Engineering Papers⌕ Search

SEARCH · Engineering Papers

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.

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

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

West Virginia University Industrial Assessment Center (Final Progress Report)

The Industrial Assessment Center at West Virginia University has been successful in workforce development, and in generation of energy savings for manufacturing facilities during the period 2016 to 2021. Graduate and undergraduate students have benefited from energy assessment experience and most of them have found good positions as energy engineers and analysts in the industrial sector. Several peer reviewed research papers in archival journals as well as conference papers on the topic of energy engineering and assessment have been published. The implemented energy savings for manufacturing facilities have been significant in the areas of lighting, compressed air, process heating, steam, HVAC, chillers and cooling towers, and motors. In addition, water use reduction, smart manufacturing applications to save energy, cyber security evaluation, energy management, productivity improvements and waste reduction opportunities that lead to energy intensity reductions have been explored. The students have obtained an opportunity to interact with energy efficiency and productivity improvement professionals at various conferences and workshops and their research has generated important results. In summary, the West Virginia University Industrial Assessment Center (WVU-IAC) has fulfilled its mission in regard to workforce development, energy efficiency for manufacturing facilities, and laid a strong platform enhancing sustainability through reductions in carbon emissions achieved through energy efficiency and energy management initiatives and reductions in water usage and waste reduction. During the project period (2016-2021) the WVU-IAC has made numerous energy efficiency, water use reduction, waste reduction, and productivity improvement recommendations, a significant number of them having been implemented by the manufacturing facilities. The research adds significant understanding to the area of energy efficiency, water and waste reduction, and productivity improvement. The technical effectiveness and economic feasibility of the methods and techniques investigated and demonstrated through this project have been exemplary, resulting in significant recommended and implemented resource savings and reductions in carbon emissions. The project has been of significant benefit to the public owing to replication of results within the industrial sector, thus reducing operating costs for businesses that result in increase of growth and employment, as well as community benefits in terms of reductions in carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Deep Reinforcement Learning Based HVAC Control for Reducing Carbon Footprint of Buildings

In this paper, we present our work on deep reinforcement learning (DRL) based intelligent control of Heating, Ventilation, and Air Conditioning (HVAC) with the goal of reducing carbon emission. We performed this task using 1) Marginal Operating Emission Rates (MOER), where the objective was to shift the demand to the low emission period of the day and 2) Time-Of-Use (TOU) demand-response price where the objective was to shift the demand to low price period of the day. This was achieved by learning an optimal pre-cooing strategy. We found the carbon emission reduction in the range of 6%-16% depending on the opportunity presented by the MOER signal. Similarly, we observed the carbon emission reduction in the range of 23%-29% during the peak price period when TOU price was used. The results clearly demonstrated the applicability of our approach in reducing the carbon footprint of the building.

carbon emission↗
DOE OSTI2022

Mechanistic insights into metal, nitrogen doped carbon catalysts for oxygen reduction: progress in computational modeling

We report metal and nitrogen doped carbon materials (denoted as M–N–C) synthesized through high-temperature pyrolysis have been found to exhibit activity for oxygen reduction reaction (ORR) approaching that of Pt and electrochemical stability higher than previous MN 4 -containing macrocyclic molecular catalysts. Tremendous efforts have thus been devoted to the advancement of M–N–C catalysts as an economical alternative to Pt-based catalysts for proton exchange membrane fuel cell cathodes with a focus on simultaneously improving activity and stability. To this end, novel computational modeling techniques have been developed and applied to acquire knowledge crucial for accelerating the pace of M–N–C catalyst development. In this review, recent progress in computational method development, as well as the predictions of chemical structure of active sites, reaction pathways, ORR kinetics, and catalyst stability in electrochemical environments, are critically surveyed. Moreover, the crucial role of computational modeling to elucidate the functional mechanism of M–N–C catalysts for ORR in acid media and enable rational design of M–N–C catalysts is discussed with a visionary outlook for the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗
DOE OSTI2023

X-ray Absorption Spectroscopy Studies of a Molecular CO 2 -Reduction Catalyst Deposited on Graphitic Carbon Nitride

Metal-ligand complexes have been extensively explored as well-defined molecular catalysts in small molecule activation reactions such as carbon dioxide (CO 2 ) reduction. Many hybrid photocatalysts have been prepared by coupling such complexes with photoactive surfaces for use in solar CO 2 reduction. In this work, we employ X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopies, density functional theory (DFT) and computational XANES modeling to interrogate the structure of a hybrid photocatalyst consisting of a macrocyclic cobalt complex deposited on graphitic carbon nitride (C 3 N 4 ). Results show that the cobalt complex binds on C 3 N 4 through surface OH or NH 2 groups. By refining the local geometry and binding sites of this well-defined molecular cobalt complex on C 3 N 4 , here we established an important benchmark for modeling a large class of molecular catalysts that can be adapted to in situ/operando studies and further enhanced by applying chemometrics-based approaches and machine learning methods of XANES data analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phase-enabled metal-organic framework homojunction for highly selective CO 2 photoreduction

