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At least 379 records · Page 21

A Range and Performance Optimized Version of the Computer-Aided Speckle Interferometry Algorithm for Real-Time Displacement-Strain Field Monitoring

Abstract This work presents an optimized implementation of the Computer-Aided Speckle Interferometry algorithm which enables full-field determination of displacements and strains on commodity Graphics Processing Units at high resolution and frame rates. By combining careful control of the average speckle size in a laser speckle pattern with a simple sampling rate conversion scheme, a compact representation of the optical speckle is achieved. This allows for optimal use of Graphics Processing Unit architecture with robust range extension. The optimal mapping of the Computer-Aided Speckle Interferometry algorithm to Graphics Processing Unit architecture is shown in detail, and a straightforward method for disambiguating large displacements is illustrated. Lastly, this paper demonstrates a two-step subimage-tapering modification to the original algorithm that enables robust range enhancement while maintaining resolution. Results from numerical simulations on synthetic speckle patterns are shown, and runtime performance metrics are provided, with performance ranging up to 60 frames per second in some cases. The method is suitable for interactive experimental mechanics research, process and testing or any application where real-time high-resolution displacement-strain monitoring is needed. A .NET Framework class library enabling the incorporation of the algorithm into 3rd -party applications is available for download.

42 ENGINEERING↗

Multivalent interactions between CsoS2 and Rubisco mediate α-carboxysome formation

Carboxysomes are bacterial microcompartments that function as the centerpiece of the bacterial CO 2 -concentrating mechanism by facilitating high CO 2 concentrations near the carboxylase Rubisco. The carboxysome self-assembles from thousands of individual proteins into icosahedral-like particles with a dense enzyme cargo encapsulated within a proteinaceous shell. In the case of the α-carboxysome, there is little molecular insight into protein–protein interactions that drive the assembly process. In this work, studies on the α-carboxysome from Halothiobacillus neapolitanus demonstrate that Rubisco interacts with the N terminus of CsoS2, a multivalent, intrinsically disordered protein. X-ray structural analysis of the CsoS2 interaction motif bound to Rubisco reveals a series of conserved electrostatic interactions that are only made with properly assembled hexadecameric Rubisco. Although biophysical measurements indicate that this single interaction is weak, its implicit multivalency induces high-affinity binding through avidity. Taken together, our results indicate that CsoS2 acts as an interaction hub to condense Rubisco and enable efficient α-carboxysome formation.

59 BASIC BIOLOGICAL SCIENCES↗

Minimizing Cr-Evaporation from Balance Of Plant Components By Utilizing Cost-Effective Alumina-Forming Austenitic Steels

