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At least 109 records · Page 6

An accurate and efficient Ehrenfest dynamics approach for calculating linear and nonlinear electronic spectra

Linear and nonlinear electronic spectra provide an important tool to probe the absorption and transfer of electronic energy. Here, we introduce a pure state Ehrenfest approach to obtain accurate linear and nonlinear spectra that is applicable to systems with large numbers of excited states and complex chemical environments. We achieve this by representing the initial conditions as sums of pure states and unfolding multi-time correlation functions into the Schrödinger picture. By doing this, we show that one can obtain significant improvements in accuracy over the previously used projected Ehrenfest approach and that these benefits are particularly pronounced in cases where the initial condition is a coherence between excited states. While such initial conditions do not arise when calculating linear electronic spectra, they play a vital role in capturing multidimensional spectroscopies. We demonstrate the performance of our method by showing that it is able to quantitatively capture the exact linear, 2D electronic spectroscopy, and pump–probe spectra for a Frenkel exciton model in slow bath regimes and is even able to reproduce the main spectral features in fast bath regimes.

Chemistry↗

Towards the development of resonantly enhanced laser-based diagnostics for molten salt reactor safeguards

The adoption of Generation IV molten salt reactors (MSRs) depends on the ability to implement compatible monitoring instrumentation to ensure adherence to nuclear safeguards. This task is nontrivial due to the high temperature, reactive, and chemically complex fuel and coolant components contained within these systems. Optical spectroscopy techniques such as laser-induced fluorescence (LIF) and laser-induced breakdown spectroscopy (LIBS) are candidates for monitoring instrumentation. They offer many advantages for continuous monitoring, including the ability to operate at a standoff and compatibility with liquid-phase analytes. We discuss the use of LIF for the detection of Nd, a common fission fragment, within a liquid matrix. Results show that for NdCl3 dissolved in water, the Nd I 492.45 nm resonant transition is detectable without the need to induce a plasma and that the fluorescence emission can be separated in the time domain from the laser scatter signal. Additionally, we present a setup and preliminary results for measurements of solid Nd and U using resonant LIBS. The results demonstrate element-selective measurement capabilities and provide the foundational data necessary to continue the development of laser-based MSR diagnostics. This work also helps address gaps in the literature regarding energy level assignments of Nd.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

Plant-based engineering for production of high-valued natural products

Plants are a unique source of complex specialized metabolites, many of which play significant roles in human society. In many cases, however, the availability of these metabolites from naturally occurring sources fails to meet current demands. Thus, there is much interest in expanding the production capacity of target plant molecules. Traditionally, plant breeding, chemical synthesis, and microbial fermentation are considered the primary routes towards large scale production of natural products. Here, in this paper, we explore the advances, challenges, and future of plant engineering as a complementary path. Although plants are an integral part of our food and agricultural systems and sustain an extensive array of chemical constituents, their complex genetics and physiology have prevented the optimal exploitation of plants as a production chassis. We highlight emerging engineering tools and scientific advances developed in recent years that have improved the prospects of using plants as a sustainable and scalable production platform. We also discuss technological limitations and overall economic outlook of plant-based production of natural products.

59 BASIC BIOLOGICAL SCIENCES↗

Recent advances in understanding the role of solvated electrons at the plasma-liquid interface of solution-based gas discharges

The solvated electron is one of the strongest known reducing species. Solution-based glow discharges, in which a gaseous discharge is ignited between a metal electrode and a liquid surface, are an emerging spectrochemical source in analytical atomic emission and mass spectrometry. In other disciplines, the similar setup is called plasma electrolysis and can be used for materials and chemical synthesis. Regardless of its name and application areas, electrons are injected into a solution and the underlying physics and chemistry in these systems is complex. Furthermore, quantitative understanding is necessary in order to maximize performance for chemical and materials applications. In this paper, we summarize the state-of-the-art in plasma-liquid interactions involving solvated electrons, with a particular emphasis on the work by our group, and highlight potential areas of future study to both fill in knowledge gaps and drive applications forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing Hot and Long-Lived Metastable Spin States in the Photoinduced Switching of Solvated Metallogrid Complexes with Femtosecond Optical and X-ray Spectroscopies