Conversion of clean solar energy to chemical fuels is one of the promising and up-and-coming applications of metal–organic frameworks. However, fast recombination of photogenerated charge carriers in these frameworks remains the most significant limitation for their photocatalytic application. Although the construction of homojunctions is a promising solution, it remains very challenging to synthesize them. Herein, we report a well-defined hierarchical homojunction based on metal–organic frameworks via a facile one-pot synthesis route directed by hollow transition metal nanoparticles. The homojunction is enabled by two concentric stacked nanoplates with slightly different crystal phases. The enhanced charge separation in the homojunction was visualized by in-situ surface photovoltage microscopy. Moreover, the as-prepared nanostacks displayed a visible-light-driven carbon dioxide reduction with very high carbon monooxide selectivity, and excellent stability. Our work provides a powerful platform to synthesize capable metal–organic framework complexes and sheds light on the hierarchical structure-function relationships of metal–organic frameworks.

14 SOLAR ENERGY↗
DOE OSTI2022

Pathways to a net-zero-carbon water sector through energy-extracting wastewater technologies

The energy-consuming and carbon-intensive wastewater treatment plants could become significant energy producers and recycled organic and metallic material generators, thereby contributing to broad sustainable development goals, the circular economy, and the water-energy-sanitation-food-carbon nexus. This review provides an overview of the waste(water)-based energy-extracting technologies, their engineering performance, techno-economic feasibility, and environmental benefits. Here, we propose four crucial strategies to achieve net-zero carbon along with energy sufficiency in the water sector, including (1) improvement in process energy efficiency; (2) maximizing on-site renewable capacities and biogas upgrading; (3) harvesting energy from treated effluent; (4) a new paradigm for decentralized water-energy supply units.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The role of atomic carbon in directing electrochemical CO (2) reduction to multicarbon products

Electrochemical reduction of carbon-dioxide/carbon-monoxide (CO (2) R) to fuels and chemicals presents an attractive approach for sustainable chemical synthesis, but it also poses a serious challenge in catalysis. Understanding the key aspects that guide CO (2) R towards value-added multicarbon (C 2+ ) products is imperative in designing an efficient catalyst. Herein, we identify the critical steps toward C 2 products on copper through a combination of energetics from density functional theory and micro-kinetic modeling. We elucidate the importance of atomic carbon in directing C 2+ selectivity and how it introduces surface structural sensitivity on copper catalysts. Overall, this insight enables us to propose two simple thermodynamic descriptors that effectively identify C 2+ selectivity on metal catalysts beyond copper and hence it defines an intelligible protocol to screen for materials that selectively catalyze CO (2) to C 2+ products.

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

Bioinspired and biomolecular catalysts for energy conversion and storage

Metalloenzymes are remarkable for facilitating challenging redox transformations with high efficiency and selectivity. In the area of alternative energy, scientists aim to capture these properties in bioinspired and engineered biomolecular catalysts for the efficient and fast production of fuels from low-energy feedstocks such as water and carbon dioxide. In this short review, efforts to mimic biological catalysts for proton reduction and carbon dioxide reduction are highlighted. Two important recurring themes are the importance of the microenvironment of the catalyst active site and the key role of proton delivery to the active site in achieving desired reactivity. As a result, perspectives on ongoing and future challenges are also provided.

14 SOLAR ENERGY↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2025

A control-inspired approach for energy transition planning under uncertainty

As the global carbon footprint continues to grow, many countries are implementing carbon emission reduction policies which have incentivized the expansion of low-carbon and renewable technologies. However, the speed and scale of deployment falls short of that needed to meet climate goals. Energy system models serve as key tools for guiding investment decisions and helping policymakers evaluate the effects of various policies on the development of an energy system. This study focuses on the energy system of the United States and builds upon prior work by incorporating more geographic granularity to account for the trade of commodities and addresses transmission congestion through electricity price adjustments. Furthermore, real-world characteristics, such as delays in constructing new liquid fuel production and electricity generation facilities, are integrated using a sequential decision-making approach that better reflects how decisions can be updated as uncertainties unfold. Results demonstrate that stochastic programming combined with sequential decision-making produces energy transition pathways that are robust to multiple uncertain futures. Additionally, considering real-world characteristics significantly impacts the deployment of renewable technologies and the ability to meet carbon emission reduction goals while also reliably meeting demand. These findings highlight the importance of accounting for uncertainty and real-world characteristics to avoid overly optimistic projections in energy system planning.

energy systems↗
DOE OSTI2020

An Ion-Imprinting Derived Strategy to Synthesize Single-Atom Iron Electrocatalysts for Oxygen Reduction

Carbon-based single-atom catalysts (CSACs) have recently received extensive attention in catalysis research. However, the preparation process of CSACs involves a high-temperature treatment, during which metal atoms are mobile and aggregated into nanoparticles, detrimental to the catalytic performance. Herein, an ion-imprinting derived strategy is proposed to synthesize CSACs, in which isolated metal-nitrogen-carbon (Me-N 4 -C x ) moiety covalently binds oxygen atoms in Si-based molecular sieve frameworks. Such a feature makes Me-N 4 -C x moiety well protected/confined during the heat treatment, resulting in the final material enriched with single-atom metal active sites. As a proof of concept, a single-atom Fe-N-C catalyst is synthesized by using this ion-imprinting derived strategy. Finally, experimental results and theoretical calculations demonstrate high concentration of single FeN 4 active sites distributed in this catalyst, resulting in an outstanding oxygen reduction reaction (ORR) performance with a half-wave potential of 0.908 V in alkaline media.