A solid oxide fuel cell (SOFC) is a clean and efficient energy conversion device. The development of intermediate-temperature SOFCs has made it preferable to use metallic interconnects (MICs) to greatly reduce the cost and significantly increase the efficiency compared to ceramic interconnect materials. However, gaseous chromium species will evaporate from the chromium-containing layer formed on the surface of commonly used MICs and balance of plant (BoP) components. Volatile chromium species have been shown to form solid deposits which poison the cathodes of SOFCs, causing drastic cell performance degradation and thereby limiting commercialization. In order to alleviate the Cr poisoning and achieve long-term high performance of SOFC stacks, various Al 2 O 3 -forming austenitic (AFA) stainless steels applied at different temperatures are evaluated in this project. Based on our Phase I results (500 h operation), it is shown that on the AFAs, an alumina-based protective layer forms under high temperature that is invulnerable to water vapor effects and suppresses the diffusion of chromium and manganese which can prevent the generation of spinels on the alloy surface. Therefore, 310S, OC4 and OC5 at 800 °C and 625, OC11 and OC11LZ at 900 °C are selected to be tested in the Phase II long-term operation. From the results, we find that besides the lower Cr evaporation rates and better oxidation resistance of AFAs than benchmark alloys after short-term (500 h) operation, AFAs also possess the sturdy and compact alumina layer after a long-term operation (5000 h). A protective oxide layer is of great importance for the long-term high-temperature operation of structural materials. The high-temperature oxidation behavior of AFAs and commercial 310S and 625 alloys in Air + 10% H 2 O at 800 °C and 900 °C is systematically investigated. Severe breakaway oxidation and minor spallation are observed for the 310S and 625 after the long-term operation, while the AFAs show high oxidation resistance. It is found that the formation of a continuous alumina layer could greatly prevent the volatilization of chromium vapors. In addition, the corresponding evolving models are discussed. Chromium evaporation from BoP components in high-temperature environment could severely deteriorate the electrochemical performance of SOFC. Several methods were applied to evaluate the Cr evaporation rates of BoP after 500 h exposure at 800 °C to 900 °C in air with 10% H 2 O. An optimal method was designed to exclude the effect of silicon (Si) deposits from quartz tube and sodium (Na) deposits from the sodium carbonate on the oxidation process and the chemical interaction between Cr gaseous species and alumina tube which could provide further quantitative correlation of the evaporated Cr species quantities and degradation rates of SOFC. Based on the great performance of AFAs after long-term operation, AFAs are assembled with Anode-supported cells (ASC) to investigate the the Cr deposition of anode-supported cell under a constant current density of 0.5 A cm -2 at 800 °C with AFA alloys compared with commercial alloys. In addition, the anodic and cathodic processes are deconvoluted by distribution of relaxation times (DRT) method which are comprehensively discussed. It is found out that the voltage exhibited a slight decrease of 5.09 % and 1.54 % in the presence of OC11 and OC11LZA alloy, respectively. However, a considerable decrease of 22.14 % and 12.06 % was determined in the presence of 310S and 625 alloy, respectively. AFAs possessing the low-cost, low Cr evaporation rates and the high oxidation resistance will make it of great potential to replace the existing BoP components.

01 COAL, LIGNITE, AND PEAT↗

Minimizing Cr-Evaporation from Balance of Plant Components by Utilizing Cost-Effective Alumina-Forming Austenitic Steels

A solid oxide fuel cell (SOFC) is a clean and efficient energy conversion device. The development of intermediate-temperature SOFCs has made it preferable to use metallic interconnects (MICs) to greatly reduce the cost and significantly increase the efficiency compared to ceramic interconnect materials. However, gaseous chromium species will evaporate from the chromium-containing layer formed on the surface of commonly used MICs and balance of plant (BoP) components. Volatile chromium species have been shown to form solid deposits which poison the cathodes of SOFCs, causing drastic cell performance degradation and thereby limiting commercialization. In order to alleviate the Cr poisoning and achieve long-term high performance of SOFC stacks, various Al2O3-forming austenitic (AFA) stainless steels applied at different temperatures are evaluated in this project. Based on our Phase I results (500 h operation), it is shown that on the AFAs, an alumina-based protective layer forms under high temperature that is invulnerable to water vapor effects and suppresses the diffusion of chromium and manganese which can prevent the generation of spinels on the alloy surface. Therefore, 310S, OC4 and OC5 at 800 °C and 625, OC11 and OC11LZ at 900 °C are selected to be tested in the Phase II long-term operation. From the results, we find that besides the lower Cr evaporation rates and better oxidation resistance of AFAs than benchmark alloys after short-term (500 h) operation, AFAs also possess the sturdy and compact alumina layer after a long-term operation (5000 h). A protective oxide layer is of great importance for the long-term high-temperature operation of structural materials. The high-temperature oxidation behavior of AFAs and commercial 310S and 625 alloys in Air + 10% H 2 O at 800 °C and 900 °C is systematically investigated. Severe breakaway oxidation and minor spallation are observed for the 310S and 625 after the long-term operation, while the AFAs show high oxidation resistance. It is found that the formation of a continuous alumina layer could greatly prevent the volatilization of chromium vapors. In addition, the corresponding evolving models are discussed. Chromium evaporation from BoP components in high-temperature environment could severely deteriorate the electrochemical performance of SOFC. Several methods were applied to evaluate the Cr evaporation rates of BoP after 500 h exposure at 800 °C to 900 °C in air with 10% H 2 O. An optimal method was designed to exclude the effect of silicon (Si) deposits from quartz tube and sodium (Na) deposits from the sodium carbonate on the oxidation process and the chemical interaction between Cr gaseous species and alumina tube which could provide further quantitative correlation of the evaporated Cr species quantities and degradation rates of SOFC. Based on the great performance of AFAs after long-term operation, AFAs are assembled with Anode-supported cells (ASC) to investigate the the Cr deposition of anode-supported cell under a constant current density of 0.5 A cm -2 at 800 °C with AFA alloys compared with commercial alloys. In addition, the anodic and cathodic processes are deconvoluted by distribution of relaxation times (DRT) method which are comprehensively discussed. It is found out that the voltage exhibited a slight decrease of 5.09 % and 1.54 % in the presence of OC11 and OC11LZA alloy, respectively. However, a considerable decrease of 22.14 % and 12.06 % was determined in the presence of 310S and 625 alloy, respectively. AFAs possessing the low-cost, low Cr evaporation rates and the high oxidation resistance will make it of great potential to replace the existing BoP components.

