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At least 1,495 records · Page 83

Anode Boosted Electrolyzer

The aim of this project is to develop an anode catalyst and anolyte delivery system in renewably powered flow-electrolyzers that utilize waste carbon dissolved in non-potable process water as the anolyte to lower the overall cell potential at which hydrogen is generated (Anode-Boosting) while simultaneously purifying a non-potable water source. This project spans several of the desired aspects in the Renewable Hydrogen Transportation Fuel Pathways of interest: it combines renewably sourced energy with waste hydrocarbons, leading to enhanced water-splitting and eventual delivery and distribution of hydrogen for use in fuel cell powered transportation. Deployment of an Anode-Boosted Electrolysis process will provide a significant improvement in the effective energy efficiency for the generation of hydrogen due to a reduced cell potential and the desirable removal of organic impurities in waste water, offering a route to generating clean hydrogen and clean(er) water.

08 HYDROGEN↗

Accelerated Data Analytics for Power-System Time-Series (ADAPT) [Final Project Report]

Over the past decade, electric utilities have made significant progress in deploying networks of phasor measurement units (PMUs). The high-speed measurements provided by PMUs are valuable for offline analysis, but the sheer volume of data presents a challenge for utilities. The Accelerated Data Analytics for Power-System Time-Series (ADAPT) project was created to address this challenge by developing SciSync, an open-source software tool that enables utilities to rapidly read, process, analyze, and review grid measurements. SciSync was designed to provide the capabilities of Archive Walker, a research tool developed by PNNL, along with the reliability and performance of commercial-grade software.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A First Principles Approach to Spectral Phonon Transport in Heterostructures

Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale

36 MATERIALS SCIENCE↗

Persona of Transition Metal Ions in Solids: A Statistical Learning on Local Structures of Transition Metal Oxides

Abstract The local structure of a transition metal (TM) ion is a function of cation elements and valence states. More than that, in this work, by employing a trove of first‐principles data of TM oxides, the local structures of TM cations are statistically analyzed to extract detailed information about cation site preference, bond length, site structural distortion, and cation magnetization. It is found that cation radius alone poorly describes the local structure of a transition metal oxide, while the statistics of coordination number as well as the TMO bond length distribution, especially that of the 3d TMs, can provide comprehensive knowledge for understanding the behavior of TM elements. Based on these statistics, the interplay of site distortion due to the Jahn–Teller effect, cation site similarity, and a new set of ionic radii are all obtained to chart the “persona” of transition metal ions in solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural Flexibility of Metal Chelate Complexes and Its Relation to Supramolecular Chemistry

In this study, crystal structures of metal chelate and related complexes in the Cambridge Structural Database have been analyzed, with respect to their use as components in supramolecular metal-organic compounds. In β-diketonate complexes, the distribution of angles between ligands is relatively broad; other ligands, such as 2,2'-bipyridine, yield significantly narrower distributions. According to the principle of structure correlation, these distributions reflect the ease of distorting the various families of complexes. A comparison through density functional theory calculations also indicates that angular distortions require significantly less energy for M(β-diketonate) 3 than for M(2,2'-bipyridine) 3 . The differences are likely to affect the construction of supramolecular systems from different combinations of metals and ligands, including the likelihood that the desired structures will be obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Zintl Concept Applied to Intergrowth Structures: Electron‐Hole Matching, Stacking Preferences, and Chemical Pressures in Pd 5 InAs

