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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 127 records · Page 7

Is the Trotterized UCCSD Ansatz Chemically Well-Defined?

The variational quantum eigensolver (VQE) has emerged as one of the most enticing near-term quantum algorithms that can be used to simulate many-body systems such as molecular electronic structures. Serving as an attractive ansatz in the VQE algorithm, unitary coupled cluster (UCC) theory has seen a renewed interest in recent literature. Yet, unlike the original classical UCC theory, implementation on a quantum computer requires a finite-order Suzuki-Trotter decomposition to separate the exponentials of the large sum of Pauli operators. While previous literature has recognized the non-uniqueness of different orderings of the operators in the Trotterized form of UCC methods, the question of whether or not different orderings matter at the chemical scale has not been addressed. In this letter, we explore the effect of operator ordering on the Trotterized UCCSD ansatz, as well as the much more compact k-UpCCGSD ansatz recently proposed by Lee et al. We observe a significant, system-dependent variation in the energies of Trotterizations with different operator orderings. The energy variations occur on a chemical scale, sometimes on the order of hundreds of kcal/mol. This letter establishes the need to define not only the operators present in the ansatz, but also the order in which they appear. This is necessary for adhering to the quantum chemical notion of a ``model chemistry'', in addition to the general importance of scientific reproducibility. As a final note, we suggest a useful strategy to select out of the combinatorial number of possibilities, a single well-defined and effective ordering of the operators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Attractive Way to Correct for Missing Singles Excitations in Unitary Coupled Cluster Doubles Theory

Coupled cluster methods based exclusively on double excitations are comparatively “cheap” and interesting model chemistries, as they are typically able to capture the bulk of the dynamic electron correlation effects. The trade-off in such approximations is that the effect of neglected excitations, particularly single excitations, can be considerable. Using standard and electron-pair-restricted T 2 operators to define two flavors of unitary coupled cluster doubles (UCCD) methods, we investigate the extent to which missing single excitations can be recovered from low-order corrections in many-body perturbation theory (MBPT) within the unitary coupled cluster (UCC) formalism. Here, our analysis includes the derivations of finite-order UCC energy functionals, which are used as a basis to define perturbative estimates of missed single excitations. This leads to the novel UCCD[4S] and UCCD[6S] methods, which consider energy corrections for missing single excitations through fourth- and sixth-order in MBPT, respectively. We also apply the same methodology to the electron-pair-restricted ansatz, but the improvements are only marginal. Our findings show that augmenting UCCD with these post hoc perturbative corrections can lead to UCCSD-quality results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shift in Peaks of PAH-Associated Health Risks From East Asia to South Asia and Africa in the Future

Lung cancer risk from exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is expected to change significantly by 2050 compared to 2008 due to changes in climate and emissions. Integrating a global atmospheric chemistry model, a lung cancer risk model, and plausible future emissions trajectories of PAHs, we assess how global PAHs and their associated lung cancer risk will likely change in the future. Benzo(a)pyrene (BaP) is used as an indicator of cancer risk from PAH mixtures. From 2008 to 2050, the population-weighted global average BaP concentrations under all RCPs consistently exceeded the WHO-recommended limits, primarily attributed to residential biofuel use. Peaks in PAH-associated incremental lifetime cancer risk shift from East Asia (4 × 10 –5 ) in 2008 to South Asia (mostly India, 2–4 × 10 –5 ) and Africa (1–2 × 10 –5 ) by 2050. In the developing regions of Africa and South Asia, PAH-associated lung cancer risk increased by 30–64% from 2008 to 2050, due to increasing residential energy demand in households for cooking, heating, and lighting, the continued use of traditional biomass use, increases in agricultural waste burning, and forest fires, accompanied by rapid population growth in these regions. Due to more stringent air quality policies in developed countries, their PAH lung cancer risk substantially decreased by ~80% from 2008 to 2050. Climate change is likely to have minor effects on PAH lung cancer risk compared to the impact of emissions. Future policies, therefore, need to consider efficient combustion technologies that reduce air pollutant emissions, including incomplete combustion products such as PAH.

54 ENVIRONMENTAL SCIENCES↗

Sub 20 cm -1 computational prediction of the CH bond energy – a case of systematic error in computational thermochemistry

Here, the bond dissociation energy of methylidyne, D 0 (CH), is studied using an improved version of the High-Accuracy Extrapolated ab initio Thermochemistry (HEAT) approach as well as the Feller–Peterson–Dixon (FPD) model chemistry. These calculations, which include basis sets up to nonuple (aug-cc-pCV9Z) quality, are expected to be capable of providing results substantially more accurate than the ca. 1 kJ mol -1 level that is characteristic of standard high-accuracy protocols for computational thermochemistry. The calculated 0 K CH bond energy (27 954 ± 15 cm -1 for HEAT and 27 956 ± 15 cm -1 for FPD), along with equivalent treatments of the CH ionization energy and the CH + dissociation energy (85 829 ± 15 cm -1 and 32 946 ± 15 cm -1 , respectively), were compared to the existing benchmarks from Active Thermochemical Tables (ATcT), uncovering an unexpected difference for D 0 (CH). This has prompted a detailed reexamination of the provenance of the corresponding ATcT benchmark, allowing the discovery and subsequent correction of a systematic error present in several published high-level calculations, ultimately yielding an amended ATcT benchmark for D 0 (CH). Finally, the current theoretical results were added to the ATcT Thermochemical Network, producing refined ATcT estimates of 27 957.3 ± 6.0 cm -1 for D0(CH), 32 946.7 ± 0.6 cm -1 for D 0 (CH + ), and 85 831.0 ± 6.0 cm -1 for IE(CH).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A reaction mechanism for plasma electrolysis of AgNO 3 forming silver nanoclusters and nanoparticles

