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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗
DOE OSTI2023

Anomalous near-equilibrium capillary imbibition induced by nanoscale surface topography

Here, this work reports that the nanoscale surface topography induces a crossover from the classical Lucas–Washburn imbibition dynamics to a long-lived anomalously slow regime observed near thermodynamic equilibrium conditions. A compact analytical model considering the interplay between interfacial wetting, thermal motion, and the nanoscale physical topography accounts for experimental observations for the case of capillary rise of different nonvolatile liquids in simple glass tubes. Analytical predictions supported by topographic analysis via atomic force microscopy indicate that topographic features with a specific range of nanoscale dimensions determine the crossover condition and anomalous imbibition rate. Our findings have important implications for the scientific understanding and technical application of capillary imbibition and suggest strategies to control the adsorption of specific liquids in porous materials with complex surface topography.

Capillary driven imbibition↗
DOE OSTI2021

High‐efficiency adsorption of various heavy metals by tea residue biochar loaded with nanoscale zero‐valent iron

Abstract Nanoscale zero‐valent iron (nZVI) loaded on tea residue biochar activated with phosphoric acid composites was synthesized. This adsorbent can efficiently adsorb multiple heavy metal ions such as Pb (II), Cr (III), Cu (II), and Ni (II) simultaneously. The adsorption process was found to follow the pseudo‐second‐order kinetic model. Equilibrium adsorption capacities reached 288.18, 162.34, 242.72, and 267.22 mg·g −1 for Pb(II), Cr(III), Cu(II), and Ni(II), respectively. The common interfering ions exhibited lower influence on its adsorption capacity. The adsorption mechanism includes reduction, ion exchange, surface complexation and precipitation. Furthermore, the waste adsorbent was converted into a catalyst in situ, which could catalyze the degradation of Congo red by establishing an electron transfer pathway. This research provides a new concept for the sustainable utilization of industrial tea residues and the harmless treatment of waste nZVI composite adsorbents.

Liu, Shuang↗
DOE OSTI2024

Regulation of Electron Cloud Density by Electronic Effects of Substituents to Optimize Photocatalytic H 2 Evolution of Carbon Dots

Carbon dots (CDs) have a wide light absorption range, which are promising candidates for photocatalytic water splitting H 2 evolution, but they show low activity for hydrogen evolution reaction (HER) due to the slow transfer efficiencies of photogenerated carriers. The electron cloud density of photocatalyst is essential for the separation and migration of photogenerated carriers. In this study, the effect mechanism of electron cloud density regulated by the substituents with different electronic effects on the photocatalytic HER of glucose-based CDs is clarified. CDs-SO 3 H and CDs-OH are first obtained by introducing electron-drawing group (–SO 3 H) and electron-donating group (–OH) using a tailoring post-processing strategy. Experimental results show that the H 2 yield catalyzed by CDs-SO 3 H is 89.95 µmol•g –1 in 4 h, which is about four times that of CDs, and 7.4 times that of CDs-OH. The –SO 3 H induces a much negative energy band and high electron cloud density on CDs edges, promoting the separation and transfer of photogenerated carriers; while the CDs-OH exhibits a high positive charge density and an upward energy band, hindering the surface complexation of electron-hole pairs and HER. Furthermore, this study will provide an insight into the design of CDs catalysts with efficient photocatalytic HER at a molecular level.

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

“Lagrangian disks” in M-theory

While the study of bordered (pseudo-)holomorphic curves with boundary on Lagrangian submanifolds has a long history, a similar problem that involves (special) Lagrangian submanifolds with boundary on complex surfaces appears to be largely overlooked in both physics and math literature. We relate this problem to geometry of coassociative submanifolds in G 2 holonomy spaces and to Spin(7) metrics on 8-manifolds with T 2 fibrations. As an application to physics, we propose a large class of brane models in type IIA string theory that generalize brane brick models on the one hand and 2d theories T[M 4 ] on the other.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantifying the atomistic free-volume morphology of materials with graph theory

