerations, there are still many fundamental questions about the surface chemistry and heterogeneous processes that are involved in the conversion mechanism. Our research was aimed at investigating the role of the electrode surface and heterogeneous processes in this catalysis. Gaining this fundamental understanding of the origin of pyridine’s effectiveness is important to the continued optimization of solar-driven CO 2 reduction.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Assessing the Impacts of CO 2 Reduction and Utilization Technologies on Regional Freshwater Resources

This work, a product of the Bioenergy Technologies Office (BETO)-supported multi-lab CO 2 Reduction and Upgrading for e-Fuels Consortium (CO 2 RUe), focuses on advanced research and development and cross-cutting evaluation of environmental, economic, and social sustainability for CO 2 reduction and upgrading for fuels and chemicals. The Consortium develops and de-risks advanced technologies that use renewable electricity to convert CO 2 into e-fuels and commodity chemicals. One key aspect of environmental sustainability consideration is water resources. This report summarizes a three-year study that analyzed the impacts of water consumption in select CO 2 reduction and utilization technologies in two future scenarios using a pair of water indices—water availability index and water stress footprint. The analyses also account for projected electricity grid mixes and their water withdrawal and water consumption demand in grid regions. The work identifies drivers, challenges, and critical areas in water sustainability, along with valuable insights into technological and regional factors. The study also explores the potential of using non-traditional water resources to reduce water stress and increase availability. These findings are intended to support industry stakeholders and BETO with the knowledge needed for informed decision-making, contributing to strategies to mitigate risks associated with the implementation of CO 2 utilization technologies.

09 BIOMASS FUELS↗
DOE OSTI2022

Regularizing Invertible Neural Networks for Airfoil Design Through Dimension Reduction

This work examines how dimension reduction can improve the performance of invertible neural networks (INN) for airfoil design. Design workflows are typically expensive, relying on many evaluations of high fidelity computational fluid dynamics (CFD) models. Furthermore, the inverse design problem is typically ill-posed. That is, multiple valid solutions exist that satisfy the design criteria. Regularization can reduce this inverse design space and simplify the problem. We study the use of subspace-based input dimension reduction to act as a regularizer for the INN model and improve the recovery of new airfoil shapes with desired performance characteristics. We find that the dimension reduction identifies two dominant modes, relating to airfoil thickness and camber, that optimally determine the airfoil's aerodynamics. We demonstrate the capability of the proposed INN model to generate 100 airfoils that satisfy the specific aerodynamic and structural characteristics.

airfoil design↗
DOE OSTI2023

Regional Carbon Emission Reduction Prediction via Retrofits of Commercial Buildings with a Case Study of US School Buildings in Hot Climates

Retrofitting commercial buildings has great potential to reduce carbon emissions as demonstrated by previous studies in some specific cities, but their regional carbon emission reduction potential is still unknown. Thus, we develop a method to predict the long-term regional carbon emission reduction potential by retrofitting commercial buildings. School buildings in hot climate zones in the continental U.S. are selected as an example. The results show that the aggregated carbon emission reduction potential of school buildings in that region reduces from 3.33 to 2.01 megatons from 2024 to 2050 due to the increased penetration of renewable energy.

building energy simulation↗
DOE OSTI2020

EMS-Induced Mutagenesis of Clostridium carboxidivorans for Increased Atmospheric CO 2 Reduction Efficiency and Solvent Production

Clostridium carboxidivorans (P7) is one of the most important solvent-producing bacteria capable of fermenting syngas (CO, CO 2 , and H 2 ) to produce chemical commodities when grown as an autotroph. This study aimed to develop ethyl methanesulfonate (EMS)-induced P7 mutants that were capable of growing in the presence of CO 2 as a unique source of carbon with increased solvent formation and atmospheric CO 2 reduction to limit global warming. Phenotypic analysis including growth and end product characterization of the P7 wild type (WT) demonstrated that this strain grew better at 25 °C than 37 °C when CO 2 served as the only source of carbon. In the current study, 55 mutagenized P7-EMS mutants were developed by using 100 mM and 120 mM EMS. Interestingly, using a forward genetic approach, three out of the 55 P7-EMS mutants showed a significant increase in ethanol, butyrate, and butanol production. The three P7-EMS mutants presented on average a 4.68-fold increase in concentrations of ethanol when compared to the P7-WT. Butyric acid production from 3 P7-EMS mutants contained an average of a 3.85 fold increase over the levels observed in the P7-WT cultures under the same conditions (CO 2 only). In addition, one P7-EMS mutant presented butanol production (0.23 ± 0.02 g/L), which was absent from the P7-WT under CO 2 conditions. Most of the P7-EMS mutants showed stability of the obtained end product traits after three transfers. Most importantly, the amount of reduced atmospheric CO 2 increased up to 8.72 times (0.21 g/Abs) for ethanol production and up to 8.73 times higher (0.16 g/Abs) for butyrate than the levels contained in the P7-WT. Additionally, to produce butanol, the P7-EMSIII-J mutant presented 0.082 g/Abs of CO 2 reduction. This study demonstrated the feasibility and effectiveness of employing EMS mutagenesis in generating solvent-producing anaerobic bacteria mutants with improved and novel product formation and increased atmospheric CO 2 reduction efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

