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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Physical and chemical effects of isopropanol exchange in cement-based materials

Drying cement-based materials is a necessary step to characterize the microstructure by microscopy, adsorption, or mercury intrusion. The isopropanol (IPA) exchange method is commonly used to replace the pore solution prior to drying, as it reduces the capillary pressure and thereby helps to preserve the microstructure of the hydrated cementitious materials. However, some physical and chemical effects of IPA on hydration products have been reported. These effects cannot be completely avoided, but can be reduced by shortening the exchange duration, in particular for effects on ettringite. This study carried out experiments with different exchange durations and IPA removal techniques to address research gaps in the literature. For 1-mm cubes of cement paste with IPA diffusion coefficient of 1 × 10{sup −11} m{sup 2}/s, the compared exchange durations are 5 min, 15 min (value from the literature), 40 min (when the mixture at the sample center achieves 95% of the drop in surface tension from water to IPA), 80 min (when the IPA/water mixture at the sample center reaches an azeotrope), 5 h (when over 99% IPA is replaced at the sample center), and 24 h (prolonged exchange). After IPA exchange, samples were either directly dried at 40 °C with flushing N{sub 2} or washed by diethyl ether prior to N{sub 2} drying. Even though the exchange duration of 40 and 80 min, in theory, can reduce the damage from capillary pressure, the nitrogen adsorption results do not show any advantage in preventing microstructural alteration. The 5-h exchange provided results similar to the 24-h exchange, but the latter induced slightly more serious chemical effects resulting from the longer contact of IPA with hydration products. In addition, the compared IPA removal techniques do not show significant differences. Therefore, this study suggests using small samples (~1 mm) for microstructural studies following IPA exchange for a period corresponding to the time when 99% of the water (mole fraction) at the sample center is replaced.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Geometrical and chemical effects on the electrochemistry of single-wall carbon nanotube (SWCNT) network electrodes

Single-wall carbon nanotube (SWCNT) network is a promising electrode material for bio detection. Unfortunately, the associations between their physical as well as chemical properties and observed electrochemical performance are not known. This hinders any systematic optimization of the network properties towards specific analytes. Here we present a consistent physicochemical and electrochemical characterization of differently treated SWCNT networks. The results unambiguously show that (i) even if the electrochemical properties of different electrodes are practically identical when assessed by surface insensitive outer sphere redox (OSR) probes their behavior with inner sphere redox (ISR) probes can be drastically different. Further, (ii) the choice of the modification method (structural, chemical, electrochemical) heavily depends on nature of the target analyte, which are typically ISR probes. Although, (iii) chemical changes in the carbon phase appeared to be minor, effects of different treatments on oxidation states of Fe appeared to have a strong effect on the electrochemical performance of the networks in the case of ISR probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Chemical controls on the propagation and healing of subcritical fractures

Human activities involving subsurface reservoirs—resource extraction, carbon and nuclear waste storage—alter thermal, mechanical, and chemical steady-state conditions in these systems. Because these systems exist at lithostatic pressures, even minor chemical changes can cause chemically assisted deformation. Therefore, understanding how chemical effects control geomechanical properties is critical to optimizing engineering activities. The grand challenge in predicting the effect of chemical processes on mechanical properties lays in the fact that these phenomena take place at molecular scales, while they manifest all the way to reservoir scales. To address this fundamental challenge, we investigated chemical effects on deformation in model and real systems spanning molecular- to centimeter scales. We used theory, experiment, molecular dynamics simulation, and statistical analysis to (1) identify the effect of simple reactions, such as hydrolysis, on molecular structures in interfacial regions of stressed geomaterials; (2) quantify chemical effects on the bulk mechanical properties, fracture and displacement for granular rocks and single crystals; (3) develop initial understanding of universal scaling for individual displacement events in layered geomaterials; and (4) develop analytic approximations for the single-chain mechanical response utilizing asymptotically correct statistical thermodynamic theory. Taken together, these findings advance the challenging field of chemo-mechanics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Oxidation kinetic modelling of Fe-based oxygen carriers for chemical looping applications: Impact of the topochemical effect