Here, we introduce a new computational methodology for the identification and characterization of free volume within/around atomistic configurations. This scheme employs a three-stage workflow, by which spheres are iteratively grown inside of voxels, and ultimately converted to planar graphs, which are then characterized via a graph-based order parameter. Our approach is computationally efficient, physically intuitive, and universally transferable to any material system. Validation of our methodology is performed on several sets of materials problems: (1) classification of unique free volumes in various crystal phases, (2) autonomous detection and classification of complex surface defects during epitaxial growth simulations, (3) characterization of free volume defects in metals/alloys, and (4) quantification of the spatio-temporal behavior of nano-scale free volume morphologies as a function of both temperature and free-volume size. Our method accurately identifies and characterizes unique free volumes over a multitude of systems and length scales, indicating its potential for future use in understanding the relationship between free volume morphology and material properties under both static and dynamic conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effects of crystallographic orientation on calcite dissolution under alkaline conditions

Here, this study investigates the dissolution of calcite’s (104) and (100) surfaces under alkaline conditions (pH 8.8–13.1) using vertical scanning interferometry under flow-through conditions. The dissolution rate of (100) surfaces decreases with increasing pH. For example, the dissolution rate at pH 8.8 is more than 20 times higher than that at pH 13.1. In contrast, the dissolution rate of (104) surfaces is far less sensitive to pH. We explain these observations as being on account of the preferential adsorption of [OH – ] on (100) surfaces, inhibiting their dissolution. Particularly, this is because Ca-surface sites on (100) surfaces are less coordinated and have a stronger tendency for [OH – ] adsorption. As a result, (100) surfaces dissolve nearly twice as fast as (104) surfaces at pH 8.8, whereas (104) surfaces dissolved ~4.5 times faster than (100) surfaces at pH 13.1; indicating an inversion in dissolution behavior. The dissolution rate of (104) surfaces at pH 13.1 is 60 % of the rate at pH 10–12 because of the formation of slow dissolving microfacets of other orientations. The rhombohedral dissolution etch-pits formed on (104) surfaces, at lower pH’s, disappeared upon exposure to solutions with pH > 12 and were replaced by protrusions. The addition of up to 4m (molality) NaCl enhances the dissolution of (104) surfaces at pH 8.8–13.1 and (100) surfaces at pH 8.8–11.0, and inhibited the dissolution of (100) surfaces at pH = 12.0–13.1. In addition, the competing adsorption between OH – and CO 3 2– species mitigates the inhibition effects of CO 3 2– on both surfaces at pH 13.1 compared to pH 11, and the dissolution of (100) surfaces is far less affected by CO 3 2– than (104) surfaces. These results provide new insights into the rates and mechanisms of how crystallographic orientations affect calcite’s dissolution at alkaline pH conditions.

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

Fate of arsenic during the interactions between Mn-substituted goethite and dissolved Fe(II)

Geogenic arsenic has become a globally-distributed groundwater contaminant, liberated from the weathering of arsenic-bearing sulfide minerals and often transported to aquifer sediments adsorbed to iron oxides. Among the iron oxides, goethite (α-FeOOH) is uniquely important for the fate of arsenic because of its widespread abundance, stability, and high affinity for binding arsenic. Goethite is ubiquitous in soils and sediments and often contains substituted elements, including manganese. Structural manganese may affect the surface reactivity and redox capacity of goethite and alter the mechanisms of recrystallization catalyzed by dissolved Fe(II), potentially affecting arsenic adsorption. Here, this study examined the fate of As(V) during the interactions between dissolved Fe(II) and Mn-substituted goethites at pH 4 and 7 as well as associated changes in arsenic speciation. At pH 7, the addition of dissolved Fe(II) initially increases the adsorption of As(V) onto Mn-bearing and Mn-free goethites. For the Mn-substituted goethites, the adsorbed As(V) slowly releases to solution at longer aging times. Fe(II) addition at pH 4 slightly increases As(V) uptake by Mn-substituted goethites, with differences in total sorption correlating with the Mn content in goethite. The addition of Fe(II) releases substantial dissolved manganese but the amount solubilized is higher at pH 4 compared to 7, suggesting that the presence of adsorbed As(V) may substantially promote the Mn release at pH 4. X-ray absorption fine structure spectroscopy shows that arsenic is stabilized as As(V) in all the samples and adsorbed on goethite via a bidentate binuclear mechanism. Fitting results show that the binding distance and coordination numbers are stable in Mn-free goethite and Mn-substituted goethite samples; the effect of substituted Mn on the surface complex structure is minor. High resolution transmission electron microscopy and X-ray diffraction confirm that no secondary ferrous arsenate minerals precipitate under both pH conditions. This study improves our understanding of the Fe(II)-As(V) interactions on iron oxides, and demonstrates that the substituted cations such as manganese may quantitatively alter the geochemical fate of arsenic during the reaction of dissolved Fe(II) with Fe(III) oxides.