In plasma-driven solution electrolysis (PDSE), gas-phase plasma-produced species interact with an electrolytic solution to produce, for example, nanoparticles. An atmospheric pressure plasma jet (APPJ) directed onto a liquid solution containing a metallic salt will promote reduction of metallic ions in solution, generating metallic clusters that nucleate to form nanoparticles. In this article, results from a computational investigation are discussed of a PDSE process in which a radio-frequency APPJ sustained in helium impinges on a silver nitrate solution, resulting in growth of silver nanoparticles. A reaction mechanism was developed and implemented in a global plasma chemistry model to predict nanoparticle growth. To develop the reaction mechanism, density functional theory was used to generate probable silver growth pathways up to Ag 9 . Neutral clusters larger than Ag 9 were classified as nanoparticles. Kinetic reaction rate coefficients for thermodynamically favorable growth pathways were estimated based on an existing, empirically determined base reaction mechanism for smaller Ag particle interactions. These rates were used in conjunction with diffusion-controlled reaction rate coefficients that were calculated for other Ag species. The role of anions in reduction of Agn ions in forming nanoparticles is also discussed. Oxygen containing impurities or admixtures to the helium, air entrainment into the APPJ, and dissociation of saturated water vapor above the solution can produce additional reactive oxygen species in solution, resulting in the production of anions and O 2 – in particular. For a given molarity, delivering a sufficient fluence of reducing species will produce similar nanoparticle densities and sizes for all applied power levels. In conclusion, comparisons are made to alternate models for nanoparticle formation, including charged nanoparticles and use of direct current plasmas.

36 MATERIALS SCIENCE↗

The approximate second order coupled-cluster method based on a size-consistent Brillouin–Wigner partitioning

We present a variant of the approximate second order coupled-cluster method (CC2) with a two-parameter size-consistent Brillouin–Wigner (BW-s) partitioning instead of a Møller–Plesset (MP) partitioning for the unperturbed Hamiltonian, which we refer to as BWs-CC2. The computational complexity of this model scales identically to CC2 with molecular size. Conventional CC2 and its regularized BWs-CC2 variants, as well as conventional MP2 and two of its regularized BW-s2 variants, were assessed on a 535 element database spanning thermochemistry, non-covalent interactions, barrier heights, and isomerization energies. To ensure a well-defined model chemistry, the assessment was performed using internally stable spin-polarized Hartree–Fock (HF) orbitals in the finite aug-cc-pVQZ basis without counterpoise corrections. As a result of using stable orbitals, contrary to conventional wisdom, we find that CC2 substantially outperforms MP2 on molecules with significantly spin contaminated reference orbitals without a significant increase in error on systems with a spin-pure reference, showing the value of its single substitutions. While no single choice of regularization parameters can be optimal for all datasets, we find that BWs-CC2 generally outperforms both CC2 and BW-s2 with a single judicious parameter choice. Additional tests on dipole moments and bond lengths of diatomics provide further support for the utility of this choice. Furthermore, the main outliers and poorest performing cases are associated with large amounts of spin-contamination in the HF reference, which is indicative of systems with either strong correlation or extensive artificial symmetry breaking. Overall, these findings argue that the perception of the quality of the CC2 ground state should be reevaluated and that it can be further improved upon by the soundly based BWs-CC2 variant with the recommended parameter choice.

Correlation energy↗

Reaction mechanism for atmospheric pressure plasma treatment of cysteine in solution

Mechanisms for the cold atmospheric plasma (CAP) treatment of cells in solution are needed for more optimum design of plasma devices for wound healing, cancer treatment, and bacterial inactivation. However, the complexity of organic molecules on cell membranes makes understanding mechanisms that result in modifications (i.e. oxidation) of such compounds difficult. As a surrogate to these systems, a reaction mechanism for the oxidation of cysteine in CAP activated water was developed and implemented in a 0-dimensional (plug-flow) global plasma chemistry model with the capability of addressing plasma-liquid interactions. Reaction rate coefficients for organic reactions in water were estimated based on available data in the literature or by analogy to gas-phase reactions. The mechanism was validated by comparison to experimental mass-spectrometry data for COST-jets sustained in He/O 2 , He/H 2 O and He/N 2 /O 2 mixtures treating cysteine in water. Results from the model were used to determine the consequences of changing COST-jet operating parameters, such as distance from the substrate and inlet gas composition, on cysteine oxidation product formation. Results indicate that operating parameters can be adjusted to select for desired cysteine oxidation products, including nitrosylated products.

