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At least 721 records · Page 40

Spin Polarization Enhanced Ethanol Selectivity in Electrocatalytic CO 2 Reduction on the Paramagnetic CuO Surface

We report an electrochemical CO 2 reduction reaction catalyzed by a paramagnetic and conductive CuO/Cu interface with spins polarized by a moderate external magnetic field (MF) of similar to 800 gauss, achieving a similar to 30% increase in CO 2 -to-C 2+ Faradaic efficiency (FE) compared to that in the absence of the MF in a flow cell electrolyzer. At a current density of 400 mA/cm 2 , the CO 2 -to-C 2+ FE reached 86.7 ± 2.7% with 47.9 ± 1.4% cathodic energy efficiency (EE) in contrast to the CO 2 -to-C 2+ FE of 67.6% with 36.4% of EE in the absence of MF. Notably, ethanol production exhibits a much higher response to the MF (similar to 55.6% increase in FE) than ethylene (similar to 6.4% increase in FE) at 400 mA/cm 2 . In situ surface-enhanced Raman spectroscopy (SERS) captured magnetic-field-enhanced *CO coverage and ethanol-forming C 2 intermediates on CuO/Cu, providing direct spectroscopic evidence of spin-modulated pathway selection. Here, computational study suggests that the enhancement of ethanol selectivity is due to the reduced reaction kinetic barrier under MF, while the ethylene selectivity is less affected, mainly due to the insensitivity of the kinetic barriers under MF.

10 SYNTHETIC FUELS↗

Study of Tritium Transport in Nuclear-Grade Graphite and Molten Fluoride Salt Systems

High-temperature salts are proposed as coolant in recent reactor technologies including Fluoride Salt-Cooled High Temperature Reactor (FHR) with fluoride salt as primary and secondary loop coolant, Molten Salt Reactors (MSRs) with fuel salt, and high-magnetic-field fusion machines with salt coolant blanket. The baseline coolant is {sup 7}Li{sub 2}BeF{sub 4} (flibe) due to its good thermal-hydraulic and neutronic properties. Tritium produced in flibe due to neutron irradiation makes the issue of tritium transport an area of great interest. In the temperature range of 427- 704 deg. C, tritium readily diffuses through metallic reactor structural materials, which makes tritium control and capture a key technical challenge. It is anticipated that tritium can be captured by graphite, as graphite material showed a high affinity for tritium in the Molten Salt Reactor Experiment (MSRE) due to the porous and irregular crystallite microstructure. Two types of nuclear grade graphite which used as core components for FHR: matrix graphite, which encapsulates the TRISO (Tri-structural-isotropic) fuel particles in FHR, and high purity, isotropic nuclear grade graphite IG-110 which can be used as moderator and reflector in reactor core for both fission and fusion reactor. The microstructure of matrix graphite and IG-110 is different from that of matrix graphite, due to the raw material and manufacturing processes. There are three phenomena important for predicting tritium transport in graphite-salt systems: tritium species diffusion in molten flibe; tritium species transport at the salt-graphite interface; and tritium species transport in graphite. In this summary microstructure characterization of IG-110 and matrix graphite, characterization of graphite-salt interface as well as techniques for trace tritium detection in graphite are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DyG-DPCD: A Distributed Parallel Community Detection Algorithm for Large-Scale Dynamic Graphs