36 MATERIALS SCIENCE↗

Surrogate models to optimize plasma-assisted atomic layer deposition in high aspect ratio features

In this work, we explore surrogate models to optimize plasma enhanced atomic layer deposition (PEALD) in high aspect ratio features. In plasma-based processes such as PEALD and atomic layer etching (ALE), surface recombination can dominate the reactivity of plasma species with the surface, which can lead to unfeasibly long exposure times to achieve full conformality inside nanostructures like high aspect ratio vias. Using a synthetic dataset based on simulations of PEALD, we train artificial neural networks to predict saturation times based on cross section thickness data obtained for partially coated conditions. The results obtained show that just two experiments in undersaturated conditions contain enough information to predict saturation times within 10% of the ground truth. A surrogate model trained to determine whether surface recombination dominates the plasma–surface interactions in a PEALD process achieves 99% accuracy. This demonstrates that machine learning can provide a new pathway to accelerate the optimization of PEALD processes in areas such as microelectronics. Our approach can be easily extended to ALE and more complex structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗

Machine learning based algorithms for uncertainty quantification in numerical weather prediction models

Complex numerical weather prediction models incorporate a variety of physical processes, each described by multiple alternative physical schemes with specific parameters. The selection of the physical schemes and the choice of the corresponding physical parameters during model configuration can significantly impact the accuracy of model forecasts. There is no combination of physical schemes that works best for all times, at all locations, and under all conditions. It is therefore of considerable interest to understand the interplay between the choice of physics and the accuracy of the resulting forecasts under different conditions. This paper demonstrates the use of machine learning techniques to study the uncertainty in numerical weather prediction models due to the interaction of multiple physical processes. The first problem addressed herein is the estimation of systematic model errors in output quantities of interest at future times, and the use of this information to improve the model forecasts. The second problem considered is the identification of those specific physical processes that contribute most to the forecast uncertainty in the quantity of interest under specified meteorological conditions. In order to address these questions we employ two machine learning approaches, random forests and artificial neural networks. The discrepancies between model results and observations at past times are used to learn the relationships between the choice of physical processes and the resulting forecast errors. Numerical experiments are carried out with the Weather Research and Forecasting (WRF) model. The output quantity of interest is the model precipitation, a variable that is both extremely important and very challenging to forecast. The physical processes under consideration include various micro-physics schemes, cumulus parameterizations, short wave, and long wave radiation schemes. The experiments demonstrate the strong potential of machine learning approaches to aid the study of model errors.

97 MATHEMATICS AND COMPUTING↗

The Role of Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology: Proceedings of a Workshop

