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Results for “carbon 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.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Carbonic Anhydrase Variants Catalyze the Reduction of Dialkyl Ketones with High Enantioselectivity

Abstract Human carbonic anhydrase II (hCAII) naturally catalyzes the reaction between two achiral molecules—water and carbon dioxide—to yield the achiral product carbonic acid through a zinc hydroxide intermediate. We have previously shown that a zinc hydride, instead of a hydroxide, can be generated in this enzyme to create a catalyst for the reduction of aryl ketones. Dialkyl ketones are more challenging to reduce, and the enantioselective reduction of dialkyl ketones with two alkyl groups that are similar in size and electronic properties, is a particularly challenging transformation to achieve with high activity and selectivity. Here, we show that hCAII, as well as a double mutant of it, catalyzes the enantioselective reduction of dialkyl ketones with high yields and enantioselectivities, even when the two alkyl groups are similar in size. We also show that variants of hCAII catalyze the site‐selective reduction of one ketone over the other in an unsymmetrical aliphatic diketone. Computational docking of a dialkyl ketone to variants of hCAII containing the zinc hydride provides insights into the origins of the reactivity of various substrates and the high enantioselectivity of the transformations and show how a confined environment can control the enantioselectivity of an abiological intermediate.

Chen, Reichi↗
DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
DOE OSTI2020

Large Trees Dominate Carbon Storage in Forests East of the Cascade Crest in the United States Pacific Northwest

Large-diameter trees store disproportionally massive amounts of carbon and are a major driver of carbon cycle dynamics in forests worldwide. In the temperate forests of the western United States, proposed changes to Forest Plans would significantly weaken protections for a large portion of trees greater than 53 cm (21 inches) in diameter (herein referred to as “large-diameter trees”) across 11.5 million acres (~4.7 million ha) of National Forest lands. This study is among the first to report how carbon storage in large trees and forest ecosystems would be affected by a proposed policy. We examined the proportion of large-diameter trees on National Forest lands east of the Cascade Mountains crest in Oregon and Washington, their contribution to overall aboveground carbon (AGC) storage, and the potential reduction in carbon stocks resulting from widespread harvest. We analyzed forest inventory data collected on 3,335 plots and found that large trees play a major role in the accumulated carbon stock of these forests. Tree AGC (kg) increases sharply with tree diameter at breast height (DBH; cm) among five dominant tree species. Large trees accounted for 2.0 to 3.7% of all stems (DBH ≥ 1” or 2.54 cm) among five tree species; but held 33 to 46% of the total AGC stored by each species. Pooled across the five dominant species, large trees accounted for 3% of the 636,520 trees occurring on the inventory plots but stored 42% of the total AGC. A recently proposed large-scale vegetation management project that involved widespread harvest of large trees, mostly grand fir, would have removed ~44% of the AGC stored in these large-diameter trees, and released a large amount of carbon dioxide to the atmosphere. Given the urgency of keeping additional carbon out of the atmosphere and continuing carbon accumulation from the atmosphere to protect the climate system, it would be prudent to continue protecting ecosystems with large trees for their carbon stores, and also for their co-benefits of habitat for biodiversity, resilience to drought and fire, and microclimate buffering under future climate extremes.

21-inch rule↗
DOE OSTI2022

Trends in oxygenate/hydrocarbon selectivity for electrochemical CO (2) reduction to C 2 products

The electrochemical conversion of carbon di-/monoxide into commodity chemicals paves a way towards a sustainable society but it also presents one of the great challenges in catalysis. Herein, we present the trends in selectivity towards specific dicarbon oxygenate/hydrocarbon products from carbon monoxide reduction on transition metal catalysts, with special focus on copper. We unveil the distinctive role of electrolyte pH in tuning the dicarbon oxygenate/hydrocarbon selectivity. The understanding is based on density functional theory calculated energetics and microkinetic modeling. We identify the critical reaction steps determining selectivity and relate their transition state energies to two simple descriptors, the carbon and hydroxide binding strengths. The atomistic insight gained enables us to rationalize a number of experimental observations and provides avenues towards the design of selective electrocatalysts for liquid fuel production from carbon di-/monoxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

A Biochemical Magic Frequency

Life is composed principally of four classes of biomolecules - protein, nucleic acid, polysaccharide and lipid. Using 1) estimates of the reducing equivalents (electron pairs) needed to synthesize these biomolecules from carbon dioxide, and 2) measurements of the molecular composition of different organisms, we calculated the average number of electron pairs required for the reduction of carbon dioxide to biological carbon (electron pairs/carbon atom). These calculations showed that the carbon of the Earths biosphere is at the reduction level of formaldehyde that requires 2 electron pairs/carbon atom to be synthesized from carbon dioxide. This was also the reduction level of carbon of individual organisms, except for those that stored large amounts of fuel as lipid. Since this chemical property of life is easily discovered and probably universal, it's most likely known by other intelligent life in the universe. It could be the one thing we know about other carbon-based life in the universe, and the one thing that other intelligent life knows about us. We believe this common knowledge that formaldehyde represents the reduction level of life's carbon could lead to the selection of the 72.83814 GHz line of the 0,0,0,1,0,1 ground-state rotational transition of formaldehyde as a frequency for interstellar communication.