Abstract Enumerating the potential stacking sequences of layers is a fundamental way to account for the structure diversity of solid state compounds. In many cases, these stacking variations represent polymorphs with only small energetic differences. Here, we examine a compound for which the preferred stacking pattern instead reveals key aspects about its chemical bonding: Pd 5 InAs. Its structure is based on the intergrowth of slabs of the AuCu 3 and PtHg 2 (or alternatively, fluorite) structure types. Two basic stacking arrangements are available to this compound, represented by the Pd 5 TlAs and HoCoGa 5 structure types. DFT total energy calculations reveal that the former outcompetes the latter by a staggering 0.65 eV/formula unit. Through a combination of DFT‐reversed approximation Molecular Orbital (DFT‐raMO) and DFT‐Chemical Pressure (DFT‐CP) analysis we trace this preference to two factors. First, with DFT‐raMO analysis, we derive a Zintl‐like bonding scheme of Pd 5 InAs. This scheme, along with the inspection of selected crystal orbitals, is then connected to preferred stacking through the coordination environments of the Pd atoms at the interface between the Pd−In and Pd−As layers. In the hypothetical HoCoGa 5 ‐type and observed Pd 5 InAs‐type structures, different Pd coordination environments arise at the interfaces. The hypothetical structure features square planar PdIn 2 As 2 units, in each of which the same 4d‐orbital serves in the Pd sublattice's role as both Lewis acid (for interactions with the As) and Lewis base (for interactions with the In). In the observed structure, tetrahedral PdIn 2 As 2 units occur instead, so that these contradictory roles are distributed to separate 4d‐orbitals, leading to more effective bonding. DFT‐CP analysis illustrates that this driving force for the Pd 5 TlAs‐type arrangement is supplemented by a favorable alignment of the packing tensions in the parent structures. Altogether, the resulting picture demonstrates how the reaction of simple intermetallic structures to form intergrowths can be guided by recognizable chemical interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers

Dynamic graph embedding has emerged as a very effective technique for addressing diverse temporal graph analytic tasks (i.e., link prediction, node classification, recommender systems, anomaly detection, and graph generation) in various applications. Such temporal graphs exhibit heterogeneous transient dynamics, varying time intervals, and highly evolving node features throughout their evolution. Hence, incorporating long-range dependencies from the historical graph context plays a crucial role in accurately learning their temporal dynamics. In this paper, we develop a graph embedding model with uncertainty quantification, TransformerG2G, by exploiting the advanced transformer encoder to first learn intermediate node representations from its current state (t) and previous context (over timestamps [t–1,t–l], l is the length of context). Moreover, we employ two projection layers to generate lower-dimensional multivariate Gaussian distributions as each node's latent embedding at timestamp t. We consider diverse benchmarks with varying levels of "novelty" as measured by the TEA (Temporal Edge Appearance) plots. Here, our experiments demonstrate that the proposed TransformerG2G model outperforms conventional multi-step methods and our prior work (DynG2G) in terms of both link prediction accuracy and computational efficiency, especially for high degree of novelty. Furthermore, the learned time-dependent attention weights across multiple graph snapshots reveal the development of an automatic adaptive time stepping enabled by the transformer. Importantly, by examining the attention weights, we can uncover temporal dependencies, identify influential elements, and gain insights into the complex interactions within the graph structure. For example, we identified a strong correlation between attention weights and node degree at the various stages of the graph topology evolution.

97 MATHEMATICS AND COMPUTING↗

Dilute Pd/Au Alloy Nanoparticles Embedded in Colloid-Templated Porous SiO 2 : Stable Au-Based Oxidation Catalysts

Dilute alloy materials hold great promise for enhancing selectivity in catalytic reactions. A major challenge with such catalytic materials is developing supported alloy nanoparticles (NPs) with a catalytically optimal composition that are stable with respect to sintering. Here, we demonstrate that NP Pd/Au catalysts with minor concentrations of Pd prepared by a colloid-templating approach are active for oxygen dissociation and catalytic oxidation, as exemplified by CO oxidation. Using electron microscopic imaging, infrared spectroscopy, and X-ray photoelectron spectroscopy, we demonstrate that Pd is stabilized within the Au nanoparticle in its metallic state with minor amounts of Pd at the surface. The Pd–Au nanoparticles are embedded in the colloidally templated silica and form a thermally stable catalyst at high temperature. Surface analysis by diffuse reflectance infrared spectroscopy indicates that the Pd atomic distribution at the surface varies with the bulk concentration, forming isolated Pd atoms at 2% Pd and a mixture of Pd monomers and small Pd clusters at 9% Pd. X-ray absorption fine structure analysis indicates that Pd is well distributed in the bulk of the nanoparticle. In conclusion, in-depth understanding of this new class of catalytic materials opens the way to a wide array of possibilities for crucial enhancement of activity and selectivity in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pb Sorption at the Barite (001)–Water Interface