Quantum concepts hold the potential to enable significant advances in sensing and imaging technologies that could be vital to the study of biological systems. The workshop Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology, held online March 8–10, 2021, was organized to examine the research and development needs to advance biological applications of quantum technology. Hosted by the National Academies of Sciences, Engineering, and Medicine, the event brought together experts working on state-of-the-art, quantum-enabled technologies and scientists who are interested in applying these technologies to biological systems. Through talks, panels, and discussions, the workshop facilitated a better understanding of the current and future biological applications of quantum-enabled technologies in fields such as microbiology, molecular biology, cell biology, plant science, mycology, and many others. The workshop was organized around three main themes. The first, quantum in biology, examined quantum concepts that are hypothesized to be important for life processes and that researchers are working to observe through biological imaging and sensing. The second, quantum for biology, addressed ways to use quantum concepts to enhance technologies for biological imaging and sensing. The third, biology for quantum, offered a wider discussion of how the frontiers of biological imaging and sensing could enable future study using quantum concepts, tools, or technologies. Throughout the workshop, participants identified a wide range of emerging approaches and opportunities at the intersection of quantum physics and biological sensing and imaging. During the workshop, there were some differences in how each speaker defined the term quantum. During one of the panels, Prem Kumar offered thoughts on what phenomena are classical versus quantum, explaining that techniques get progressively more quantum as you move from just having superposition to having superposition with measurement and entanglement. Another explanation from Clarice Aiello delineates the definition into several levels. This includes a base level of “quantum-ness,” which reflects that all matter is made of atoms, and when these particles are isolated they behave based on quantum mechanical principles. A second level is related to quantum coherence, where a single quantum object might be found in a coherent superposition state. A final level, which she described as the quantum-entangled level, involves multiple quantum systems which are entangled among themselves. Overall, the workshop touched on concepts such as superposition, entanglement, and squeezing and their potential implications for communication, computing, and simulation, in addition to the workshop’s main focal area, biological sensing and imaging. At the opening of the workshop, Thorsten Ritz of the University of California, Irvine, identified two questions at the heart of quantum biology: Is the machinery of life quantum mechanical, and can quantum mechanics be used to study the machinery of life in new ways? Participants highlighted systems in which researchers have explored these questions, from the vast array of molecular interactions involved in biological processes such as photosynthesis, to the mechanics involved in cellular functions such as differentiation and aggregation, to the role of oscillating magnetic fields in flight orientation among birds. Sensing and imaging technologies are crucial to biological research; these technologies could both enhance the study of quantum effects and be enhanced by quantum concepts. A critical challenge in biological research is to develop imaging and sensing tools that do not damage or interfere with the often fragile and fleeting systems being studied. Attendees discussed a variety of established and emerging technologies that could enhance noninvasive biological imaging, including single- and two-photon spectroscopy, single-molecule spectroscopy, quantum illumination, ghost imaging, and cryo-electron microscopy. One example came from Marlan Scully who gave a keynote address on the first day of the workshop. Scully emphasized the use of different laser technologies, which exhibit coherence and other quantum properties, in moving toward real-world biological applications, such as the detection of SARS-CoV-2. Both tools and theory will play an important role in advancing quantum biology research and applications. Several participants suggested theorists and experimentalists should work in tandem to understand and model biological processes. While physics often reduces systems to their simplest forms for fundamental insights, participants also noted the value of observing and understanding biological systems in all their “messiness,” capturing both the inner workings of biological systems and the complex interactions that occur within and between organisms. In discussions among participants, several attendees stressed the need to match emerging tools with the right scientific questions. Rather than developing quantum technologies as “a hammer looking for a nail,” participants emphasized a focus on exploring the problems these technologies are best suited to address. For example, it is important to consider the size of the phenomenon being studied, the timescales that are important in answering the scientific question, and other relevant considerations. Every tool along the spectrum from classical to quantum involves its own set of trade-offs. For example, Ted Laurence of the Lawrence Livermore National Laboratory said that quantum measurements, such as single photon counting, fluorescence transitions, and lasers, can take longer to produce the same results as classical measurements. These quantum measurements, however, do not require calibration and can enable new research questions to be answered. Prem Kumar, Northwestern University, noted that, despite their promise, quantum approaches should not be used simply for the sake of using quantum, especially in situations where classical approaches better meet the needs of the researcher. Understanding and applying quantum concepts could enable advances in a wide range of application areas including energy, synthetic biology, medicine, and sustainability. For example, Michelle O’Malley, University of California, Santa Barbara, described how improved noninvasive imaging approaches could help capture the complex interactions and functions involved in the breakdown of organic matter by microbial communities and lead to new technologies for capturing valuable products from plant waste. Several other participants discussed needs in tracking the movement of metabolites and molecules in microbial communities for insights into nutrient cycling in environments such as soil. Margaret Ahmad, Sorbonne University, discussed potential opportunities to leverage the magnetic properties of cryptochromes to advance new treatment approaches for diseases such as COVID-19 and cancer. Looking toward the future development of the field, participants discussed challenges to advancing quantum biology that arise from disciplinary disconnects between physicists and biologists. The siloing of academic research disciplines represents a significant barrier to progress. Disconnects in terminology, motivations and priorities, and structural barriers to collaborative work underscore the need for concerted efforts to bridge these divides. Attendees and speakers offered suggestions for resolving these divergences, establishing a shared language, moving the field forward, and fostering meaningful feedback between disciplines. Overall, participants stressed a need for balance, open communication, collaboration, unity, and clear dialogue on trade-offs between quantum and classical approaches. Keiko Torii, The University of Texas at Austin, said that the best collaborations happen when the project provides mutual advantages that can show off everyone’s talents, each team finds the work interesting, and partners develop a camaraderie to pursue new knowledge. To enable near- and long-term opportunities in this space, participants suggested that exploratory, high-risk funding could improve existing instrumentation to explore quantum enhancement collaboratively. They also emphasized the need for collaboration between quantum physicists and sensing/imaging scientists, which could be advanced through a dedicated quantum biology investigator program. People, even more than technology, will be crucial to the future of quantum biology. Participants explored training, education, and workforce needs to further develop this burgeoning field and cultivate the next generation of scientists. While many programs are still in their nascent stages, participants highlighted examples of approaches and programs being developed at various types of institutions to engage students and professional scientists in quantum biology research. Several participants stressed the need for an inclusive approach, spanning disciplines as well as communities to foster a diverse field fueled by the intellectual contributions of a wide range of people, including historically under-resourced schools and students. To increase awareness and excitement about quantum physics and related areas of biology, attendees suggested capitalizing on the “buzz” around quantum. Several participants emphasized the need to start early, introducing students to quantum concepts and their appealing “weirdness” in K–12 education. Engaging students early—before they become entrenched in traditional disciplinary siloes as typically happens in graduate school—could help to galvanize interest in the area and foster a generation of scientists with the interdisciplinary mindset and skills needed to advance this interdisciplinary field. While these efforts could be advanced at many levels and across multiple sectors, several participants suggested a national quantum biology center could be a valuable hub to coordinate and support quantum biology education and workforce development across academia, industry, and government.