Weber, Arthur L.↗
DOE OSTI2023

A Deep Learning-Based Workflow for Fast Prediction of 3D State Variables in Geological Carbon Storage: A Dimension Reduction Approach

In this study, we used deep learning techniques, which are a form of artificial intelligence, to create fast and effective models for predicting how fluids flow in underground geological formations. This is important for managing geological carbon storage, a method used to fight climate change by storing carbon dioxide underground. The challenge lies in the complex nature of these underground spaces and the large amount of data needed to accurately simulate them. To overcome these issues, we developed a new workflow that reduces the data’s complexity before training the deep learning model and then reconstructs the predicted results in their original form. We also proposed a unique approach to handle the specific complexities found in 3D saturation fields, a crucial aspect of fluid flow prediction. We tested our method using real-world data from the Gulf of Mexico. Our results show that our approach not only accurately predicts fluid behavior but also significantly reduces computation time. This will greatly improve real-time decision-making and risk assessment in large-scale geological carbon storage operations.

Wang, Hongsheng↗
DOE OSTI2024

Solvent-free synthesis of Co single atom and nanocluster decorated N-doped carbon for efficient oxygen reduction

The advancement of efficient, cheap, and durable catalysts for oxygen reduction reaction (ORR) to substitute Pt/C in metal-air batteries is of paramount importance. However, traditional solvent-based methods fall short in terms of environmental benign and scalability. Herein, a solvent-free organic-inorganic self-assembly approach is explored to construct cobalt single atom and cobalt nanocluster decorated nitrogen-doped porous carbon spheres (Co-SA/NC@NCS). The solvent-free synthesis demonstrates an impressively high yield (282 g/L) and the resultant Co-SA/NC@NCS possesses a high N content (6.9 wt%). Density functional theory calculations disclose that the Co-SAs and Co-NCs are able to optimize the surface oxygen adsorption capability and enhance the conductivity of the NCS, thereby facilitating the ORR performance. Here, the solvent-free synthesis is also feasible for the synthesis of other non-noble metal element (Fe, Ni, and Zn) decorated nitrogen-doped porous carbon spheres.

Nitrogen-doped carbon↗
DOE OSTI2022

Carbon supports for oxygen reduction catalysts

The invention provides a method of making a electrocatalyst from waste tires. The method comprises the steps of providing rubber pieces; optionally contacting the rubber pieces with a sulfonation bath to produce sulfonated rubber; pyrolyzing the rubber to produce tire-derived carbon composite comprising carbon black, wherein the pyrolyzing comprises heating to at least 200° C.-2400° C.; activating the tire-derived carbon composite by contacting the tire-derived carbon composite with an alkali anion compound to provide activated tire-derived carbon supports; and loading the activated carbon-based supports with platinum cubes. In another embodiment, the tire-derived carbon composite is activated by annealing in a carbon dioxide atmosphere.

Naskar, Amit K.↗
DOE OSTI2025

Multistep catalytic abiotic CO2 conversion to sugars through C1 intermediates

Carbon dioxide (CO2) to multicarbon (Cn) upgrading for commodity chemicals, fuel production, or artificial food synthesis using renewable energy input is a golden target for researchers in sustainable carbon emission reduction. Here, we explore and analyze a flexible modular roadmap for the task, utilizing sequential electro-, photo-, and organocatalysis to develop a strategy for CO2 conversion using the key and elusive formaldehyde precursor of interest for sugar generation. We study the electrochemical carbon dioxide reduction reaction to methanol in a flow cell and its discontinuous photooxidation to formaldehyde (PMOR) with excellent selectivity. Utilizing a highly active N-heterocyclic carbene catalyst enables tunable generation of C4-C6 aldoses without undesirable byproducts, with carbon conversion yield reaching 60 to 80% for desired pentose, tetrose, and triose product mixtures and over 20% for hexose. This approach presents a roadmap for CO2 valorization, aiming to bridge carbon waste streams with sustainable sugar synthesis and opening broad avenues for green chemical production.