Sorption of ions at the mineral-water interface is an important factor that determines the fate of toxic metals in the environment. Here, we use barite as a model substrate to understand the interaction of toxic-metal lead (Pb) with ionic crystals. The coverage and location of Pb sorbed to the (001) surface was measured as a function of aqueous Pb concentration ([Pb] aq ) using in situ specular resonant anomalous X-ray reflectivity (RAXR) to determine the sorption capacity and process. In this work, the results show that Pb sorption occurs via incorporation (primarily within the top barite layer similar to 3 angstrom in depth) and adsorption (mostly as an inner-sphere complex at similar to 2 angstrom in height) simultaneously. Both the incorporated and adsorbed Pb coverages increase with increasing [Pb] aq up to [Pb] aq similar to 200 mu M, above which the adsorbed fraction increases more rapidly than the incorporated fraction. This enhanced adsorption has a height distribution that is further extended (>= 15 angstrom from the surface) than that observed in lower [Pb] aq . This change in distribution is interpreted as arising from additional sorption of outer-sphere species or Pb-bearing phases precipitated on the surface. Desorption experiments in Pb-free solutions show that the incorporated fraction is more resistant to removal than the adsorbed fraction, consistent with the speciation-dependent stabilities premised in the classical sorption models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing the Influence of Salts on the Hydration Structure of Ionic SDS Micelles by Contrast-Variation Small-Angle Neutron Scattering

The influence of lithium chloride (LiCl) on the hydration structure of anionic micelles of sodium dodecyl sulfate (SDS) in water was studied using the contrast-variation small-angle neutron scattering (SANS) technique. In the past, extensive computational studies have shown that the distribution of invasive water plays a critical role in the self-organization of SDS molecules and the stability of the assemblies. However, in past scattering studies the degree of the hydration level was not examined explicitly. Here, a series of contrast-variation SANS data was analyzed to extract the intramicellar radial distributions of invasive water and SDS molecules from the evolving spectral lineshapes caused by the varying isotopic ratios of water. By addressing the intramicellar inhomogeneous distributions of water and SDS molecules, a detailed description of how the counterion association influences the micellization behavior of SDS molecules is provided. The extension of our method can be used to provide an in-depth insight into the micellization phenomenon, which is commonly found in many soft matter systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Efficient Reactive Force Field without Explicit Coordination Dependence for Studying Caustic Aluminum Chemistry

Reactive force fields (RFFs) are an expedient approach to sample chemical reaction paths in complex systems, relative to density functional theory. However, there is continued need to improve efficiencies, specifically in systems that have slow transverse degrees of freedom, as in highly viscous and superconcentrated solutions. Here, we present an RFF that is differentiated from current models (e.g., ReaxFF) by omitting explicit dependence on the atom coordination and employing a small parameter set based on Lennard-Jones, Gaussian, and Stillinger–Weber potentials. In this study, the model was parametrized from AIMD simulation data and is used to model aluminate reactivity in sodium hydroxide solutions with extensive validation against experimental radial distribution functions, computed free energy profiles for oligomerization, and formation energies. In conclusion, the model enables simulation of early stage Al(OH) 3 nucleation which has significant relevance to industrial processing of aluminum and has a computational cost that is reduced by 1 order of magnitude relative to ReaxFF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vapor-Deposited n = 2 Ruddlesden–Popper Interface Layers Aid Charge Carrier Extraction in Perovskite Solar Cells

Interfacial passivation with bulky organic cations such as phenetylammonium iodide has enabled high performance for metal halide perovskite optoelectronic devices. However, the homogeneity of these interfaces and their formation dynamics are poorly understood. Here we study how Ruddlesden-Popper 2D phases form at a 3D perovskite interface when the 2D precursors are introduced via solution or via vapor. When using vapor deposition, we observe uniform coverage of the capping layer and the formation of a predominantly n = 2 Ruddlesden-Popper phase. In contrast, when using solution deposition, we observe the presence of a mixture of n = 2 and n = 1 in the film and the formation of aggregates of the organic cations. As a result of the better phase purity and uniformity, vapor deposition enables higher median solar cell performance with narrower distribution compared to solution-treated films. This study provides fundamental information that the perovskite community can use to better design capping layers to achieve higher charge extraction efficiencies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simultaneous Observation of Carrier-Specific Redistribution and Coherent Lattice Dynamics in 2H-MoTe 2 with Femtosecond Core-Level Spectroscopy