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

Promoting Atomically Dispersed MnN 4 Sites via Sulfur Doping for Oxygen Reduction: Unveiling Intrinsic Activity and Degradation in Fuel Cells

Carbon supported and nitrogen coordinated single Mn site catalysts (Mn-N-C) catalysts are the most desirable platinum group metal (PGM)-free cathode catalysts for proton exchange membrane fuel cells (PEMFCs) due to their insignificant Fenton reactions (vs. Fe), earth abundances (vs. Co) and encouraging activity and stability. However, current Mn-N-C catalysts suffer from high over-potential due to low intrinsic activity and less dense MnN 4 sites. Herein, we present sulfur-doped Mn-N-C catalyst (Mn-N-C-S) synthesized through an effective adsorption-pyrolysis process. Using electron microscopy and X-ray absorption spectroscopy (XAS) techniques, we verify the uniform dispersion of MnN 4 sites and confirm the effect of S doping on the Mn-N coordination. The Mn-N-C-S catalyst exhibits a favorable oxygen reduction reaction (ORR) activity in acidic media relative to the S-free Mn-N-C catalyst. The corresponding membrane electrode assembly (MEA) generated a remarkable performance with a peak power density of 500 mW cm -2 under a realistic H 2 /air environment. The constant voltage tests of fuel cells confirm the much-enhanced stability of the Mn-N-C-S catalyst compared to the Fe-N-C and Fe-N-C-S catalysts. The electron microscopy and Fourier transform XAS analysis provide insights into catalyst degradation associated with Mn oxidation and agglomeration. The theoretical calculation elucidates that the promoted ORR activity is mainly attributed to the spatial effect stemmed from the repulsive interaction between the ORR intermediates and adjacent S do-pants.

25 ENERGY STORAGE↗
DOE OSTI2023

Electrochemical Reduction of Flue Gas Carbon Dioxide to Commercially Viable C2-C4 Products (Final Report)

This is the final scientific/technical report for a DOE project focused on the electrochemical conversion of CO 2 in non-aqueous solvents to novel products. Electrochemical reduction of CO 2 provides an attractive route to produce valuable fuels and chemicals that can simultaneously lower greenhouse gas emissions when powered by renewable electricity. While recent technological advances have shown the feasibility of industrial CO 2 electroreduction, many challenges remain to improve this technology and expand the list of economically viable products. The vast majority of electrochemical CO 2 reduction research has been conducted in aqueous media under neutral to alkaline conditions, leading to commonly reported products including carbon monoxide, formic acid, methane, methanol, ethylene, acetic acid, and ethanol. In comparison, non-aqueous media for CO 2 reduction has been underexplored but represents a possible avenue to yield new products and improved operating conditions. The aim of the project was to convert waste CO 2 in the form of flue gas to a multicarbon C2 - C4 chemical product in a reactor designed to achieve economically competitive values of current density and selectivity. The project strived to advance the technology readiness of an electrochemical CO 2 reduction process in alcohol solvents from the proof-of-concept stage to a device capable of meeting performance metrics for commercial viability. In the initial plan, the University of Louisville researchers were to focus on investigating the electrochemical process and improving the faradaic efficiency for novel C2 – C4 species, while also working on a parallel effort to build a practical electrolysis reactor to markedly increase the CO 2 reduction current density. The reactor development effort also aimed to engineer a dual-electrolyte feed strategy with non-aqueous catholyte and aqueous anolyte to promote water oxidation as the coupling anodic half-reaction to enable a sustainable and economical overall process. At the outset, the University of North Dakota was to investigate the feasibility of operating directly from coal-derived flue gas without separate capture and purification. The research team sought to determine impurity effects and test mitigation strategies, as well as engineer the gaseous feed system for high reactor tolerance to lower CO 2 concentration. In the last half year of the project, the focus was planned to shift to integrating the advances in the catalysis, electrochemical conditions, reactor design, and flue gas compatibility into a fully functional device and improve it for maximum current density and faradaic efficiency for C2 – C4 species. Knowledge of the full system components, constraints, and maximum performance was then to be used as the basis for a thorough technoeconomic analysis (TEA) and life cycle analysis (LCA) at the end of the project.

01 COAL, LIGNITE, AND PEAT↗