58 GEOSCIENCES↗
DOE OSTI2026

Computer simulation of reaction and transport of core-scale serpentinization of Fe-bearing olivine and evolution of geological hydrogen

We present reactive flow and transport simulations of core-scale serpentinization of forsteritic, Fe-bearing olivine under hydrothermal conditions. The model captures fluid flow, evolving porosity–permeability, and redox-controlled H 2 production in a cylindrical core over 55 days at 245 °C and 37 bar. Key processes include olivine dissolution, precipitation of serpentine and magnetite, and oxidation of Fe2+ to Fe 3+ . Here, results show strong coupling among flow velocity, alteration front propagation, and spatially heterogeneous H 2 generation. Elevated H2 concentrations align with inlet-localized magnetite precipitation, consistent with experiments. Secondary mineral formation reduces porosity and permeability, altering transport pathways. Reactive flow at the fluid–solid interface governs H 2 generation rates and distribution. Dissolved SiO2 promotes serpentine and talc formation by suppressing brucite, while bicarbonate extends reaction duration and moderates surface complexation effects.

Geologic hydrogen↗
DOE OSTI2020

Surface Reactivity Analysis of the Crude Oil–Brine–Limestone Interface for a Comprehensive Understanding of the Low-Salinity Waterflooding Mechanism

Low-salinity waterflooding (LSWF) has proven to improve oil recovery in carbonate formations through rock wettability alteration, although the underlying mechanism remains elusive. Multivalent ionic exchange and calcite dissolution have usually been investigated using geochemical analysis in secondary coreflooding. In this work, coreflooding, in tertiary mode, coupled with a surface reactivity analysis approach was employed to investigate the interplay of wettability alteration mechanisms such as mineral dissolution, electrostatic bond attraction, and the effect of pH at in situ conditions. Improved oil recovery (IOR) in tertiary mode observed by coreflooding in Indiana limestone rocks showed an ionic strength dependence, that is, reducing brine ionic strength resulted in an increase in oil recovery. Coreflooding results showed that the seawater and low-salinity brines deprived of Mg 2+ ions resulted in the lowest IOR in tertiary mode, indicating the significance of Mg 2+ on IOR in limestone rocks. Similar results were observed through the contact angle measurement showing the limestone rock wettability state dependence on ionic strength and the effect of Mg2+ ions. Surface reactivity analysis showed an increase in solution pH, Ca 2+ and Mg 2+ ions concentration in the effluent solution from the coreflooding in tertiary mode using low salinity brines (about 40 and 20% increase in the effluent composition for Ca 2+ and Mg 2+ , respectively). These changes in solution composition were used to calculate the in situ oil–brine and rock–brine zeta potential using a validated surface complexation model, showing the changes of zeta potential as brine is injected into limestone rocks. The results show that using seawater-like brine in tertiary mode resulted in no mineral dissolution or ionic exchange. However, improved oil recovery (IOR) using such seawater-like brine was due to wettability alteration caused by reduced electrostatic bond attraction associated with Mg 2+ ions [from 2.6 × 10 –13 (mol/m 2 ) 2 for formation water salinity to 1.5 × 10 –13 (mol/m 2 ) 2 for seawater salinity]. Using low-salinity brines in tertiary mode improved oil recovery by mineral dissolution, resulting in oil desorption and an increase in solution pH. Finally, the increase in solution pH also resulted in reduced electrostatic bond attraction which lead to rock wettability alteration using low-salinity brines.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2024

Invariant Molecular Representations for Heterogeneous Catalysis

Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used. This study introduces a novel machine learning (ML) method to learn adsorption energies from multiple DFT functionals by using invariant molecular representations (IMRs). To do this, we first extract molecular fingerprints for the reaction intermediates and later use a Siamese-neural-network-based training strategy to learn invariant molecular representations or the IMR across all available functionals. Our Siamese network-based representations demonstrate superior performance in predicting adsorption energies compared with other molecular representations. Notably, when considering mean absolute values of adsorption energies as 0.43 eV (PBE-D3), 0.46 eV (BEEF-vdW), 0.81 eV (RPBE), and 0.37 eV (scan+rVV10), our IMR method has achieved the lowest mean absolute errors (MAEs) of 0.18 0.10, 0.16, and 0.18 eV, respectively. These results emphasize the superior predictive capacity of our Siamese network-based representations. The empirical findings in this study illuminate the efficacy, robustness, and dependability of our proposed ML paradigm in predicting adsorption energies, specifically for propane dehydrogenation on a platinum catalyst surface.