59 BASIC BIOLOGICAL SCIENCES↗

Photophysical Properties and Electronic Structure of Hydroporphyrin Dyads Exhibiting Strong Through-Space and Through-Bond Electronic Interactions

Electronic interactions between tetrapyrroles are utilized in natural photosynthetic systems to tune the light-harvesting and energy/charge-transfer processes in these assemblies. Such interactions also can be employed to tailor the electronic properties of tetrapyrrolic dyads and larger arrays for use in materials science and biomedical research. Here we have utilized static and time-resolved optical spectroscopy to characterize the optical absorption and emission properties of a set of chlorin and bacteriochlorin dyads with varied degrees of through-bond (TB) and through-space (TS) interactions between the constituent macrocycles. The dyads consist of two chlorins or two bacteriochlorins joined by a linker that utilizes a triple-double-triple bond (enediyne) motif in which the double bond portion is a ester-substituted ethylene or o-phenylene unit. The photophysical studies are coupled with density functional theory (DFT) calculations to probe the ground-state molecular orbital (MO) characteristics of the dyads and time-dependent calculations (TDDFT) to elucidate excited-state properties. The latter include electronic characteristics of the singlet excited state manifold and the absorption transitions to these states from the electronic ground state. Comparison of the MO and calculated spectral properties of each dyad with the linker present versus disrupted (by eliminating the double-bond portion) gives insight into the relative contributions of TB versus TS interactions to the electronic properties of the dyads. The results show that the TB and TS contributions are additive (constructively interfere), which is not always the case for molecular dyads. Most of the dyads have shorter lifetimes of the lowest singlet excited state compared to the parent monomer, which derives from increased S 1 → S 0 internal conversion. The enhancement is greater for the dyads in benzonitrile than in toluene. Furthermore, the studies provide insights into the nature of the electronic interactions between the constituents in the tetrapyrrole arrays and how these interactions dictate the spectral properties and excited-state decay characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual’s response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