Dynamic (Temporal) graphs capture the valuable evolution of real-world systems, from the continuously evolving patterns of social interactions and genetic pathways to the dynamic fluctuations of economic forces. Detecting communities for such evolving networks poses unique challenges. Detecting and analyzing the evolution of communities within dynamic graphs unlocks valuable insights into the underlying structural and temporal patterns of real-world systems. However, the sheer volume of modern graph data and the inherent complexity of the temporal dimension pose significant challenges to scalable community detection algorithms. Addressing this gap, our work explores the limited landscape of scalable distributed-memory parallel methods specifically designed for dynamic network community detection. We propose a novel parallel algorithm, DyG-DPCD (Dynamic Graph Distributed Parallel Community Detection), to detect communities in dynamic networks using the Message Passing Interface (MPI) framework. We present a vertex-centric approach, allowing us to detect communities through local optimization. Furthermore, we enhance our baseline algorithm by incorporating three heuristics, which improve the algorithm’s performance significantly while maintaining the quality of the solutions. We demonstrate the efficiency of our algorithm by experimenting on several real-world large-scale networks with hundreds of millions of edges spanning diverse domains. Notably, DyG-DPCD achieves speedups between 25× and 30× for large networks that we experimented on using NERSC compute nodes. In conclusion, our algorithm outperforms the STINGER parallel re-agglomeration algorithm by 30×.

97 MATHEMATICS AND COMPUTING↗

Microstructure, Transport, and Mechanics of Compacted Clay Simulated at the 0.1 μm Scale (1400 Smectite Clay Particles) Using a Coarse-Grained Model with Explicit Counterions

Clay-rich geomaterials play a critical role in many subsurface systems. The macroscale properties of these materials (low permeability, high ionic conductivity, high swelling pressure, etc.) are sensitive to molecular-level adsorption and hydration interactions at clay−water interfaces. Efforts to develop multiscale simulation approaches to predict these properties reveal a scale gap between atomistic simulations (typically limited to systems smaller than 10 nm) and continuum-scale models (which use computational grid elements with dimensions ≳ 10 μm). In this study, we present a coarse-grained (CG) framework that partly bridges this gap by simulating compacted smectite clay assemblages with dimensions of 0.1 μm containing 1,400 clay particles across a range of dry densities (1,050 to 1,850 kg·m −3 ) and Na/Ca counterion compositions (Na fraction ranging from 0.2 to 1). The simulated systems, along with their reconstructed binary three-dimensional pore networks, are used to evaluate the microstructure, pore size distribution, tortuosity, ion diffusivity, and swelling pressure of compacted smectite clay. Results show that our approach captures important features of the mesoscale heterogeneity of compacted clays, including tactoid formation, hierarchical porosity, and anisotropic pore networks. Results also reveal how compaction and counterion composition govern emergent behaviors, including dominant pore sizes, directional transport, and electrochemical response. This work highlights the potential of CG simulations to bridge molecular and continuum scales and to advance geotechnical and environmental applications involving clay-rich materials as well as related nanoporous media such as geopolymers and calcium-silicate-hydrate. However, the results also suggest that accurate prediction of certain microstructural and mechanical properties (e.g., swelling pressure) may require even larger-scale systems on the order of 1 μm.

02 PETROLEUM↗

Enabling discovery data science through cross-facility workflows

Experimental and observational instruments for scientific research (such as light sources, genome sequencers, accelerators, telescopes and electron microscopes) increasingly require High Performance Computing (HPC) scale capabilities for data analysis and workflow processing. Next-generation instruments are being deployed with higher resolutions and faster data capture rates, creating a big data crunch that cannot be handled by modest institutional computing resources. Often these big data analysis pipelines also require near real-time computing and have higher resilience requirements than the simulation and modeling workloads more traditionally seen at HPC centers. While some facilities have enabled workflows to run at a single HPC facility, there is a growing need to integrate capabilities across HPC facilities to enable cross-facility workflows, either to provide resilience to an experiment, increase analysis throughput capabilities, or to better match a workflow to a particular architecture. In this paper we describe the barriers to executing complex data analysis workflows across HPC facilities and propose an architectural design pattern for enabling scientific discovery using cross-facility workflows that includes orchestration services, application programming interfaces (APIs), data access and co-scheduling.