60 APPLIED LIFE SCIENCES↗

The role of stiffness in training and generalization of ResNets

Neural ordinary differential equations (NODEs) have recently regained popularity as large-depth limits of a large class of neural networks. In particular, residual neural networks (ResNets) are equivalent to an explicit Euler discretization of an underlying NODE, where the transition from one layer to the next is one time step of the discretization. The relationship between continuous and discrete neural networks has been of particular interest. Notably, analysis from the ordinary differential equation viewpoint can potentially lead to new insights for understanding the behavior of neural networks in general. In this work, we take inspiration from differential equations to define the concept of stiffness for a ResNet via the interpretation of a ResNet as the discretization of a NODE. Here, we then examine the effects of stiffness on the ability of a ResNet to generalize, via computational studies on example problems coming from climate and chemistry models. We find that penalizing stiffness does have a unique regularizing effect, but we see no benefit to penalizing stiffness over L 2 regularization (penalization of network parameter norms) in terms of predictive performance.

97 MATHEMATICS AND COMPUTING↗

NEWTS USGS Brackish Water Database

Data from the USGS Brackish Water Database on brackish water compositions from across the US. Data has been filtered for high salinity and completeness of data attributes. Data has been transposed and converted for ease of input into aqueous chemistry modeling software including OLI Systems and Geochemist's Workbench. Original data from: Qi, S.L., and Harris, A.C., 2017, Geochemical Database for the Brackish Groundwater Assessment of the United States: U.S. Geological Survey data release, https://doi.org/10.5066/F72F7KK1.

Brackish Groundwater↗

NEWTS USGS Produced Waters Database

Data from the USGS Produced Waters Database on produced water compositions from across the US. Data has been filtered for completeness of data attributes. Data has been transposed and converted for ease of input into aqueous chemistry modeling software including OLI Systems and Geochemist's Workbench. Original data from: Blondes, M. S., Gans, K. D., Engle, M. A., Kharaka, Y. K., Reidy, M. E., Saraswathula, V., Thordsen, J. J., Rowan, E. L., & Morrissey, E. A. (2019). U.S. Geological Survey National Produced Waters Geochemical Database v2.3 [Data set]. U.S. Geological Survey. https://doi.org/10.5066/F7J964W8

Geochemists Workbench↗

NEWTS EPA Gasification Dataset and Case Studies

Data from the US EPA Gasification Database containing gasification effluent data from selected U.S. coal power plants. Original data from: Nguyen, Dan-Tam, Eastern Research Group. Sep 29, 2015. Analytical Database for the Steam Electric Rulemaking - DCN SE05359. https://www.regulations.gov/document/EPA-HQ-OW-2009-0819-5640 Files include: Original data tab, processed data and charge balance information in "NEWTS_EPA_Gasification_Effluent_Dataset_all_tabs.xlsx" Individual .csv files for data in format for input into aqueous chemistry modeling software (OLI Systems and Geochemist's Workbench) Data input templates for modeling streams in OLI Systems and Geochemist's Workbench Case studies for selected solved streams modeled in OLI Systems and Geochemist's Workbench

gasification↗

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Minerals Database and Dashboard

The poster, presented at the American Geophysical Union (AGU) 2023 Conference, highlights NETL's National Energy Water Treatment & Speciation (NEWTS) Database & Dashboard. This poster reviews the work done to aggregate disparate water quality data for energy-related wastewater streams, to process and integrate the datasets, and enable easy integration with aqueous chemistry modeling software to support water management and beneficial reuse decision-making.

Wenzlick, Madison↗

National Energy Water Treatment and Speciation (NEWTS) Database & Dashboard

The Department of Energy's Office of Fossil Energy & Carbon Management (DOE/FECM) through the National Energy Technology Laboratory (NETL) has launched a free online tool, the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard, which can be utilized by community leaders and water researchers to better understand the composition of energy-related wastewater streams. The NEWTS Database and Dashboard provide public access to difficult-to-access datasets, including the original data sources and the processed data forms for input into aqueous chemistry modeling software. The data provided by the tool will help mitigate environmental risks and identify possible sources of valuable critical minerals (CM). The goal of this ASME Power presentation is to highlight the data and capabilities of this free online-tool for obtaining high quality water datasets in formats that are easy for modeling the treatment and recovery of valuable resources from effluent waste stream associated with energy operations.

Siefert, Nicholas↗

Theoretical Calculation Study of Nanomaterials

In recent years, theoretical simulations using computational physics and chemistry models have been used widely to predict the physical, chemical, and structural properties of nanomaterials. To reflect such rapid progress, two Special Issues on the theoretical study of nanomaterials were published. The 36 articles collected cover broad re-search fields and applications. In this Editorial, we provide an overview of these pub-lications and summarize the main findings. Based on these research outcomes, we lay out some future research directions.

First-principles calculations↗

Tropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval

We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January–February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system.

54 ENVIRONMENTAL SCIENCES↗