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

Toward Understanding and Controlling Organic Reactions on Metal Oxide Catalysts

Metal oxides have structurally complex surfaces on which a variety of adsorption site types can occur, including cation sites, anion sites, oxygen vacancy sites, and Brønsted acid sites. These sites can catalyze the catalytic transformation of organic molecules via diverse routes, thus enabling H abstraction, O abstraction, C–C bond formation, and other reactions. This Perspective provides an update on recent advances and future directions for various organic reactions on metal oxide catalyst surfaces, particularly for C–H activation of alkanes and for C–C bond formation with organic oxygenate reactants. Here, we put emphasis on the molecular scale details, on the active site structures required to enable the formation of kinetically relevant transition states, energetic descriptors, as well as contemporary ideas to enable low activation energies. This progress has been enabled by specialized experiments and the increased capabilities of modern electronic structure calculations.

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

Revealing an Intermediate Cu–O/OH Superstructure on Cu(110)

Identifying the atomic structure and formation mechanism of intermediates during chemical transformations is challenging because of their short-lived nature. With a combination of microscopic and spectroscopic measurements and first-principles calculations, herein we report the formation of a metastable intermediate Cu–O/OH superstructure during the reaction of hydrogen with oxygen-covered Cu(110). This superstructure resembles the parent c(6 × 2)-O phase and can be termed as c(6 × 2)-(4O+2OH) with OH groups occupying the missing Cu sites between isolated Cu atoms. Using atomistic calculations, we elucidate the reaction pathways leading to the c(6 × 2)-(4O+2OH) formation via both molecular and dissociative H 2 adsorption. In this work, the results demonstrate the complex surface dynamics resulting from the parallel reaction pathways and may open up the possibility of directing the reaction dynamics by deliberately manipulating transient surface structure and composition.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unveiling the Electrocatalytic Hydrogen Evolution Reaction Pathway on RuP 2 through Ab Initio Grand Canonical Monte Carlo

In this study, the high catalytic reactivity of ruthenium phosphide (RuP 2 ) has been identified by first-principles density functional theory (DFT) calculations for the electrocatalytic hydrogen evolution reaction (HER). Complex surface reconstructions are considered by applying the ab initio grand canonical Monte Carlo (ai-GCMC) algorithm, efficiently providing a sufficient phase-space exploration of possible surfaces. Combined with surface-phase Pourbaix diagrams, we are able to identify the actual surfaces that obtained under specific experimental environments, thus leading to a more accurate understanding of the nature of the active sites and the binding strength of adsorbates. Specifically, through hundreds of surface reconstructions and hydrogenation states generated with ai-GCMC, we identify the most favorable surface phases of RuP 2 under aqueous acidic conditions. We discover that the HER activity is determined by multiple surfaces with different stoichiometries within a narrow electrode potential window. Low HER overpotential (η) has been found for each of the identified surfaces, as low as 0.04 V. High H-coverage reconstructed surfaces have been discovered under acidic conditions, and the surface Ru sites introduced by additional Ru adatoms or exposed by P-vacancies serve as the active sites for HER based on their nearly reversible H binding. Furthermore, this work provides atomistic insights into the origin of high HER activity on RuP 2 by exploring the dynamic surface phases of electrocatalysts and features a generalizable method to explore the reconstructed/hydrogenated surface space as a function of experimental conditions.