In this study, we employ few-femtosecond extreme ultraviolet (XUV) transient absorption spectroscopy to reveal simultaneously the intra- and interband carrier relaxation and the light-induced structural dynamics in nanoscale thin films of layered 2H-MoTe 2 semiconductor. By interrogating the valence electronic structure via localized Te 4 d (39-46 eV) and Mo 4 p (35-38 eV) core levels, the relaxation of the photoexcited hole distribution is directly observed in real time. We obtain hole thermalization and cooling times of 15 ± 5 fs and 380 ± 90 fs, respectively, and an electron-hole recombination time of 1.5 ± 0.1 ps. Furthermore, excitations of coherent out-of-plane A 1g (5.1 THz) and in-plane E 1g (3.7 THz) lattice vibrations are visualized through oscillations in the XUV absorption spectra. By comparison to Bethe-Salpeter equation simulations, the spectral changes are mapped to real-space excited-state displacements of the lattice along the dominant A 1g coordinate. By directly and simultaneously probing the excited carrier distribution dynamics and accompanying femtosecond lattice displacement in 2H-MoTe 2 within a single experiment, our work provides a benchmark for understanding the interplay between electronic and structural dynamics in photoexcited nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stochastic density functional theory combined with Langevin dynamics for warm dense matter

Here, this study overviews and extends a recently developed stochastic finite-temperature Kohn-Sham density functional theory to study warm dense matter using Langevin dynamics, specifically under periodic boundary conditions. The method's algorithmic complexity exhibits nearly linear scaling with system size and is inversely proportional to the temperature. Additionally, a linear-scaling stochastic approach is introduced to assess the Kubo-Greenwood conductivity, demonstrating exceptional stability for dc conductivity. Utilizing the developed tools, we investigate the equation of state, radial distribution, and electronic conductivity of hydrogen at a temperature of 30 000 K. As for the radial distribution functions, we reveal a transition of hydrogen from gaslike to liquidlike behavior as its density exceeds 4 g/cm 3 . As for the electronic conductivity as a function of the density, we identified a remarkable isosbestic point at frequencies around 7 eV, which may be an additional signature of a gas-liquid transition in hydrogen at 30 000 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES)

This report presents the physical and chemical characterization of breaker and sorter reject materials sourced from the Prairie State Generation facility, as part of the Illinois Rare Earth Novel Extraction and Supply (IRENES) project. Key analyses include particle size distribution, density, angle of repose, proximate and ultimate composition, mineralogy, and elemental content. Breaker reject material was found to be coarser and higher in ash content (~80%) with lower calorific value, while sorter reject showed finer distribution, lower ash (~68%), and higher carbon and energy content. XRD and XRF analyses confirmed the presence of REE-bearing minerals and relevant oxides, supporting process design and beneficiation strategy development for critical mineral recovery.

01 COAL, LIGNITE, AND PEAT↗

Using the Diffusion Equation to Predict CST Resin Breakthroughs - 19051

The crystalline silicotitanate, CST, resin manufactured by UOP Honeywell is well-suited for single-use decontamination of caustic liquid wastes at Hanford and Savannah River Sites. There are many measurements of column loading and breakthrough for CST resin decontamination of Cs-137 in various Hanford and SRS waste simulants. Such measurements provide a very good basis for estimating CST resin demand and these more refined predictions make the CST column loading as efficient as possible given the very expensive CST resin. Although there are a variety of tools for predicting chromatographic resin column performance, [1-4], there is a particularly useful method that is suitable as a simple spreadsheet model [4]. This spreadsheet model is an analytical error function for the mass transfer zone (mtz) diffusion width in resin columns and is well-suited for resin breakthrough and column loading. This paper describes just such an error function spreadsheet model and how well the error function agrees with more traditional models and fits the observed small scale breakthrough curves for CST that can then better predict large scale column loading efficiency. The very high sorption of Cs onto CST tends to be slower than that of other lower sorption resins and as a result of the slow CST kinetics, there is also a marked asymmetry in many CST breakthrough curves. The CST breakthrough asymmetry is largely due to the distribution of CST particle sizes because smaller particles sorb much faster than larger particles. It is then the smaller particles that determine the leading mtz at a decontamination factor of 1,000 breakthrough and therefore the decontamination efficiency for a given loading. The larger CST particles correspondingly determine the tailing mtz width and therefore the overall loading efficiency and it is important to model both leading and tailing mtz widths to best optimize CST for a particular Cs-137 decontamination application. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