Antypas, Katerina B.↗

Quantifying heterogeneous deformation in grain boundary regions on shock loaded tantalum using spherical and sharp tip nanoindentation

Grain boundaries play an important role in the overall mechanical performance of metals and alloys; however, isolating the effects of individual grain boundaries remains rather challenging experimentally. In this work, wire-feed, electron beam additively manufactured tantalum is studied under shock loading conditions generating incipient spall damage. Three grain boundaries aligned parallel to the shock direction were isolated inside a single sample. Postmortem metallography showed voids preferentially appeared on two of the three grain boundaries which had high misorientation angles > 30° compared to the third grain boundary with a relatively lower misorientation angle < 10°. Nanoindentation in grain boundary regions for both pyramidal and spherical tips showed characteristically different strain hardening trends for each grain boundary. Significant local strain hardening is present on both sides of one high angle grain boundary, while strain softening is captured at the other high angle grain boundary. A negligible trend of either hardening or softening is shown in the vicinity of the single low angle grain boundary. As a result, this leads to the conclusion that the trend of strain hardening/softening in grain boundary regions is not monotonically correlated to the susceptibility of specific grain boundaries to an increased propensity for void damage.

36 MATERIALS SCIENCE↗

In-situ probing of coupled atomic restructuring and metallicity of oxide heterointerfaces induced by polar adsorbates

Microscopic understanding of the surface-controlled conductivity of the two dimensional electron gas at complex oxide interfaces is crucial for developing functional interfaces. We observe conductivity and structural modification using in-situ synchrotron surface x-ray diffraction as the surface of a model LaAlO 3 /SrTiO 3 (001) heterostructure is changed by polar adsorbates. We find that polar adsorbate-induced interfacial metallicity reduces polar distortions in the LaAlO 3 layer. First-principles density functional theory calculations show that surface dipoles introduced by polar adsorbates lead to additional charge transfer and the reduction of polar displacements in the LaAlO 3 layer, consistent with the experimental observations. Our study supports that internal structural deformations controlling functionalities can be driven without the application of direct electrical or thermal bias and offers a route to tuning interfacial properties. Furthermore, these results also highlight the important role of in-situ x-ray scattering with atomic resolution in capturing and exploring structural distortions and charge density changes caused by external perturbations such as chemical adsorption, redox reaction, and generation and/or annihilation of surface defects.

74 ATOMIC AND MOLECULAR PHYSICS↗

Dynamics of plasma atomic layer etching: Molecular dynamics simulations and optical emission spectroscopy

Atomic layer etching is intrinsically dynamic as it involves sequential and repeated exposures of a surface to be etched with different species at different energies. The composition and structure of the near surface region change in both time and depth. Full understanding of this process requires resolving both temporal and spatial variations. In this work, we consider silicon (Si) atomic layer etching (ALE) by alternating exposure to chlorine gas (Cl 2 ) and argon ions (Ar + ). Molecular dynamics (MD) simulations are compared to experimental measurements with the aim of better understanding the dynamics of ALE and to test the simulation procedure. The simulations help to more fully interpret the experimental measurements. Further, optical emission measured just above the surface being etched can be related to etch products and can, therefore, be directly compared to simulation predictions. The simulations capture the measured initial product distribution leaving the surface and match the measured etch per cycle reasonably well. While simulations demonstrate the importance of ion-induced surface damage and mixing into a layer below the surface, the depth of which depends mainly on ion energy, the experiments suggest there is more Cl mixed into the layer than the MD procedure predicts.

74 ATOMIC AND MOLECULAR PHYSICS↗

Titanium-Carbide Formation at Defective Curved Graphene-Titanium Interfaces

ABSTRACT Physical and chemical properties of graphene-metal interfaces have been largely examined with the objective of producing nanostructured carbon-based electronic devices. Although electronic properties are key to such devices, appropriate structural, thermal and mechanical properties are important for device performance as well. One of the most studied is the graphene-titanium (G-Ti) interface. Titanium is a low density, high strength versatile metal that can form alloys with desirable properties for applications ranging from aerospace to medicine. Small clusters and thin films of titanium deposited on graphene have also been examined. However, while some experiments show that thin films of titanium on graphene can be removed without damaging graphene hexagonal structure, others reported the formation of titanium-carbide (TiC) at G-Ti interfaces. In a previous work [ACS Appl. Mater. Interfaces, 2017, 9 (38), pp 33288-33297], we have shown that pristine G-Ti interfaces are resilient to large thermal fluctuations even when G-Ti structures lie on curved or kinked substrates. Here, using classical molecular dynamics with the third-generation Charge Optimized Many Body (COMB3) potential, we show that di-interstitial defective G-Ti structures on a copper substrate with a relatively large curvature kink, present signs of TiC formation. This result might help explain the different experimental results mentioned above.