An atomistic understanding of the photoinduced spin-state switching (PSS) within polynuclear systems of d 4 –d 7 transition metal ion complexes is required for their rational integration into light-driven reactions of chemical and biological interest. However, in contrast to mononuclear systems, the multidimensional dynamics of the PSS in solvated molecular arrays have not yet been elucidated due to the expected complications associated with the connectivity between the metal centers and the strong interactions with the surroundings. Herein, the PSS in a solvated triiron(II) metallogrid complex is characterized using transient optical absorption and X-ray emission spectroscopies on the femtosecond time scale. The complementary measurements reveal the photoinduced creation of energy-rich (hot) and long-lived quintet states, whose dynamics differ critically from their mononuclear congeners. We report this finding opens major prospects for developing novel schemes in solution-phase spin chemistry that are driven by the dynamic PSS process in compact oligometallic arrays.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

Solvent Induced Proton Polarization within the Nuclear–Electronic Orbital Framework

To explicitly account for nuclear quantum effects and solvent environments in simulations of chemical processes, the nuclear-electronic orbital approach is coupled with a polarizable continuum model (PCM). This NEO–PCM approach is used to explore the influence of solvation on nuclear polarization through applications to a water dimer and a set of protonated water tetramers. Nuclear polarization in these species is analyzed in terms of changes in proton density and oxygen–hydrogen bond length. Solvation is shown to enhance nuclear polarization with increasing dielectric constant. For the water dimer, the internal, hydrogen-bonded proton is shown to polarize more than the external, free proton. Moreover, proton quantization leads to greater solvent polarization through their mutual polarization. Furthermore, these calculations highlight the complex interplay among electronic, nuclear, and solvent polarization in chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing metastability for grain size control in multiprincipal element alloys during additive manufacturing

Abstract Controlling microstructure in fusion-based metal additive manufacturing (AM) remains a significant challenge due to the many parameters that directly impact solidification condition. Multiprincipal element alloys (MPEAs), also known as high entropy alloys, offer a vast compositional space to design for microstructural engineering due to their chemical complexity and exceptional properties. Here, we use the FeMnCoCr system as a model platform for exploring alloy design in MPEAs for AM. By exploiting the decreasing stability of the face-centered cubic phase with increasing Mn content, we achieve notable grain refinement and breakdown of epitaxial columnar grain growth. We employ a multifaceted approach encompassing thermodynamic modeling, operando synchrotron X-ray diffraction, multiscale microstructural characterization, and mechanical testing to gain insight into the solidification physics and its ramifications on the resulting microstructure of FeMnCoCr MPEAs. This work aims toward tailoring desirable grain sizes and morphology through targeted manipulation of phase stability, thereby advancing microstructure control in AM applications.

Wakai, Akane↗

Application of Ionic Liquids for the Recycling and Recovery of Technologically Critical and Valuable Metals

Population growth has led to an increased demand for raw minerals and energy resources; however, their supply cannot easily be provided in the same proportions. Modern technologies contain materials that are becoming more finely intermixed because of the broadening palette of elements used, and this outcome creates certain limitations for recycling. The recovery and separation of individual elements, critical materials and valuable metals from complex systems requires complex energy-consuming solutions with many hazardous chemicals used. Significant pressure is brought to bear on the improvement of separation and recycling approaches by the need to balance sustainability, efficiency, and environmental impacts. Due to the increase in environmental consciousness in chemical research and industry, the challenge for a sustainable environment calls for clean procedures that avoid the use of harmful organic solvents. Ionic liquids, also known as molten salts and future solvents, are endowed with unique features that have already had a promising impact on cutting-edge science and technologies. This review aims to address the current challenges associated with the energy-efficient design, recovery, recycling, and separation of valuable metals employing ionic liquids.

36 MATERIALS SCIENCE↗

Generalized representative structures for atomistic systems

A new method is presented to generate atomic structures that reproduce the essential characteristics of arbitrary material systems, phases, or ensembles. Previous methods allow one to reproduce the essential characteristics (e.g. the chemical disorder) of a large random alloy within a small crystal structure. The ability to generate small representations of random alloys, along with the restriction to crystal systems, results from using the fixed-lattice cluster correlations to describe structural characteristics. A more general description of the structural characteristics of atomic systems is obtained using complete sets of atomic environment descriptors. These are used within for generating representative atomic structures without restriction to fixed lattices. A general data-driven approach is provided here utilizing the atomic cluster expansion (ACE) basis. The N-body ACE descriptors are a complete set of atomic environment descriptors that span both chemical and spatial degrees of freedom and are used within for describing atomic structures. The generalized representative structure (GRS) method presented within generates small atomic structures that reproduce ACE descriptor distributions corresponding to arbitrary structural and chemical complexity. It is shown that systematically improvable representations of crystalline systems on fixed parent lattices, amorphous materials, liquids, and ensembles of atomic structures may be produced efficiently through optimization algorithms. With the GRS method, we highlight reduced representations of atomistic machine-learning training datasets that contain similar amounts of information and small 40–72 atom representations of liquid phases. The ability to use GRS methodology as a driver for informed novel structure generation is also demonstrated. The advantages over other data-driven methods and state-of-the-art methods restricted to high-symmetry systems are highlighted.