59 BASIC BIOLOGICAL SCIENCES↗

On the interactions between molten aluminum and high entropy alloy particles during aluminum matrix composite processing

The feasibility of adding AlCrTiV high entropy alloy (HEA) particles to molten aluminum to make metal matrix composites was studied. Equiatomic AlCrTiV HEA particles, produced by a solid state reduction process, were dispersed into pure aluminum and 7075 alloy (Al-5.8Zn-2.3Mg-1.4Cu, all weight %) melt and by a ultrasonic dispenser. It was found that the AlCrTiV particles reacted with molten aluminum, leading to the formation of Al 45 (Cr,V) 7 and Al 3 Ti intermetallic phases in the aluminum matrix composites. Although the AlCrTiV HEA particles did not survive in molten aluminum during composite processing, the final composite materials showed significantly improved mechanical properties, due to grain refinement and dispersion strengthening. Finally, the research suggests that the interactions between matrix aluminum alloys and the particles are key in controlling the final microstructure and properties of the composites.

36 MATERIALS SCIENCE↗

Recent Insights Into Interfacial Transport and Chemical Reactions of Plasma–Generated Species in Liquid

The chemistry of plasma–liquid interactions involves a complex interplay of physical and chemical processes at the plasma–liquid interface. These interactions give rise to the generation, transport, and transformation of various reactive species. Since the publication of the Lorenz Roadmap in 2016, significant progress has been made in understanding the interfacial transport and coupled reactions of plasma-generated species with inorganic and organic compounds. However, critical aspects of plasma–liquid chemistry and mass transfer still require further investigation. Here, this review summarizes recent work on processes at the plasma–liquid interface and the coupled reactions in the liquid phase. We highlight key findings related to the involvement of O atoms, H radicals, solvated electrons, photons, and nitrogen-derived species at the interface and within the bulk liquid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Architected mesoporous crystalline magnesium silicates with ordered pore structures

Novel approaches to harness earth abundant silicates as building blocks for carbon dioxide removal, capture, utilization, and storage are gaining increasing attention in the context of sustainable and low carbon energy and resource recovery. Advancing a calibrated understanding of these fluid-silicate interactions is essential for developing scalable processes. One of the challenges in developing predictive controls over these interactions is the compositional and morphological heterogeneity of naturally occurring, heterogeneous magnesium silicate minerals. To address this challenge, the synthesis of architected mesoporous crystalline magnesium silicate (Mg 2 SiO 4 ) is proposed. While synthesis routes for producing amorphous mesoporous magnesium silicates have been developed via sol-gel methods, approaches to synthesize crystalline magnesium silicates with well-controlled pore size distributions have not been explored. The conventional approaches of converting matter that is amorphous to crystalline states at elevated temperatures results in a heterogeneous pore size distribution. To develop controls on pore size distribution, amorphous mesoporous magnesium silicates are coated with carbon. This approach preserves the pore size distributions during the amorphous to crystalline transformations of Mg-silicates at elevated temperatures. The carbon coating is removed on heating. Magnesium silicate particles produced using this approach have highly ordered pores around 2.58 nm and a specific surface area of 124.25 m 2 /g. In this study, we report the chemical compositions, morphologies, phase transitions, and pore structures of the intermediate materials produced during the synthesis of crystalline mesoporous magnesium silicates. The transitions, and pore structures of the intermediate materials produced during the synthesis of crystalline mesoporous magnesium silicates. Furthermore, the synthesis routes discussed in this study can be applied translationally to produce metal silicates with ordered mesoporous structures.

36 MATERIALS SCIENCE↗

Using Diel Solute Signals to Assess Ecohydrological Processing in Lotic Systems

Lotic systems are a prominent ecohydrological interface within which complex, coupled interactions occur between ecological, hydrological, and geochemical processes. This chapter reviews the ecological processes driving diel signals in oxygen as well as major nutrients and other trace elements. It discusses how diel signals can be used to evaluate functioning and interactions within stream ecosystems. The chapter considers potential future research directions and outstanding questions still to be addressed by or about diel solute signals and associated processes. High-resolution sensor-based time series and associated tools and conceptual advances are being integrated into environmental management. Quantitative tools to disentangle diel biogeochemically-driven signals from other sources of variability in continuous time series are growing. Theoretical models of diel process dynamics are helping to spur hypothesis generation and new ways of approaching diel signals in lotic systems.