catalysis (heterogeneous), defects, membrane, carb↗

Equilibria and Rate Phenomena from Atomistic to Mesoscale: Simulation Studies of Magnetite

Batteries are complex devices composed of multiple components that operate far from equilibrium and may operate under extreme stress and varying loads. Research of isolated battery components are valuable to the fundamental understanding of the physical processes occurring within each constituent element. When the components are integrated into a full device and operated under realistic conditions, it can be difficult to decouple the physical processes that occur across multiple interfaces and multiple length scales. Thus, the physical processes studied in isolated components may change in a full battery setup or may be irrelevant to performance. Simulation studies on many length scales play a key role in the analysis of experiments and in the elucidation of the relevant physical processes impacting performance. In this Account, we aim to highlight the use of modeling on multiple length scales to identify rate limiting phenomena in lithium-ion batteries. To illustrate the utility of modeling, we examine lithium-ion batteries with nanostructured magnetite, Fe 3 O 4 , as the positive electrode active material against a solid Li 0 negative electrode. Due to continuous operation away from equilibrium, batteries exhibit highly nonideal behavior, and a model that aims to reproduce behavior under realistic operating conditions must be able to capture the physics occurring on the length scales relevant to the performance of the system. It is our experience that limiting behavior in lithium-ion batteries can be observed on the atomic scale and up through the electrode scale and thus, predictive models must be capable of integrating and communicating physics across multiple length scales. Magnetite is studied as an electrode material for lithium-ion batteries, but it is found to suffer from slow solid-state transport of lithium, slow reaction kinetics, and poor cycling. Magnetite (Fe 3 O 4 ) is a material capable of undergoing multiple electron transfers (MET), and can accept up to eight lithium per formula unit (Li 8 Fe 3 O 4 ). Magnetite, (Fe 8a 3+ )[Fe 3+ Fe 2+ ] 16d O 4,32e 2– , has a close-packed inverse spinel structure and undergoes intercalation, structural rearrangement, and conversion reactions upon full lithiation. To overcome solid-state transport resistances, magnetite can be nanostructured to decrease Li + diffusion lengths, and this has been shown to increase capacity. Additionally, unique architectures incorporating both carbon and Fe 3 O 4 have shown to alleviate transport and cycling issues in the material. Here, we solely address traditional composite electrodes, in which Fe 3 O 4 is synthesized as nanoparticles and combined with additives to fabricate the electrode. In the case of nanoparticulate magnetite, it has been found that the electrode fabrication process results in the formation of micrometer-sized agglomerates of the Fe 3 O 4 nanoparticles, introducing a secondary structural motif. The agglomerates may form in one or more fabrication processes, and their elimination may not be straightforward or warranted. Here, we highlight the impact of these secondary formations on the performance of the Fe 3 O 4 lithium-ion battery. We illustrate how simulations can be used to design experiments, prioritize research efforts, and predict performance.