Chemical looping is a promising technology for fossil fuel utilization due to its high fuel conversion efficiency with in-situ CO 2 capture capability. Metal oxide are used as oxygen carriers (OCs) and circulate between a fuel reactor and an air reactor to perform reduction and oxidation reactions, respectively. In general, OC exiting the fuel reactor is not reduced fully to its metallic state due to many factors including carbon deposition and OC deactivation. Therefore, the effect of the initial reduction state on the OC oxidation in the air reactor is a significant parameter for consideration in developing the oxidation kinetic model. The objective of this work is to develop a physically significant kinetic model that applies to the oxidation of both initially fully and partially reduced OC with air. For this study, 1.5 mm Fe-based OC particle supported with TiO 2 was used as the model OC particle due to its complex multistep reaction nature. The oxidation kinetics were experimentally investigated in a thermogravimetric analyzer (TGA). Results indicate a significant difference in the oxidation rate profile for the OCs when oxidized from an initially fully reduced compared to an initially partially reduced state. Elemental mapping via energy-dispersive X-ray spectroscopy (EDS) reveals a shrinking-core type topochemical pattern across the OC particle, which was identified to be the cause of the dependency of kinetics on the initial reduction state. A generalized kinetic model was developed based on the observed shrinking-core behavior without presuming any rate-determining steps and experimentally validated over a broad range of temperatures (800–1000 °C) and oxygen concentrations (5, 7, 10, and 15 mol%). Impacts of particle porosity, size, and core-shell structure on the OC oxidation kinetics were analyzed in the developed oxidation kinetic model to suggest methods of improving the oxidation rate of the OC without modifying the chemical composition.

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

Chemical treatment effects on Schottky contacts to metalorganic chemical vapor deposited n-type N-polar GaN

In this article, we investigate the effect of different chemical treatments, such as solvents, bases, and acids, on the surface properties and electrical behavior of Schottky diodes fabricated on metalorganic chemical vapor deposition-grown, n-type, N-polar GaN. The I–V and C–V barrier heights of the as-grown Schottky diodes are found to be 0.40 eV and 0.60 eV, respectively, with an ideality factor n = 1.07. It is found that the solvent treatments neither change the surface nor the electrical performance of the Schottky diodes, as expected. However, the treatments by the alkaline photolithography developer and acid—the latter of which is often used to clean the surface of Ga-polar GaN films prior to metal contact deposition—degrade the performance of N-polar GaN. These base and acid treatments severely roughen the surface by creating triangular/hexagonal crystallographic facets. The I–V and C–V barrier heights of these base- and acid-treated diodes are increased to 0.63 eV and 1.00 eV, respectively, with ideality factor values n < 1.2. X-ray photoelectron spectroscopy studies indicate that base- and acid-treated surfaces have lower oxygen content as compared to the as-grown sample surface. It is understood that the increment in the barrier height for base- and acid-treated diodes could be due to the change in polarity, from N-polar to semi-polar/non-polar, on these crystallographic features. All these results demonstrate that, unlike for Ga-polar GaN, the N-polar GaN surface is highly reactive to bases and acids.

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

Retrieving Tarnished Daguerreotype Content Using X-ray Fluorescence Imaging—Recent Observations on the Effect of Chemical and Electrochemical Cleaning Methods

We report a study on the effect of chemical and electrochemical cleaning of tarnished daguerreotypes observed using X-ray fluorescence (XRF) microscopy with a micro-focussed X-ray beam from a synchrotron source. It has been found that, while both techniques result in some success depending on the condition of the plate and the experimental parameters (chemical concentration, voltage, current, etc.) the effect varies, and cleaning is often incomplete. The XRF images using Hg Lα,β at an excitation energy just above the L3 edge threshold produce fine images, regardless of the treatment. This finding confirms previous observations that if the bulk of the image particles remains intact, the surface tarnish has little effect on the quality of the original daguerreotype image retrievable from XRF.

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

New insights into fuel blending effects: Intermolecular chemical kinetic interactions affecting autoignition times and intermediate-temperature heat release