Kurz, Marie↗

Energy conversion and transport in molecular-scale junctions

Molecular-scale junctions (MSJs) have been considered the ideal testbed for probing physical and chemical processes at the molecular scale. Due to nanometric confinement, charge and energy transport in MSJs are governed by quantum mechanically dictated energy profiles, which can be tuned chemically or physically with atomic precision, offering rich possibilities beyond conventional semiconductor devices. While charge transport in MSJs has been extensively studied over the past two decades, understanding energy conversion and transport in MSJs has only become experimentally attainable in recent years. As demonstrated recently, by tuning the quantum interplay between the electrodes, the molecular core, and the contact interfaces, energy processes can be manipulated to achieve desired functionalities, opening new avenues for molecular electronics, energy harvesting, and sensing applications. This Review provides a comprehensive overview and critical analysis of various forms of energy conversion and transport processes in MSJs and their associated applications. We elaborate on energy-related processes mediated by the interaction between the core molecular structure in MSJs and different external stimuli, such as light, heat, electric field, magnetic field, force, and other environmental cues. Key topics covered include photovoltaics, electroluminescence, thermoelectricity, heat conduction, catalysis, spin-mediated phenomena, and vibrational effects. Furthermore, the review concludes with a discussion of existing challenges and future opportunities, aiming to facilitate in-depth future investigation of promising experimental platforms, molecular design principles, control strategies, and new application scenarios.

Charge transport↗

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗

Volatile Organic Compounds in Bankhead National Forest (AMF3). August to September, 2025

The formation of atmospheric aerosols through the transformation of volatile organic compounds (VOCs) is a fundamental process in aerosol-climate interactions, as these particles serve as cloud condensation nuclei and ultimately influence Earth’s radiative balance. However, there remains a critical need to quantify the effects of multiple coexisting VOC precursors on aerosol formation beyond the limitations of laboratory-scale studies. This research aims to advance the mechanistic understanding of secondary organic aerosol formation in the southeastern United States by investigating interactions among coexisting VOC precursors observed at the third ARM Mobile Facility located in the Bankhead National Forest. The dataset was generated from the deployment of Oak Ridge National Laboratory’s PTR-TOF 6000 X2 Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS) for the real-time, continuous monitoring of VOCs from August 21 to September 15, 2025. To minimize sampling artifacts and compound losses, the PTR-ToF-MS inlet was connected to the cabin flow line by replacing the existing Tygon tubing with 1/2-inch outer diameter perfluoroalkoxy (PFA) tubing. The instrument operated on an hourly measurement cycle consisting of 8 minutes of zero-air measurements followed by 52 minutes of ambient air sampling, with a temporal resolution of 10 seconds. The dataset includes concentrations, reported in ppb, of methanol, acetone, acetonitrile, isoprene, methyl vinyl ketone and methacrolein (MVK + MACR), monoterpenes, benzene, toluene, and catechol.

Atmospheric concentration of volatile organic comp↗

JAMES BUTTLE REVIEW: Interflow, subsurface stormflow and throughflow: A synthesis of field work and modelling

Interflow, throughflow and subsurface stormflow are interchangeable terms that refer to the lateral subsurface flow above a restricting layer of lower hydraulic conductivity that occurs during and following storm events. Interflow (used here) is a more dominant process in steeper catchments with high infiltration capacity soils overlying a more impermeable soil or geologic layer. Interflow as a runoff process was first recognised in the early 1900s, yet hydrologists still struggle to predict its occurrence, persistence, importance, interaction with other streamflow generation processes, and potential to connect to valleys and streams during and following storms. We review the history of interflow research and address some of the challenges in understanding its role in runoff production. We argue that characterising the controls on interflow initiation and occurrence relies on detailed field observations of subsurface properties, which exist only in limited experimental settings. This data shortcoming contributes to our inability to predict interflow or determine its contribution to streamflow more broadly. There remain many opportunities to advance our understanding of interflow that include both modelling and experimental or observational approaches in hydrology.

hillslope hydrology↗