25 ENERGY STORAGE↗
DOE OSTI2026

Achieving Phase Control of Polymorphic Tungsten Carbide Catalysts

The polymorphism of tungsten carbide (W x C) and the challenge of selectively synthesizing pure phases have impeded a precise understanding of catalytic structure−property relationships. This study establishes a framework for phase-selective synthesis of W x C through controlling carburization kinetics. By maintaining particle sizes below 10 nm, β-W 2 C is selectively synthesized using gaseous carbon precursors (CH 4 /H 2 ) via temperature-programmed carburization (TPC). Our findings reveal that W 2 C stabilization is predominantly dictated by particle size and carburization kinetics rather than support interactions, providing a tunable approach to synthesize tungsten carbide catalysts. We elucidate the mechanistic pathway of WO x carburization, demonstrating that CH 4 activation occurs at mild temperatures via lattice oxygen. Our reactor studies establish ex situ synthesized β- W 2 C as an active and stable catalyst for the reverse water-gas shift (RWGS) reaction. However, the need for passivation and reduction pretreatment leads to a complex surface structure with diminished intrinsic activity. In contrast, our in situ synthesis protocol for β-W 2 C eliminates the need for passivation and exhibits increased CO STY during RWGS, illustrating the intrinsically higher activity compared to metallic W, WC 1−x (0.5 < x < 1), and stoichiometric WC.

CO2 conversion↗
DOE OSTI2020

Spectroscopic Probe Molecule Selection Using Quantum Theory, First-Principles Calculations, and Machine Learning

Probe molecule vibrational spectra have a long history of being used to characterize materials including metals, oxides, metal-organic frameworks, and even human proteins. Furthermore, recent advances in machine learning have enabled computationally generated spectra to aid in detailed characterization of complex surfaces with probe molecules. Despite widespread use of probe molecules, the science of probe molecule selection is underdeveloped. Here, we develop physical concepts, including orbital interaction energy and the energy overlap integral, to explain and predict the ability of probe molecules to discriminate structural descriptors. We resolve the crystal orbital overlap population (COOP) to specific molecular orbitals and quantify their bonding character, which directly influences vibrational frequencies. Using only a single adsorbate calculation from density function theory (DFT), we compute the interaction energy of individual adsorbate molecular orbitals with adsorption site atomic orbitals across many different sites. Combining the molecular orbital resolved COOP and changes in orbital interaction energy enables probe molecule selection for improved discrimination of various sites. We demonstrate these concepts by comparing the predicted effectiveness of carbon monoxide (CO), nitric oxide (NO), and ethylene (C 2 H 4 ) to probe Pt adsorption sites. Finally, using a previously developed machine learning framework, we show that models trained on hundreds of thousand C 2 H 4 spectra, computed from DFT, which regress surface binding-type and generalized coordination number (GCN), outperform those trained using CO and NO spectra. Lastly, a python package, pDOS_overlap, for implementing the electron density based analysis on any combination of adsorbates and materials, is also made available.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Resolving experimental biases in the interpretation of diffusion experiments with a user-friendly numerical reactive transport approach

The reactive transport code CrunchClay was used to derive effective diffusion coefficients (D e ), clay porosities (ε), and adsorption distribution coefficients (K D ) from through-diffusion data while considering accurately the influence of unavoidable experimental biases on the estimation of these diffusion parameters. These effects include the presence of filters holding the solid sample in place, the variations in concentration gradients across the diffusion cell due to sampling events, the impact of tubing/dead volumes on the estimation of diffusive fluxes and sample porosity, and the effects of O-ring-filter setups on the delivery of solutions to the clay packing. Doing so, the direct modeling of the measurements of (radio)tracer concentrations in reservoirs is more accurate than that of data converted directly into diffusive fluxes. While the above-mentioned effects have already been described individually in the literature, a consistent modeling approach addressing all these issues at the same time has never been described nor made easily available to the community. A graphical user interface, CrunchEase, was created, which supports the user by automating the creation of input files, the running of simulations, and the extraction and comparison of data and simulation results. While a classical model considering an effective diffusion coefficient, a porosity and a solid/solution distribution coefficient (D e –ε–K D ) may be implemented in any reactive transport code, the development of CrunchEase makes it easy to apply by experimentalists without a background in reactive transport modeling. CrunchEase makes it also possible to transition more easily from a D e –ε–K D modeling approach to a state-of-the-art process-based understanding modeling approach using the full capabilities of CrunchClay, which include surface complexation modeling and a multi-porosity description of the clay packing with charged diffuse layers.

58 GEOSCIENCES↗