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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Graphene Oxide Catalyzed C-H Bond Activation: The Importance Oxygen Functional Groups for Biaryl Construction

A heterogeneous, inexpensive and environment-friendly carbon catalytic system was developed for the C-H bond arylation of benzene resulting in the subsequent formation of biaryl compounds. The oxygen-containing groups on these graphene oxide sheets play an essential role in the observed catalytic activity. The catalytic results of model compounds and DFT calculations show that these functional groups promote this reaction by stabilization and activation of K ions at the same time of facilitating the leaving of I. And further mechanisms studies show that it is the charge induced capabilities of oxygen groups connected to specific carbon skeleton together with the giant π-reaction platform provided by the π-domain of graphene that played the vital roles in the observed excellent catalytic activity. D. Mei acknowledges the support from the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory.

Arylation reaction↗
DOE OSTI2015

Synergistic Effect of Nitrogen in Cobalt Nitride and Nitrogen-Doped Hollow Carbon Spheres for Oxygen Reduction Reaction

The need for inexpensive and high-activity oxygen reduction reaction (ORR) electrocatalysts has attracted considerable research interest over the past years. Here we report a novel hybrid that contains cobalt nitride/nitrogen-rich hollow carbon spheres (CoxN/NHCS) as a high-performance catalyst for ORR. The CoxN nanoparticles were uniformly dispersed and confined in the hollow NHCS shell. The performance of the resulting CoxN/NHCS hybrid was comparable with that of a commercial Pt/C at the same catalyst loading toward ORR, but the mass activity of the former was 5.7 times better than that of the latter. The nitrogen in both CoxN and NHCS, especially CoxN, could weaken the adsorption of reaction intermediates (O and OOH), which follows the favourable reaction pathway on CoxN/NHCS according to the DFT-calculated Gibbs free energy diagrams. Our results demonstrated a new strategy for designing and developing inexpensive, non-precious metal electrocatalysts for next-generation fuels. The authors acknowledge the financial support from the National Basic Research Program (973 program, No. 2013CB733501) and the National Natural Science Foundation of China (No. 21306169, 21101137, 21136001, 21176221 and 91334013). Dr. D. Mei is supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

cobalt nitride↗
DOE OSTI2014

Mechanisms of selective cleavage of C–O bonds in di-aryl ethers in aqueous phase

A novel route for cleaving the C-O aryl ether bonds of p-substituted H-, CH 3 -, and OH- diphenyl ethers has been explored over Ni/SiO 2 catalysts at very mild conditions. The C-O bond of diphenyl ether is cleaved by parallel hydrogenolysis and hydrolysis (hydrogenolysis combined with HO* addition) on Ni. The rates as a function of H 2 pressure from 0 to 10 MPa indicate that the rate-determining step is the C-O bond cleavage on Ni. H* atoms compete with the organic reactant for adsorption leading to a maximum in the rate with increasing H 2 pressure. In contrast to diphenyl ether, hydrogenolysis is the exclusive route for cleaving an ether C-O bond of di-p-tolyl ether to form p-cresol and toluene. 4,4'-dihydroxydiphenyl ether undergoes sequential surface hydrogenolysis, first to phenol and HOC 6 H 4 O* (adsorbed), which is then cleaved to phenol (C 6 H 5 O* with added H*) and H 2 O (O* with two added H*) in a second step. Density function theory supports the operation of this pathway. Notably, addition of H* to HOC 6 H 4 O* is less favorable than a further hydrogenolytic C-O bond cleavage. The TOFs of three aryl ethers with Ni/SiO 2 in water followed the order 4,4'-dihydroxydiphenyl ether (69 h -1 ) > diphenyl ether (26 h -1 ) > di-p-tolyl ether (1.3 h -1 ), in line with the increasing apparent activation energies, ranging from 93 kJ∙mol -1 (4,4'-dihydroxydiphenyl ether) < diphenyl ether (98 kJ∙mol -1 ) to di-p-tolyl ether (105 kJ∙mol -1 ). D.M. thanks the support from the US Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and by the National Energy Research Scientific Computing Center (NERSC). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