Fuel blending effects on chemically-dominated fuel properties, such as gasoline anti-knock quality, are influenced by fundamental chemical kinetic interactions between the blending agent and the base fuel. Historically, quantification of such interactions has focused on changes to the radical pool, including $\dot{O}$H and HO 2 , while intermolecular interactions pertaining to carbonated, non-fuel-specific intermediates are typically overlooked. In this regard, this work aims to derive new insight into intermolecular chemical kinetic interactions that are intrinsic to fuel blending effects via a case study on blends of 0–30% ethanol (by volume) into FGF-LLNL (a multi-component gasoline surrogate for FACE-F research gasoline) using a rapid compression machine at a diluted/stoichiometric fuel loading, compressed pressure of 40 bar and low- to intermediate-temperature regimes that are representative of boosted SI engine operation. Ethanol blending effects on the intermediate temperature heat release (ITHR) of FGF-LLNL are characterized using experimental measurements, where ethanol is found to promote the extent of ITHR and suppress the transition from ITHR to main ignition. Chemical kinetic modeling is undertaken using a recently updated gasoline surrogate model. Sensitivity analyses on ITHR characteristics further corroborate the ethanol blending effects, and highlight the significant dependence of ITHR on both fuel-specific and non-fuel-specific reactions. An approach allowing comprehensive characterization of the complex intermolecular chemical kinetic interactions between constitutes in a fuel blend is then proposed. Application of the approach to FGF-LLNL/E0–E30 reveals that ethanol perturbs the heat release and autoignition characteristics of FGF-LLNL not only by directly changing the $\dot{O}$H and HO 2 radical pools via fuel-specific reactions, but also through intermolecular interactions where participating intermediates can be produced and consumed by various sub-chemistries. Disabling the intermolecular interactions in carbonated species between ethanol and FGF-LLNL sub-chemistries leads to somewhat slower ITHR evolution and lower ignition reactivity. The role of the individual intermolecular interaction is also characterized using the proposed approach. Lastly, implications of intermolecular interactions for future studies that aim to improve model performance are highlighted, where it is found that further investigations on the core C0-C4 chemistry are needed for developing highly accurate chemistry models for complex fuel blends.

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

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study (https://doi.org/10.1063/5.0018326), exploits the low-rank character of the polynomial expansion of potential energy to recover, using a small sample, vibrational frequencies (square roots of nuclear Hessian eigenvalues) constituting the reaction path. Furthermore, these frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four SN2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

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

Effects of chemical segregation on ductility-anisotropy in high strength Fe-Mn-Al-C lightweight austenitic steels

Ductile Fe-Mn-Al-C lightweight steels offer great potential as high specific strength materials for weight critical applications. In the present work, very high yield (~1 GPa) and ultimate tensile strength levels (~1.5 GPa) were obtained along the rolling and transverse directions of Fe-30Mn-8.5Al-0.9Si-0.9C-0.5Mo (wt.%), with high tensile elongation to failure of ~35%. This excellent mechanical behavior was attributed to the nanoscale, ordered κ-carbide precipitates formed during aging after rolling. However, tensile ductility was not isotropic through all directions of the rolled plate. In particular, the ductility was consistently lower than 5% true strain along the normal direction. Upon detailed microstructural investigations, micro-scale lamellar chemical micro-segregation bands were detected, which caused the observed anisotropic embrittlement along certain plate directions. These bands resulted in low failure strains along the normal direction since it is oriented perpendicular to these chemical segregation bands, resulting in a failure type reminiscent of delamination-induced cleavage fracture. Chemical segregation causes an inhomogeneous κ-carbide precipitate distribution upon aging, producing more pronounced mechanical anisotropy after peak-aging as compared to the solution heat treated samples. Surprisingly, deformation twinning was observed after tensile deformation of solution-heat treated specimens via electron-backscatter diffraction experiments, which is anomalous for a high stacking faulty energy (SFE) material. Further, it was proposed that chemical micro-segregation promotes locally different SFE regions, leading to deformation twinning in this nominally high SFE material. Overall, this work demonstrates the effects of chemical segregation on mechanical properties and microstructural evolution in a high performance, lightweight Fe-Mn-Al-C steel.

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

Complex Fluorine Chemical Potential Effects on the Shape and Compositional Heterogeneity of KTa 1– x Nb x O 3 Nanoparticles