atomic cluster expansion↗

Graph theory approach to determine configurations of multidentate and high coverage adsorbates for heterogeneous catalysis

Abstract Heterogeneous catalysts constitute a crucial component of many industrial processes, and to gain an understanding of the atomic-scale features of such catalysts, ab initio density functional theory is widely employed. Recently, growing computational power has permitted the extension of such studies to complex reaction networks involving either high adsorbate coverages or multidentate adsorbates, which bind to the surface through multiple atoms. Describing all possible adsorbate configurations for such systems, however, is often not possible based on chemical intuition alone. To systematically treat such complexities, we present a generalized Python-based graph theory approach to convert atomic scale models into undirected graph representations. These representations, when combined with workflows such as evolutionary algorithms, can systematically generate high coverage adsorbate models and classify unique minimum energy multidentate adsorbate configurations for surfaces of low symmetry, including multi-elemental alloy surfaces, steps, and kinks. Two case studies are presented which demonstrate these capabilities; first, an analysis of a coverage-dependent phase diagram of absorbate NO on the Pt 3 Sn(111) terrace surface, and second, an investigation of adsorption energies, together with identifying unique minimum energy configurations, for the reaction intermediate propyne (CHCCH 3 *) adsorbed on a PdIn(021) step surface. The evolutionary algorithm approach reproduces high coverage configurations of NO on Pt 3 Sn(111) using only 15% of the number of simulations required for a brute force approach. Furthermore, the screening of potentially hundreds of multidentate adsorbates is shown to be possible without human intervention. The strategy presented is quite general and can be applied to a spectrum of complex atomic systems.

36 MATERIALS SCIENCE↗

A mathematical framework for thermodynamic computing with applications to chemical reaction networks

The widespread adoption of energy-intensive computing applications has led to a growing need for energy-efficient computing approaches. Thermodynamic computing offers a promising approach for low-energy computation by leveraging the intrinsic computational capabilities of physical, chemical, or biological systems. However, the mathematical foundations of thermodynamic computing require further development to fully realize the potential energy efficiencies, as well as to assess factors like noise and operational speed. In this paper, we establish a mathematical framework for utilizing thermodynamic processes to perform fundamental operations, including addition, subtraction, multiplication, and division. We highlight the use of chemical reactions as potential computational units and explore synthetic chemical and biochemical systems as practical implementations. Additionally, we demonstrate how these principles can be applied to solving complex mathematical problems, such as ordinary differential equations (ODEs) and suggest the necessary components to implement the thermodynamic computing framework using chemical reactions based in a microfluidic device. This work enhances our understanding of thermodynamic processes for natural computing as a basis for scalable, energy-efficient computation in paradigm disruptive next-generation systems.

Cannon, William R. [Pacific Northwest National Lab↗

Understanding the Applicability of Gas/Particle Partitioning Theory to SOA using Novel Chemically-Speciated Partitioning Measurements (Final Report)

The main objective of this research grant project was to investigate the physical-chemical processes and properties of particles and partitioning gases that influence gas/particle (G/P) partitioning and timescales for equilibration, to directly determine the conditions under which equilibrium G/P partitioning theory can be applied to secondary organic aerosol (SOA). SOA constitutes a major component of submicron particles in the atmosphere, which have important implications for air quality, human and ecosystem health, radiation balance, and climate; however SOA formation, evolution and losses are not well understood. Use of novel on-line measurements of chemically-speciated partitioning measurements of both gas-phase and particle-phase components was a central component to advancing these scientific goals. The key approach was to conduct environmental chamber studies with systems of increasing complexity to determine G/P partitioning rates and equilibrium states for chemically-speciated SOA components. The project builds on our previous work on gas-wall partitioning that must be understood in order to study G/P partitioning in chambers, and to help extrapolate the results to be atmospherically relevant. The goal was to employ measurements and modeling to systematically determine when G/P partitioning theory accurately describes the distribution of oxidized organic compounds in the gas and aerosol phases, and when and why it does not (e.g., aerosol phase-state kinetic limitations, non-ideal mixing, phase separation, oligomer formation,), for chemical and physical conditions typically found throughout the continental boundary layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dissipative Assembly of Macrocycles Comprising Multiple Transient Bonds