CO2 valorization↗
DOE OSTI2022

Feasibility Study of Real-Time Carbon Emission Responsive Electric Vehicle Charging Control in Buildings: Preprint

With the progressing electrification of the transportation sector, the source of carbon emissions is gradually shifting from fossil fuel to grid electricity because of electric vehicles (EVs). The carbon intensity of the grid can fluctuate significantly within hours due to the time-varying power generation mix. Therefore, shifting EV charging loads to cleaner hours in response to the carbon intensity signals can reduce carbon emissions. Existing EV charging control methods typically consider the electricity price or the available generation by distributed energy resources (e.g., photovoltaics) to inform decision-making. Such methods tend to reduce energy costs but may neglect the environmental impact of EV charging activities. We propose and compare four carbon emission responsive EV charging controllers with various control rules. The proposed controllers are evaluated based on simulation experiments using metrics such as carbon emission reduction potential, state of charge (SOC) at departure, and peak demand. We found that the need of EV owners to have full batteries at departure could lead to an emission increase when the curtailed EV charge was compensated before departure. Further, up to 12.7% of carbon emission reduction can be achieved if the EV owners reduce the target SOC at departure by less than 15%.

carbon emission↗
DOE OSTI2020

Biofuels Policies That Have Encouraged Their Production and Use: An International Perspective

This study evaluated the effectiveness of technology-push and market-pull policies in encouraging the production and use of biofuels in 15 countries including major biofuels producers. Biofuels production and consumption data for the 12-year period of 2006-2017 showed that in most of the surveyed countries, biofuels policies played an important role in developing and growing regional and national biofuels markets. Blending mandates continue to be the main market-pull policy used to create and expand biofuels markets. Countries with a mixture of market-pull and technology-push policy instruments have been most successful at increasing biofuels production and use and also developing and deploying less mature advanced biofuels. Most policies have primarily promoted the production and use of biofuels for road transport with key long-distance transport sectors (aviation and shipping) drawing less policy attention despite being significant fuel consumers and carbon emitters. While many older policies were originally developed to promote energy security, more recent policies, such as low carbon fuel standard, have reduction in the carbon intensity of transportation fuels as a primary goal. While policies have been essential in promoting the on-going growth of biofuels, they have not been sufficient to drive the level of development needed to decarbonize the transport sector.

biofuels for transport↗
NASA NTRS1988

High temperature solid lubrication by catalytically generated carbon

The wear process in bearings generates a clean active surface. Carbon is known to form readily on catalytic surfaces through the reduction of carbon oxides or hydrocarbon. Carbon, through the adsorption of hydrocarbons, water vapor, or oxygen, becomes an effective lubricant. If these three phenomena can be made to work together, a new concept of high temperature lubrication would be available. This paper presents laboratory investigations towards the development of this concept. Carbon has been successfully produced through catalytic reduction of ethylene on a variety of metallic and ceramic surfaces containing nickel. This carbon has been shown to reduce friction at a sliding interface at elevated temperatures.

Lauer, James L.↗
DOE OSTI2025

Quantitative Imaging of Cobalt Phthalocyanine Distribution on Carbon Nanotubes: A Deep Learning Approach to Catalyst Characterization

Electrochemical reduction of carbon dioxide (CO 2 ) offers a pathway to valuable products, with catalysts playing a crucial role. This study investigates the distribution of cobalt tetraaminophthalocyanine (CoPc-NH 2 ) immobilized on carbon nanotubes (CNTs), utilizing high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to characterize CoPc-NH 2 distribution. A challenge in the quantitative HAADF-STEM analysis is the introduction of bias from manual Co atom identification. To address this, we developed and trained a convolutional neural network (CNN) using a data set generated from images of CoPc-NH 2 /CNT samples with varying Co loadings. The CNN, implemented in TensorFlow and Keras, facilitated Co atom detections. Analysis of the CNN-generated data confirmed a correlation between Co loading and surface density, consistent with findings from UV–vis spectroscopy. Furthermore, the application of Ripley’s L(d) function highlighted the presence of slight Co atom clustering. Furthermore, this work demonstrates the utility of the combined HAADF-STEM and CNN approach for providing spatially resolved information about catalyst distribution on nonplanar supports, revealing structural details that are typically lost through other characterization methods.