New Spectroelectrochemical Insights into Manganese and Rhenium Bipyridine Complexes as Catalysts for the Electrochemical Reduction of Carbon Dioxide

This study aimed to demonstrate the behavior of different complexes using IR spectroelectrochemistry (SEC), a technique that combines IR spectroscopy with electrochemistry. Four different Mn and Re catalysts for electrochemical CO 2 reduction were studied in dry acetonitrile. In the case of Mn(apbpy)(CO) 3 Br (apbpy = 4(4-aminophenyl)-2,2'-bipyridine), SEC suggested that a very slow catalytic reduction of CO 2 also occurs in acetonitrile in the absence of proton donors, but at rather negative potentials. In contrast, the corresponding Re(apbpy)(CO) 3 Br clearly demonstrated slow catalytic conversion at the first reduction potential. Switching to saturated CO 2 solutions in a mixture of acetonitrile and 5% water as a proton donor, the SEC of Mn(apbpy)(CO) 3 Br displayed a faster catalytic behavior.

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

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗
DOE OSTI2021

Site‐Specific Reduction‐Induced Hydrogenation of a Helical Bilayer Nanographene with K and Rb Metals: Electron Multiaddition and Selective Rb + Complexation

Abstract The chemical reduction of π‐conjugated bilayer nanographene 1 (C 138 H 120 ) with K and Rb in the presence of 18‐crown‐6 affords [K + (18‐crown‐6)(THF) 2 ][{K + (18‐crown‐6)} 2 (THF) 0.5 ][C 138 H 122 3− ] ( 2 ) and [Rb + (18‐crown‐6) 2 ][{Rb + (18‐crown‐6)} 2 (C 138 H 122 3− )] ( 3 ). Whereas K + cations are fully solvent‐separated from the trianionic core thus affording a “naked” 1 .3 − anion, Rb + cations are coordinated to the negatively charged layers of 1 .3 − . According to DFT calculations, the localization of the first two electrons in the helicene moiety leads to an unprecedented site‐specific hydrogenation process at the carbon atoms located on the edge of the helicene backbone. This uncommon reduction‐induced site‐specific hydrogenation provokes dramatic changes in the (electronic) structure of 1 as the helicene backbone becomes more compressed and twisted upon chemical reduction, which results in a clear slippage of the bilayers.

Zhou, Zheng↗
DOE OSTI2022

Aqueous Photoelectrochemical CO 2 Reduction to CO and Methanol over a Silicon Photocathode Functionalized with a Cobalt Phthalocyanine Molecular Catalyst

Abstract We report a precious‐metal‐free molecular catalyst‐based photocathode that is active for aqueous CO 2 reduction to CO and methanol. The photoelectrode is composed of cobalt phthalocyanine molecules anchored on graphene oxide which is integrated via a (3‐aminopropyl)triethoxysilane linker to p‐type silicon protected by a thin film of titanium dioxide. The photocathode reduces CO 2 to CO with high selectivity at potentials as mild as 0 V versus the reversible hydrogen electrode (vs RHE). Methanol production is observed at an onset potential of −0.36 V vs RHE, and reaches a peak turnover frequency of 0.18 s −1 . To date, this is the only molecular catalyst‐based photoelectrode that is active for the six‐electron reduction of CO 2 to methanol. This work puts forth a strategy for interfacing molecular catalysts to p‐type semiconductors and demonstrates state‐of‐the‐art performance for photoelectrochemical CO 2 reduction to CO and methanol.

Shang, Bo↗
DOE OSTI2020

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