Aqueous phase reaction↗
DOE OSTI2022

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dimensionality of atomic configurations to a low dimensional latent space and separate downstream parts map the latent space to predictions of basin class labels and potential energies. Here, the resulting latent space is shown to be an effective low-dimensional representation, capturing the reaction progress and guiding effective umbrella sampling to obtain accurate free energy landscapes. This approach is successfully applied to model systems including a 5D Müller Brown model, a 5D three-well model, the alanine dipeptide in vacuum, and an Au(110) surface reconstruction unit reaction. It enables automated dimensionality reduction for energy controlled reactions in complex systems, offers a unified and data-efficient framework that can be trained with limited data, and outperforms single-task learning approaches, including autoencoders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Dehydration of 1-octadecanol over H-BEA: A combined experimental and computational study

Liquid phase dehydration of 1-octdecanol, which is intermediately formed during the hydrodeoxygenation of microalgae oil, has been explored in a combined experimental and computational study. The alkyl chain of C18 alcohol interacts with acid sites during diffusion inside the zeolite pores, resulting in an inefficient utilization of the Brønsted acid sites for samples with high acid site concentrations. The parallel intra- and inter- molecular dehydration pathways having different activation energies pass through alternative reaction intermediates. Formation of surface-bound alkoxide species is the rate-limiting step during intramolecular dehydration, whereas intermolecular dehydration proceeds via a bulky dimer intermediate. Octadecene is the primary dehydration product over H-BEA at 533 K. Despite of the main contribution of Brønsted acid sites towards both dehydration pathways, Lewis acid sites are also active in the formation of dioctadecyl ether. The intramolecular dehydration to octadecene and cleavage of the intermediately formed ether, however, require strong BAS. L. Wang, D. Mei and J. A. Lercher, acknowledge the partial support from the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and by the National Energy Research Scientific Computing Center (NERSC). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

1-octadecanol↗
DOE OSTI2014

First-principles Study of Phenol Hydrogenation on Pt and Ni Catalysts in Aqueous Phase

The effects of aqueous phase on the reactivity of phenol hydrogenation over Pt and Ni catalysts were investigated using density functional theory based ab initio molecular dynamics (AIMD) calculations. The adsorption of phenol and the first hydrogenation steps via three carbon positions (ortho, meta and para) with respect to the phenolic OH group were studied in both vacuum and liquid phase conditions. To gain insight into how the aqueous phase affects the metal catalyst surface, increasing water environments including singly adsorbed water molecule, mono- (9 water molecules), double layers (24 water molecules), and the bulk liquid water which (52 water molecules) on the Pt(111) and the Ni(111) surfaces were modeled. Compared to the vacuum/metal interfaces, AIMD simulation results suggest that the aqueous Pt(111) and Ni(111) interfaces have a lower metal work function in the order of 0.8 - 0.9 eV, thus, making the metals in aqueous phase stronger reducing agents and poorer oxidizing agents. Phenol adsorption from the aqueous phase is found to be slightly weaker that from the vapor phase. The first hydrogenation step of phenol at the ortho position of the phenolic ring is slightly favored over the other two positions. The polarization induced by the surrounding water molecules and the solvation effect play important roles in stabilizing the transition states associated with phenol hydrogenation by lowering the barriers of 0.1 - 0.4 eV. The detailed discussion on the basis of the interfacial electrostatics from the current study is very useful to understand the nature of a broader class of metal catalyzed reactions in liquid solution phase. This work was supported by the US Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences and Office of Energy Efficiency and Renewable Energy. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and by the National Energy Research Scientific Computing Center (NERSC). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

aqueous phase↗
DOE OSTI2014

A Radar-like Iron based Nanohybrid as an Efficient and Stable Electrocatalyst for Oxygen Reduction

