Search NASA⌕ Search

SEARCH · Search NASA

Results for “Applicability”

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 109 records · Page 6

Biofuel Options for Marine Applications: Technoeconomic and Life-Cycle Analyses

This study performed technoeconomic and life-cycle analyses to assess the economic feasibility and emission benefits and tradeoffs of various biofuel production pathways as an alternative to conventional marine fuels. We analyzed production pathways for (1) Fischer-Tropsch diesel from biomass and cofeeding biomass with natural gas or coal, (2) renewable diesel via hydroprocessed esters and fatty acids from yellow grease and cofeeding yellow grease with heavy oil, and (3) bio-oil via fast pyrolysis of low-ash woody feedstock. We also developed a new version of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) marine fuel module for the estimation of life-cycle greenhouse gas (GHG) and criteria air pollutant (CAP) emissions of conventional and biobased marine fuels. The alternative fuels considered have a minimum fuel selling price between 2.36 and 4.58 $/heavy fuel oil gallon equivalent (HFOGE), and all exhibit improved life-cycle GHG emissions compared to heavy fuel oil (HFO), with reductions ranging from 40 to 93%. The alternative fuels also exhibit reductions in sulfur oxides and particulate matter emissions. Additionally, when compared with marine gas oil and liquified natural gas, they perform favorably across most emission categories except for cases where carbon and sulfur emissions are increased by the cofed fossil feedstocks. The pyrolysis bio-oil offers the most promising marginal CO2 abatement cost at less than $100/tonne CO2e for HFO prices >$1.09/HFOGE followed by Fischer-Tropsch diesel from biomass and natural gas pathways, which fall below $100/tonne CO2e for HFO prices >$2.25/HFOGE. Pathways that cofeed fossil feedstocks with biomass do not perform as well for marginal CO2 abatement cost, particularly at low HFO prices. This study indicates that biofuels could be a cost-effective means of reducing GHG, sulfur oxide, and particulate matter emissions from the maritime shipping industry and that cofeeding biomass with natural gas could be a practical approach to smooth a transition to biofuels by reducing alternative fuel costs while still lowering GHG emissions, although marginal CO2 abatement costs are less favorable for the fossil cofeed pathways.

Greenhouse gas, life cycle assessment, techno-econ↗

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

60 APPLIED LIFE SCIENCES↗

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗

Multicomponent Cholesky Decomposition: Application to Nuclear–Electronic Orbital Theory

The Cholesky decomposition technique is commonly used to reduce the memory requirement for storing two-particle repulsion integrals in quantum chemistry calculations that use atomic orbital bases. However, when quantum methods use multicomponent bases, such as nuclear–electronic orbitals, additional challenges are introduced due to asymmetric two-particle integrals. This work proposes several multicomponent Cholesky decomposition methods for calculations using nuclear–electronic orbital density functional theory. To analyze the errors in different Cholesky decomposition components, benchmark calculations using water clusters are carried out. The largest benchmark calculation is a water cluster (H 2 O) 27 where all 54 protons are treated quantum mechanically. Furthermore, this study provides energetic and complexity analyses to demonstrate the accuracy and performance of the proposed multicomponent Cholesky decomposition method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scaling of Transition State Vibrational Frequencies and Application of d -Band Theory to the Brønsted–Evans–Polanyi Relationship on Surfaces

Semiempirical energy relations provide a means of estimating thermodynamic properties. Specifically, linear scaling relationships (LSRs) and Brønsted–Evans–Polanyi (BEP) relationships correlate adsorption energies between adsorbates across surfaces and reaction energies with activation barriers, respectively. Although vibrational scaling relations (VSRs) exist between adsorbates at identical sites, scaling between vibrational frequencies of adsorbed local minima and transition states is lacking. Here, we present density functional theory calculations for AH X (A = C, N, O) diffusions on transition metal surfaces and reveal linear scaling between frequencies of local minima and the transition state between those minima. Using d-band theory and linear muffin tin orbital theory (LMTO), we derive the slopes of these transition state vibrational scaling relations (TSVSRs) and, in so doing, provide a rigorous theory extending the original BEP relations developed for solution chemistry to surface chemistry. Furthermore, with a single reference DFT calculation, we predict the slopes and quantify uncertainty in the predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Creating Functional Oxynitride–Silicon Interfaces and SrNbO 2 N Thin Films for Photoelectrochemical Applications

Photoelectrochemical performance dependence upon absorption length, carrier diffusion length, and surface area of an oxynitride photoabsorber is investigated. How best to fabricate optical-quality thin films of bandgap-tunable oxynitrides is also discussed. We targeted the stoichiometric compound SrNbO 2 N as an optimal wide-bandgap photoabsorber (1.9 eV) for use with silicon (1.1 eV) in a tandem structure photoelectrochemical cell. Preparation of perovskite oxynitrides at high-temperature as isolated powders is often straightforward, but it is difficult to integrate them as thin films in tandem junction devices with low-temperature materials. Here we develop the first method to prepare optical-quality SrNbO 2 N thin-films of tunable thickness and roughness on single-crystal silicon substrate. This achievement required an interfacial layer of ultra-thin TaN to be used as a barrier to reduce the inter-diffusion of silicon and oxygen during oxynitride syn-thesis. We produced a variety of SrNbO 2 N film thicknesses (20-440 nm) on n + -Si(100) surfaces. Roughness factor (0.14-21) scaled with thickness. The intrinsic photoelectrochemical activity of these devices was evaluated using a low-barrier sacrificial electron donor. Photocurrent density and photovoltage revealed a significant (and non-linear) dependence on film thickness and roughness. Furthermore, absorption length, carrier diffusion length, and surface area were each found to play key roles. Balancing these is required for optimally performing devices.