25 ENERGY STORAGE↗

Low Carbon Inducible2/Fatty Acid Desaturase4 locus in C. reinhardtii directs plastid peroxidase location and trans fatty acid production

Light capture and photosynthetic energy conversion depend on photosynthetic complexes that are embedded within lipid membranes. Components of these complexes are vulnerable to damage by reactive oxygen species, byproducts of photosynthesis that accumulate under environmental stress. Here we explore the basis for a lipid-based sensing mechanism allowing plants or algae to assess and respond to damage to the photosynthetic membranes. In Chlamydomonas reinhardtii, Low Carbon Inducible2 (LCI2) and Fatty Acid Desaturase4 (FAD4) are two proteins derived from the same locus by a differential splicing event, sharing an N-terminus encoded by the first two exons. FAD4 produces a 16-carbon, trans double bond-containing fatty acid found exclusively in phosphatidylglycerol of chloroplast membranes, while LCI2 recruits peroxidase activity to the membrane. The unique organization and transcriptional regulation of the LCI2/FAD4 locus represents a regulatory interface that allows cells to initiate the biosynthesis of a fatty acid unique to the photosynthetic membranes while also linking it to the production of an enzyme involved in the mitigation of reactive oxygen species.

Nicodemus, Timothy J [Michigan State University, E↗

Predicting a Key Catalyst-Performance Descriptor for Supported Metal Nanoparticles: Metal Chemical Potential

The chemical potential of metal atoms in supported nanoparticles provides a convenient descriptor of their performance as heterogeneous catalysts that captures the effects of particle size, support and alloying. Based on microcalorimetric measurements, the chemical potential is shown in this work to be predictable as a function of monometallic particle diameter and the adhesion energy of the particle to the support, and, for oxide supports, this adhesion energy correlates predictably with metal oxophilicity. These correlations provide predictions of metal chemical potential that can enable catalyst design. They also suggest an improvement in the Gibbs-Thomson relation for free-standing nanoparticles, whether metals or molecular solids.

metal/oxide interface↗

A hydrogeophysical framework to assess infiltration during a simulated ecosystem-scale flooding experiment

This study presents a framework to quantify changes in soil saturation in response to flooding caused by extreme hydrologic perturbation on coastal ecosystems at the interfaces and transition between terrestrial and aquatic systems. Subsurface heterogeneity limits the use of in situ measurements to quantify subsurface flow during flooding due to the spatial discontinuity in the measured data. While geophysical methods, including time-lapse electrical resistivity imaging (ERI), are increasingly used to monitor soil hydrological processes, their abilities to parameterize flow models have been underutilized. This study combines background ERI, ground penetrating radar (GPR), time-lapse ERI, soil characterization, and a numerical flow model developed using an Advanced Terrestrial Simulator (ATS) code to quantify the infiltration pathway and describe the hydrological dynamics during a simulated flooding experiment. We assessed the use of two conceptual models developed using [1] ERI and GPR data that described the stratigraphic distribution, and time-lapse ERI that mapped permeability contrast, and [2] information from a national soil database for capturing changes in saturation. Combining the ERI and GPR results with soil core data revealed the stratigraphic heterogeneity at the site with a silty clay layer from 1 to 2 m between an overlying loamy topsoil and an underlying saturated silty sand. This silty clay layer could restrict deep infiltration. The time-lapse ERI showed up to a 35% decrease in resistivity, which correlated with soil moisture data (R 2 value > 0.53) and revealed preferential infiltration zones used to inform the flow model. Numerical simulation results from both the geophysics- and soil database-informed models quantified changes in soil saturation with calculated soil moistures that agreed with field data. The geophysics-informed model captured more of the system’s variability, reflective of shallow subsurface heterogeneities. The framework presented will serve as a precursor for a robust ecohydrological model that can describe the impacts of extreme events induced by climate change on coastal ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Understanding Hydrogen Passivation Mechanism in Poly-Si Passivating Contacts: Insights from Effusion Studies

Silicon PV is the dominant PV technology, and captures >95% world market share, supporting -100 GW/year. Diffused and passivated pn junctions along with other rear side passivation technologies are the mainstream technologies and will continue to remain so in the coming decades. Passivated contacts, using tunnel oxide passivation stacks at the rear side, will gain market share from about 10% in 2022 up to 58% within the next 10 years. Most mature approaches use passivating layers of hydrogenated Al2O3 and SiNx. LPCVD SiNx provides less hydrogen for passivation compared to PECVD SiNx but can retain the hydrogen up to higher temperatures which is beneficial for firing. Although SiNx provides large amount of hydrogen, this doesn't necessarily translate to good passivation. AlOx:H contributes to retaining H at higher temperatures. Water molecules are also detected during H-effusion and may play a role in passivation of the oxide/wafer interface.