HAADF-STEM↗
DOE OSTI2022

Metallene-related materials for electrocatalysis and energy conversion

As a member of graphene analogs, metallenes are a class of two-dimensional materials with atomic thickness and well-controlled surface atomic arrangement made of metals or alloys. When utilized as catalysts, metallenes exhibit distinctive physicochemical properties endowed from the under-coordinated metal atoms on the surface, making them highly competitive candidates for energy-related electrocatalysis and energy conversion systems. Significantly, their catalytic activity can be precisely tuned through the chemical modification of their surface and subsurface atoms for efficient catalyst engineering. Here, this minireview summarizes the recent progress in the synthesis and characterization of metallenes, together with their use as electrocatalysts toward reactions for energy conversion. In the Synthesis section, we pay particular attention to the strategies designed to tune their exposed facets, composition, and surface strain, as well as the porosity/cavity, defects, and crystallinity on the surface. We then discuss the electrocatalytic properties of metallenes in terms of oxygen reduction, hydrogen evolution, alcohol and acid oxidation, carbon dioxide reduction, and nitrogen reduction reaction, with a small extension regarding photocatalysis. At the end, we offer perspectives on the challenges and opportunities with respect to the synthesis, characterization, modeling, and application of metallenes.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Prototype Bosch CO2 reduction subsystem for the RLSE experiment

Requirements for the Bosch carbon dioxide reduction subsystem were established in a study of regenerative life support evaluation experiments. A detailed design is presented including a schematic, components list and characteristics, requirements summaries, and complete definition of life systems' advanced control/monitor instrumentation applied to the Bosch subsystem. Design information needed to proceed with the final design and fabrication of a preprototype system is presented.

Heppner, D. B.↗
DOE OSTI2021

Electrochemical CO 2 Reduction Reaction over Cu Nanoparticles with Tunable Activity and Selectivity Mediated by Functional Groups in Polymeric Binder

Electrochemical carbon dioxide reduction reaction (CO 2 RR) using copper (Cu)-based catalysts has received significant attention mainly because Cu is an element capable of producing hydrocarbons and oxygenates. One possible way to control the CO 2 RR performance at the electrode interface is by modifying catalysts with specific functional groups of different polymeric binders, which are necessary components in the process of electrode fabrication. However, the modification effect of the key functional groups on the CO 2 RR activity and selectivity is poorly understood over Cu-based catalysts. In this work, the role of functional groups (e.g., -COOH and -CF 2 groups) in hydrophilic and hydrophobic polymeric binders on the CO 2 RR of Cu-based catalysts is investigated using a combination of electrochemical measurements, in-situ characterization and density functional theory (DFT) calculations. DFT results reveal that functional groups influence the binding energies of key intermediates involved in both CO 2 RR and the competing hydrogen evolution reaction, consistent with experimental observation of binder-dependent product distributions among formic acid, CO, CH 4 , and H 2 . This study provides a fundamental understanding that the selection of desired polymeric binders is a useful strategy for tuning the CO 2 RR activity and selectivity.

25 ENERGY STORAGE↗
DOE OSTI2022

Catalysts by pyrolysis: Direct observation of transformations during re-pyrolysis of transition metal-nitrogen-carbon materials leading to state-of-the-art platinum group metal-free electrocatalyst

Transition metal-nitrogen-carbon (M-N-C) materials have been the focus of scientists’ efforts to address the rising need for earth-abundant materials solutions for energy technology and decarbonization of the economy. They are viewed as one of the most promising candidates to replace platinum group metal (PGM) catalysts in the fuel cell and energy conversion fields, including the application of oxygen reduction reaction, carbon dioxide reduction reaction, and nitrogen reduction reaction. In the effort to improve M-N-C materials properties and achieve atomic dispersity of the transition metal in the carbonaceous matrix, a re-pyrolysis process has been proposed. This secondary heat treatment process of already obtained primary pyrolysis-derived M-N-C materials has been widely reported to substantially improve the electrochemical performance and operational stability of the catalysts. Here, we report a systematic investigation of this process used on samples of templated M-N-C catalysts to obtain state-of-the-art catalysts via in situ heating X-ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy (STEM), energy-dispersive X-ray spectroscopy (EDS), electron energy loss spectroscopy (EELS), X-ray diffraction (XRD), and X-ray computed tomography (CT) characterization methods. It is found that the re-pyrolysis of M-N-C materials could result in the partial amorphization of the carbonaceous substrate. It causes the rearrangement and transformation of multitudinous N moieties, leading to optimization of their morphological display and association with atomically dispersed transition metal dopants. Ultimately, the re-pyrolysis results in an increase in uniformity of the active Fe-Nx sites distribution without the formation of nano-crystalline phases (metallic or carbide) and with overall preservation of the morphology of the carbonaceous framework achieved during the first formative pyrolysis step of the templated synthesis. Finally, these observations provide confirmation that empirically established re-pyrolysis is recommended to be used on all M-N-C materials despite the different synthesis routes to obtain a practical advanced catalytic material.

36 MATERIALS SCIENCE↗