Abstract Dissipative assembly has great potential for the creation of new adaptive chemical systems. However, while molecular assembly at equilibrium is routinely used to prepare complex architectures from polyfunctional monomers, species formed out of equilibrium have, to this point, been structurally very simple. In most examples the fuel simply effects the formation of a single short‐lived covalent bond. Herein, we show that chemical fuels can assemble bifunctional components into macrocycles containing multiple transient bonds. Specifically, dicarboxylic acids give aqueous dianhydride macrocycles on treatment with a carbodiimide. The macrocycles are assembled efficiently as a consequence of both fuel‐dependent and fuel‐independent mechanisms; they undergo slower decomposition, building up as the fuel recycles the components, and are a favored product of the dynamic exchange of the anhydride bonds. These results create new possibilities for generating structurally sophisticated out‐of‐equilibrium species.

Hossain, Mohammad Mosharraf↗

Could Microplasma Ionization and Ultrahigh Mass Resolution Alleviate Chemical Separations for Elemental and Isotopic Analysis?

At the extremes, all analytical spectrometric measurements are limited by the resolution of the spectrometer system. Spectral overlaps, isobars in the case of mass spectrometry, can lead to the implementation of complex and time-consuming chemical separations to alleviate those interferences. In the area of elemental/isotopic mass spectrometry, use of sector-field instruments can provide a mass resolution of ~10,000, but still necessitate chemical separations. Described here is the coupling of the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma to ultra-high resolution Orbitrap mass analyzer systems to yield mass resolution values ranging from 70k to 1M. Resolution of this order, with commensurate improvements in precision and accuracy, holds the promise to affect elemental/isotopic determinations without the need for chemical separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Targeted Adjusting Molecular Arrangement in Organic Solar Cells via a Universal Solid Additive

The incorporation of solid additive has been considered as an effective strategy for developing organic photovoltaics with multi-components, which is independent of dynamics, playing unique roles in morphology adjustment. However, their complex working mechanisms involving specific chemical structures are selective to material systems, hence limiting their university and flexibility in application. Herein, an inert small-molecular compound naphtho[1,2-c:5,6-c′]bis[1,2,5]thiadiazole (NT) is introduced into the bulk-heterojunction blend as the solid additive, which can function with various material systems and solvents, depending on its simple π-conjugated structure and S⋯N interaction for adjusting molecular alignment. It is interesting to note that the introduced NT can not only improve device performance, but also simplify complicated pre- or post-processing methods, reduce impact from batch-to-batch differences, construct sufficient energy transfer channel as well as improve device stability. The resulting devices based on PTzBI-dF:Y6-BO system show an impressive power conversion efficiency of 17.4% with obviously enhanced T 80 lifetime of >1200 h. These findings provide useful guidelines for exploring potential universal solid additives benefitting toward commercial application.

36 MATERIALS SCIENCE↗

Unleashing the capacity of Rhodococcus for converting lignin into lipids

Bioconversion of bioresources/wastes (e.g., lignin, chemical pulping byproducts) represents a promising approach for developing a bioeconomy to help address growing energy and materials demands. Rhodococcus, a promising microbial strain, utilizes numerous carbon sources to produce lipids, which are precursors for synthesizing biodiesel and aviation fuels. However, compared to chemical conversion, bioconversion involves living cells, which is a more complex system that needs further understanding and upgrading. Various wastes amenable to bioconversion are reviewed herein to highlight the potential of Rhodococci for producing lipid-derived bioproducts. In light of the abundant availability of these substrates, Rhodococcus’ metabolic pathways converting them to lipids are analyzed from a “beginning-to-end” view. Based on an in-depth understanding of microbial metabolic routes, genetic modifications of Rhodococcus by employing emerging tools (e.g., multiplex genome editing, biosensors, and genome-scale metabolic models) are presented for promoting the bioconversion. Co-solvent enhanced lignocellulose fractionation (CELF) strategy facilitates the generation of a lignin-derived aromatic stream suitable for the Rhodococcus’ utilization. Novel alkali sterilization (AS) and elimination of thermal sterilization (ETS) approaches can significantly enhance the bioaccessibility of lignin and its derived aromatics in aqueous fermentation media, which promotes lipid titer significantly. In order to achieve value-added utilization of lignin, biodiesel and aviation fuel synthesis from lignin and lipids are further discussed. In conclusion, the possible directions for unleashing the capacity of Rhodococcus through synergistically modifying microbial strains, substrates, and fermentation processes are proposed toward a sustainable biological lignin valorization.

09 BIOMASS FUELS↗