08 HYDROGEN↗

Broad Applicability of Electrochemical Impedance Spectroscopy to the Measurement of Oxygen Nonstoichiometry in Mixed Ion and Electron Conductors

Oxygen non-stoichiometry is a fundamental feature of mixed ion and electron conductors (MIECs). In this work a general electrochemical method for determining non-stoichiometry in thin film MIECs, via measurement of the chemical capacitance, is demonstrated using ceria and ceria-zirconia (Ce 0.8 Zr 0.2 O 2-δ ) as representative materials. A.C. impedance data are collected from both materials at high temperature (750-900 °C) under reducing conditions with oxygen partial pressure (pO 2 ) in the range 10-13 to 10-20 atm. Additional measurements of ceria-zirconia films are made under relatively oxidizing conditions with pO 2 in the range 0.2 to 10 -4 atm and temperatures of 800-900 °C. Under reducing conditions, the impedance spectra are described by a simple circuit in which a resistor is in series with a resistor and capacitor in parallel, and thickness dependent measurements are used to resolve the capacitance into interfacial and chemical terms. Under more oxidizing conditions, the impedance spectra (of Ce 0.8 Zr 0.2 O 2-δ ) reveal an additional diffusional feature, which enables determination of the ionic resistance of the film in addition to the capacitance, and hence the transport properties. A generalized mathematical formalism is presented for recovering the non-stoichiometry from the chemical capacitance, without recourse to defect chemical models. The ceria non-stoichiometry values are in good agreement with literature values determined by thermogravimetric measurements but display considerably less scatter and are collected on considerably shorter timescales. Here, the thermodynamic analysis of Ce 0.8 Zr 0.2 O 2-δ corroborates earlier findings that introduction of Zr into ceria enhances its reducibility.

08 HYDROGEN↗

General Kinetic Model for pH Dependence of Proton-Coupled Electron Transfer: Application to an Electrochemical Water Oxidation System

The pH dependence of proton-coupled electron transfer (PCET) reactions, which are critical to many chemical and biological processes, is a powerful probe for elucidating their fundamental mechanisms. Herein, a general, multichannel kinetic model is introduced to describe the pH dependence of both homogeneous and electrochemical PCET reactions. According to this model, a weak pH dependence can arise from the competition among multiple sequential and concerted PCET channels involving different forms of the redox species, such as protonated and deprotonated forms, as well as different proton donors and acceptors. The contribution of each channel is influenced by the relative populations of the reactant species, which often depend strongly on pH, leading to complex pH dependence of PCET apparent rate constants. This model is used to explain the origins of the experimentally observed weak pH dependence of the electrochemical PCET apparent rate constant for a ruthenium-based water oxidation catalyst attached to a tin-doped In2O3 (ITO) surface. The weak pH dependence is found to arise from the intrinsic differences in the rate constants of participating channels and the dependence of their relative contributions on pH. This model predicts that the apparent maximum rate constant will become pH-independent at higher pH, which is confirmed by experimental measurements. Our analysis also suggests that the dominant channels are electron transfer at lower pH and sequential PCET via electron transfer followed by fast proton transfer at higher pH. Furthermore, this work highlights the importance of considering multiple competing channels simultaneously for PCET processes.

Catalysts↗

GPM IMERG V07B and V06B: Evaluation Using Ground-Based Radar Observations and Application in Global Mesoscale Convective System Tracking

This study evaluates the latest Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07B) against its predecessor V06B, for studying mesoscale convective systems (MCSs). Both versions are compared using ground-based radar and rain gauge data from five meteorologically diverse regions: the contiguous United States (including eastern coastlines), Amazon rainforest, central Argentina mountains, equatorial Indian Ocean, and northern Australia across multiple temporal (0.5–6 hours) and spatial scales (0.1°–0.25°). An updated global MCS tracking dataset is developed by integrating satellite-observed infrared brightness temperature with IMERG V07B. Comparation of IMERG against radar observations reveals that IMERG demonstrates better performance in capturing the probability distribution and quantitative contributions of rainfall (from no-rain to intense-rain conditions) over tropical oceans than over land, with marked improvements in IMERG V07B for heavy-to-intense rain (> 10 mm h-1). Over land, systematic biases persist: IMERG tends to overestimate light-to-moderate rain (1–10 mm h-1) while underestimating heavy-to-intense rain. Additionally, aggregating IMERG to coarser resolutions (3-hourly or 0.25°) improves consistency with radar observations, outperforming the 1-hourly/0.1° resolution. The new IMERG V07B-based global MCS dataset exhibits consistent statistical characteristics with the V06B-based dataset, despite lower mean rain rates and reduced heavy precipitation contributions. These findings offer valuable insights for utilizing IMERG V07B in global precipitation studies, MCS characterization, and model evaluation.

Zhang, Sihan↗