effusion study↗

dynamics of organic-mineral interactions at the metal oxide-solution interface as studied via binding energetics (Final report)

This project focused on addressing longstanding fundamental and experimental uncertainties on how dissolved organic substances (DOS) interact with metal oxide surface under environmentally relevant conditions. By leveraging a custom-built real-time, in-tandem flow adsorption microcalorimetry-UV-Vis/fluorescence spectroscopy platform, we characterized the binding energetics, kinetics and mechanistic pathways driving DOS-metal oxide interactions at temporal resolution on the order of 1-5 seconds. We studied a diverse suite of model organic compounds/substances – including monocarboxylates (e.g. acetate and benzoate), di-carboxylates (oxalate and succinate), amino acids, amino-based nanparticles and natural organic matter – interacting at the mineral-water interface of structurally- and/or chemically distinct metal oxides (including SiO2, boehmite, ferrihydrite, and γ-Al2O3). Our results indicated that DOS-metal oxide interactions are governed by multi-step reaction pathways, often switching between distinct, resolvable enthalpy- and entropy-driven non-electrostatic or electrostatic configurations. To quantify these interactions, we developed and implemented an analytical workflow that integrates peak deconvolution and Monte-Carlo based error propagation to determine site-specific thermodynamic and kinetic parameters for individual binding/debinding events. In addition to resolving apparent first-order rate constants of each event, we were able to quantify associated apparent equilibrium constants as well as free energy, enthalpy and entropy contribution to the activation and subsequent progression of the binding/debinding process across compounds, compound class and metal oxide surfaces. The kinetic-thermodynamic data produced in this study captured how the interplay between oxide surface reactivity and DOS molecular structure jointly drives binding-debinding dynamics. Notably, that at pH below PZC of the oxide surface, neutral species were heavily involved in monocarboxylate binding, while anionic species drove dicarboxylate binding. Also, that among amino acids 1) positional isomers show distinctive binding characteristics to each other while enantiomers show no significant differences in binding characteristics, 2) molecules that bind via outer-sphere complexation show a larger entropic shift between binding and debinding with no impact on oxide surface while 3) inner-sphere interactions increased anion exchange capacity of the oxide surface. The new insights and data from this work has great potential for improving predictive modeling of carbon dynamics and specifically organic-mineral interactions in environmental and industrial systems.

54 ENVIRONMENTAL SCIENCES↗

Advective gas flow in bentonite: Development and comparison of enhanced multi-phase numerical approaches

Understanding the impact of repository gas, generated from degradation of waste and its interaction with the host rock, is essential when assessing the performance and safety function of long-term disposal systems for radioactive waste. Numerical models based on conventional multi-phase flow theory have historically been applied to predict the outcome and impact of gas flow on different repository components. However, they remain unable to describe the full complexity of the physical processes observed in water-saturated experiments (e.g., creation of dilatant pathways) and thus, the development of novel representations for their description is required when assessing fully saturated clay-based systems. This was the primary focus of Task A within the international cooperative project DECOVALEX-2019 (D-2019) and refinement of these approaches is the primary focus of this study (Task B in the current phase of DECOVALEX-2023). This paper summarises development of enhanced numerical representations of key processes and compares the performance of each model against high-quality laboratory test data. Experimental data reveals that gas percolation in water-saturated compacted bentonite is characterised by four key features: (i) a quiescence phase, followed by (ii) the gas breakthrough, which leads to a (iii) peak value, which is then followed by (iv) a negative decay. Three models based on the multiphase flow theory have been developed. These models can provide good initial values and reasonable responses for gas breakthrough (although some of them still predict a too-smooth response). Peak gas pressure values are in general reasonably well captured, although maximum radial stress differences are observed at 48 mm from the base of the sample. Here, numerical peak values of 12.8 MPa are predicted, whereas experimental values are about 11 MPa. These models are also capable of providing a reasonable representation of the negative pressure decay following peak pressure. However, other key specific features (such as the timing of gas breakthrough) still require a better representation. The model simulations and their comparison with experimental data show that these models need to be further improved with respect to model parameter calibration, the numerical representation of spatial heterogeneities in material properties and flow localisation, and the upscaling of the related physical processes and parameters. To further understand gas flow localisation, a new conceptual model has been developed, which shows that discrete channels can possibly be induced through the instability of gas-bentonite interface during gas injection, thus providing a new perspective for modeling gas percolation in low-permeability deformable media.