When kinetic conditions dominate and dictate the growth in a nanoparticle synthesis, properties of the synthesis environment can have considerable effects on the properties of the products. Such effects were studied here, where the solution environment was changed via the addition of KF to the hydrothermal syntheses of KTa 1– x Nb x O 3 and KTaO 3 . One result demonstrated the straightforward cause-and-effect relationship between the solution and reaction kinetics: KF directly increased the solution stability of the Ta species and therefore decreased its reaction rate, resulting in a change in composition heterogeneity of Ta and Nb in the KTa 1– x Nb x O 3 particles. However, not all effects are so simple; changing the chemical potential of the solution with KF can also promote the formation of particles with anisotropic defect enhanced kinetic Wulff shapes instead of cuboidal shapes. The increased F chemical potential in the solution enabled the formation of planar defects in the bulk, which accelerated growth in-plane to form particles characterized by flat rectangular flake geometries. In this work, thermodynamic modeling with density functional theory calculations confirmed that sufficient KF concentrations can drive the formation of a defect phase K n +1 Ta n O 3 n F.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗
DOE OSTI2021

Effect of nitric oxide and exhaust gases on gasoline surrogate autoignition: iso-octane experiments and modeling

Exhaust gas recirculation (EGR) is widely used in advanced internal combustion engines to reduce engine emissions as well as control combustion phasing. Among various species present in EGR gases, CO 2 and H 2 O are two major components that can thermally and chemically affect fuel autoignition. It is of fundamental interest to isolate the thermal and chemical effects of CO 2 and H 2 O on fuel autoignition, especially as such an effort has not been reported in the literature. Moreover, nitric oxide (NO) is known to exhibit strong chemical effects on fuel autoignition, which in turn affects engine combustion phasing. The effects of ultra-low NO addition (< 100 ppm) on fuel autoignition at low temperatures are also not well understood. Recognizing these problems, autoignition experiments of iso-octane (a major gasoline surrogate component) in air are performed in this study using a rapid compression machine at varying compressed pressures, equivalence ratios, dilution levels with an EGR gas analogue (consisting of CO 2 , H 2 O, O 2 , and N 2 ) and N 2 only, and varying amounts of NO addition. Furthermore, the thermal and chemical effects of the EGR gas analogue are isolated and evaluated by comparing the ignition delay time datasets of EGR and N2-only diluted cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Modeling Equilibrium Solid–Liquid Interfaces under Effective Constant Chemical Potential Using Machine Learning Interatomic Potentials

The chemical potential (μ) of species in solution is essential for understanding various chemical processes at interfaces. Molecular dynamics (MD) simulations, constrained by fixed compositions, cannot maintain constant chemical potential with reference to a targeted concentration or chemical potential under nonequilibrium or dynamic conditions, as solute species can migrate to the interface and deplete (or enrich) the bulk due to solute-interface interactions. In this study, we introduce a simple and computationally efficient approach named iterative quasi-constant chemical potential molecular dynamics (iqCμMD) simulation, which helps simulate targeted molar concentrations of species in solution. iqCμMD overcomes the limitations of conventional MD by adjusting the number of species in the solution to reach a target bulk concentration (chemical potential), which allows simulation of the interface under the bulk conditions comparable to experiment. We demonstrate our approach using machine learning interatomic potential (MLIP)-based MD simulations of the Na 2 SO 4,aq –graphene interface, and to show the transferability of our approach, we also perform classical force field-based MD simulations of NaCl aq –air and NaCl aq –graphite interfaces, which produce comparable results to previous CμMD simulations. Our results also show that the iqCμMD approach efficiently achieves the desired bulk ion concentration within two iterations, and by utilizing MLIPs, we can achieve converged results using relatively small-scale simulations compared to previous CμMD simulations. By combining iqCμMD with MLIP-driven simulations, solid–liquid interfaces can be modeled under an effective constant chemical potential with DFT-level accuracy. Here, we show that iqCμMD offers a robust and simple computational framework for constant chemical potential simulations, as its only requirement is to be able to converge interfacial simulations with a measurable bulk region.

Chemical structure↗
DOE OSTI2020

Chemical bond effects in classical site density functional theory of inhomogeneous molecular liquids

Intra-molecular interactions or chemical bonds represent one of the main distinguishing characteristic of molecular fluids. Development of accurate and practical methods to treat these effects is one of the long standing problems in classical site density functional theory (SDFT). One particular instance when these issues become particularly severe is the case of classical interactions potentials with auxiliary sites or dummy atoms. In this situation current SDFT implementations, such as three-dimensional reference interaction site model (3D-RISM), lead to nonphysical results. We re-examine this issue in this work using our recent reformulation of SDFT. We put forward a simple practical solution to this problem, and illustrate its utility for the case of spherical solutes in diatomic liquids.

Chuev, Gennady N.↗