The present study shows a design concept for fabricating Fe-PyNG hybrid via strong coupling between FePc and pyridine-N. The prominent features of the Fe-PyNG hybrid include high electrocatalytic activity, superior durability, and better performance than Pt/C toward ORR in alkaline media. These features potentially make Fe-PyNG an outstanding nonprecious metal cathode catalyst for fuel cells. The incorporation of Fe ion and pyridine-N afforded effective bonding and synergetic coupling effects, which lead to significant electrocatalytic performance. DFT calculations indicate that N-modified Fe is a superior site for OOH adsorption and ORR reaction. Meanwhile, the strong chemical bonding between FePc and pyridyne in PyNG leads to its superior stability. We believe that our present synthetic strategy can be further extended to develop other metal complexes/N-doped carbon materials for broad applications in the field of catalysts, batteries, and supercapacitors. This work was supported by National Basic Research Program of China (973 Program) (2013CB733501), the National Natural Science Foundation of China (NSFC-21306169, 21176221, 21136001 and 21101137), Zhejiang Provincial Natural Science Foundation of China (ZJNSF-R4110345) and the New Century Excellent Talents in University Program (NCET-10-0979). We thank Prof. Youqun Zhu for Instruments support. D. Mei is supported by the US Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Effect of Graphene with Nanopores on Metal Clusters

Porous graphene, which is a novel type of defective graphene, shows excellent potential as a support material for metal clusters. In this work, the stability and electronic structures of metal clusters (Pd, Ir, Rh) supported on pristine graphene and graphene with different sizes of nanopore were investigated by first-principle density functional theory (DFT) calculations. Thereafter, CO adsorption and oxidation reaction on the Pd-graphene system were chosen to evaluate its catalytic performance. Graphene with nanopore can strongly stabilize the metal clusters and cause a substantial downshift of the d-band center of the metal clusters, thus decreasing CO adsorption. All binding energies, d-band centers, and adsorption energies show a linear change with the size of the nanopore: a bigger size of nanopore corresponds to a stronger metal clusters bond to the graphene, lower downshift of the d-band center, and weaker CO adsorption. By using a suitable size nanopore, supported Pd clusters on the graphene will have similar CO and O2 adsorption ability, thus leading to superior CO tolerance. The DFT calculated reaction energy barriers show that graphene with nanopore is a superior catalyst for CO oxidation reaction. These properties can play an important role in instructing graphene-supported metal catalyst preparation to prevent the diffusion or agglomeration of metal clusters and enhance catalytic performance. This work was supported by National Basic Research Program of China (973Program) (2013CB733501), the National Natural Science Foundation of China (NSFC-21176221, 21136001, 21101137, 21306169, and 91334013). D. Mei acknowledges the support from the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and by the National Energy Research Scientific Computing Center (NERSC).

cobalt↗
DOE OSTI2019

Computer–aided process intensification: Challenges, trends and opportunities

Chemicals based products and the processes that manufacture them play important roles in sustaining our society. Chemical, biochemical, petrochemical and related processes are characterized by either conversion of specific raw materials to desired chemicals or extraction of desired chemicals from specific raw materials. Well–known examples in the first category are the conversion of methanol and acetic acid to form methyl acetate and water, and, carbon dioxide hydrogenation to methanol via the reverse water gas shift reaction. In the second category, the use of de–methanizer, de–ethanizer, de–propanizer, and so on, separation steps in gas processing plants are well–known. In the conversion–based processes, as the conversions of raw materials are usually not 100% complete, energy intensive downstream separation techniques need to be employed to separate the desired products and recycle the unreacted raw materials. Note that the conversion process itself may also be energy intensive. In the extraction–based processes where product chemicals do not usually represent 100% of the raw material, energy intensive separation techniques are commonly employed to achieve the desired separations. This means that for both categories of processes, energy in different forms need to be supplied and the processes during operation have the potential to produce waste that may lead to negative environmental impacts and cause supply chain issues. Furthermore, planet earth is facing challenges with respect to energy, water, food, and environment, and significant improvements in process efficiencies of new and/or existing processes are needed.