58 GEOSCIENCES↗

Meso-scale modeling and damage analysis of carbon/epoxy woven fabric composite under in-plane tension and compression loadings

The mechanical properties and damage behaviors of carbon/epoxy woven fabric composite under in-plane tension and compression are studied at the meso-scale level through experiment and simulation. An efficient representative volume element (RVE) modeling method with consistent mesh, high yarn volume fraction and realistic geometry is proposed. The material constitutive laws with plasticity, tension-compression asymmetry and damage evolution are established for the three components - yarn, matrix and interface, respectively. Significantly different mechanical properties and damage evolutions are observed depending on loading conditions and initial geometry characteristics. It shows a non-linear stress-strain curve with clear transition region and intensive damage in tension, while a quasi-linear behavior up to facture is observed in compression with little damage prior to final fracture. Furthermore, compared to the constant Poisson's ratio with straining in compression, a dramatic increase in Poisson's ratio appears in tension. Simulation shows damage mechanisms including transverse damage, matrix damage and delamination, which all play critical roles in the property evolution. In particular, the rapid damage accumulation after elastic deformation destroys the strong bonds and causes the easy deformation of transverse yarns which results in the transition region and large Poisson's ratio in tension. All the mechanical behaviors and damage evolutions are well captured and explained with the current RVE model.

42 ENGINEERING↗

Acidities of MgO surface sites: implications for the formation mechanism of Mg(OH) 2

The hydroxylation of periclase (MgO) to brucite (Mg(OH) 2 ) is thought to be an important intermediate step when using MgO to capture CO 2 from the atmosphere. However, the mechanism of hydroxylation of MgO to form Mg(OH) 2 is poorly understood. In this work, we used atomic-scale density functional tight binding simulations coupled with the metadynamics rare event method to analyze the surface chemistry of MgO and the acid dissociation equilibrium constants (pK a ) of its surface sites. The method and parameters were validated by calculating the pK a for hydroxylation of the first shell water bound to aqueous Mg 2+ ion. The pK a value derived using a probabilistic method was 12.3, which is in fair agreement with the accepted value of 11.4, with the difference between them equal to a ∼5 kJ mol −1 error in the calculations. We then extended these pK a calculations to probe the hydroxylation reactions of the surface sites of the MgO(100)–water interface, arriving at pK a s of 5.4 to deprotonate terminal water molecules bound to the surface magnesium sites (η-OH 2 or 〉MgOH 2 ), and 13.9 to deprotonate hydroxylated bridging oxygen sites (μ 5 -oxo or 〉O). Hydroxide (OH − ) adsorption on the surface was also probed and found to be less thermodynamically favorable than deprotonation of the terminal water molecule. The plausibility of the computed pK a s was verified using an activity-based speciation model and compared to pH measurements of water equilibrated with MgO nanoparticles and single crystals. The model predicted a solution pH of 7.1 when surface sites buffered and the pH of 12.0 when MgO dissolution dominated. These are close to the experimental initial solution pHs of 7–7.5 and the long term pHs of ∼10.5. The similarity suggests that the calculated pK a values from the DFTB+/metadynamics simulations are plausible and that these methods can be a useful tool to probe reaction mechanisms involving covalent bonds.

Adapa, Sai Krishna Reddy [Oak Ridge National Labor↗