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

Analytical and Computational Advances, Opportunities, and Challenges in Marine Organic Biogeochemistry in an Era of “Omics”

Advances in sampling tools, analytical methods, and data handling capabilities have been fundamental to the growth of marine organic biogeochemistry over the past four decades. There has always been a strong feedback between analytical advances and scientific advances. However, whereas advances in analytical technology were often the driving force that made possible progress in elucidating the sources and fate of organic matter in the ocean in the first decades of marine organic biogeochemistry, today process-based scientific questions should drive analytical developments. Several paradigm shifts and challenges for the future are related to the intersection between analytical progress and scientific evolution. Untargeted “molecular headhunting” for its own sake is now being subsumed into process-driven targeted investigations that ask new questions and thus require new analytical capabilities. However, there are still major gaps in characterizing the chemical composition and biochemical behavior of macromolecules, as well as in generating reference standards for relevant types of organic matter. Field-based measurements are now routinely complemented by controlled laboratory experiments and in situ rate measurements of key biogeochemical processes. And finally, the multidisciplinary investigations that are becoming more common generate large and diverse datasets, requiring innovative computational tools to integrate often disparate data sets, including better global coverage and mapping. Here, we compile examples of developments in analytical methods that have enabled transformative scientific advances since 2004, and we project some challenges and opportunities in the near future. We believe that addressing these challenges and capitalizing on these opportunities will ensure continued progress in understanding the cycling of organic carbon in the ocean.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

From nucleons to nuclei to fusion reactions

Nuclei are prototypes of many-body open quantum systems. Complex aggregates of protons and neutrons that interact through forces arising from quantum chromo-dynamics, nuclei exhibit both bound and unbound states, which can be strongly coupled. In this respect, one of the major challenges for computational nuclear physics, is to provide a unified description of structural and reaction properties of nuclei that is based on the fundamental underlying physics: the constituent nucleons and the realistic interactions among them. This requires a combination of innovative theoretical approaches and high-performance computing. In this contribution, we present one of such promising techniques, the ab initio no-core shell model/resonating-group method, and discuss applications to light nuclei scattering and fusion reactions that power stars and Earth-base fusion facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Network Anomaly Detection Using Federated Learning

The internet is turning out to be an integral part of every-one's lives as more and more devices are being connected to serve societal needs. Our work is motivated by two ma-jor observations. Firstly, one drawback of connecting to the network is the threat of network attacks that can compromise users' private information, leading to data loss and adversely affecting productivity. There are several traditional security mechanisms to defend against these attacks, such as firewalls, virtual private networks (VPNs), demilitarized zones (DMZs), and vulnerability scanners. One way to prevent these attacks is early detection and prevention. However, these kinds of architecture do not scale very well because of their centralized nature. Secondly, we observe from heuristics and data set distributions that the majority of the requests made to a server are innocuous. Therefore, almost all server request data sets are highly imbalanced, weighted highly towards the harmless requests.

Marfo, William↗
DOE OSTI2024

From Design to Device: Challenges and Opportunities in Computational Discovery of p -Type Transparent Conductors

A high-performance p -type transparent conductor (TC) does not yet exist but could lead to advances in a wide range of optoelectronic applications and enable new architectures for, e.g., next-generation photovoltaic (PV) devices. High-throughput computational material screenings have been a promising approach to filter databases and identify new p -type TC candidates and some of these predictions have been experimentally validated. However, most of these predicted candidates do not have experimentally achieved properties on par with n -type TCs used in solar cells and therefore have not yet been used in commercial devices. Thus, there is still a significant divide between transforming predictions into results that are actually achievable in the laboratory and an even greater lag in scaling predicted materials into functional devices. In this perspective, we outline some of the major disconnects in this materials discovery process—from scaling computational predictions into synthesizable crystals and thin films in the laboratory to scaling laboratory-grown films into real-world solar devices—and share insights to inform future strategies for TC discovery and design. Published by the American Physical Society 2024

14 SOLAR ENERGY↗
DOE OSTI2016

Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshop we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