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At least 469 records · Page 26

Alkaline earth stannates: The next silicon?

Semiconductor materials are being used in an increasingly diverse array of applications, with new device concepts being proposed each year for solar cells, flat-panel displays, sensors, memory, and spin transport. This rapid progress of invention outpaces the development of new semiconductor materials with the required properties and performance. In many applications, high carrier mobility at room temperature is required in addition to specific functional properties critical to the device concept. We review recent developments on high mobility stannate perovskite oxide materials and devices.

36 MATERIALS SCIENCE↗

Structural and dynamical description of the enzymatic reaction of a phosphohexomutase

Enzymes are known to adopt various conformations at different points along their catalytic cycles. Here, we present a comprehensive analysis of 15 isomorphous, high resolution crystal structures of the enzyme phosphoglucomutase from the bacterium Xanthomonas citri. The protein was captured in distinct states critical to function, including enzyme-substrate, enzyme-product, and enzyme-intermediate complexes. Key residues in ligand recognition and regions undergoing conformational change are identified and correlated with the various steps of the catalytic reaction. In addition, we use principal component analysis to examine various subsets of these structures with two goals: (1) identifying sites of conformational heterogeneity through a comparison of room temperature and cryogenic structures of the apo-enzyme and (2) a priori clustering of the enzyme-ligand complexes into functionally related groups, showing sensitivity of this method to structural features difficult to detect by traditional methods. This study captures, in a single system, the structural basis of diverse substrate recognition, the subtle impact of covalent modification, and the role of ligand-induced conformational change in this representative enzyme of the α-D-phosphohexomutase superfamily.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel technologies for emission reduction complement conservation agriculture to achieve negative emissions from row-crop production

Plants remove carbon dioxide from the atmosphere through photosynthesis. Because agriculture’s productivity is based on this process, a combination of technologies to reduce emissions and enhance soil carbon storage can allow this sector to achieve net negative emissions while maintaining high productivity. Unfortunately, current row-crop agricultural practice generates about 5% of greenhouse gas emissions in the United States and European Union. Here, to reduce these emissions, significant effort has been focused on changing farm management practices to maximize soil carbon. In contrast, the potential to reduce emissions has largely been neglected. Through a combination of innovations in digital agriculture, crop and microbial genetics, and electrification, we estimate that a 71% (1,744 kg CO 2 e/ha) reduction in greenhouse gas emissions from row crop agriculture is possible within the next 15 y. Importantly, emission reduction can lower the barrier to broad adoption by proceeding through multiple stages with meaningful improvements that gradually facilitate the transition to net negative practices. Emerging voluntary and regulatory ecosystems services markets will incentivize progress along this transition pathway and guide public and private investments toward technology development. In the difficult quest for net negative emissions, all tools, including emission reduction and soil carbon storage, must be developed to allow agriculture to maintain its critical societal function of provisioning society while, at the same time, generating environmental benefits.

54 ENVIRONMENTAL SCIENCES↗

NTRC regulates CP12 to activate Calvin–Benson cycle during cold acclimation

NADPH-dependent thioredoxin reductase C (NTRC) is a chloroplast redox regulator in algae and plants. Here, we used site-specific mutation analyses of the thioredoxin domain active site of NTRC in the green alga Chlamydomonas reinhardtii to show that NTRC mediates cold tolerance in a redox-dependent manner. By means of coimmunoprecipitation and mass spectrometry, a redox- and cold-dependent binding of the Calvin–Benson Cycle Protein 12 (CP12) to NTRC was identified. NTRC was subsequently demonstrated to directly reduce CP12 of C. reinhardtii as well as that of the vascular plant Arabidopsis thaliana in vitro. As a scaffold protein, CP12 joins the Calvin–Benson cycle enzymes phosphoribulokinase (PRK) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) to form an autoinhibitory supracomplex. Using size-exclusion chromatography, NTRC from both organisms was shown to control the integrity of this complex in vitro and thereby PRK and GAPDH activities in the cold. Thus, NTRC apparently reduces CP12, hence triggering the dissociation of the PRK/CP12/GAPDH complex in the cold. Like the ntrc::aphVIII mutant, CRISPR-based cp12::emx1 mutants also exhibited a redox-dependent cold phenotype. In addition, CP12 deletion resulted in robust decreases in both PRK and GAPDH protein levels implying a protein protection effect of CP12. Both CP12 functions are critical for preparing a repertoire of enzymes for rapid activation in response to environmental changes. This provides a crucial mechanism for cold acclimation.

54 ENVIRONMENTAL SCIENCES↗

MICROLENSING DISCOVERY OF A POPULATION OF VERY TIGHT, VERY LOW MASS BINARY BROWN DWARFS

Although many models have been proposed, the physical mechanisms responsible for the formation of low-mass brown dwarfs (BDs) are poorly understood. The multiplicity properties and minimum mass of the BD mass function provide critical empirical diagnostics of these mechanisms. We present the discovery via gravitational microlensing of two very low mass, very tight binary systems. These binaries have directly and precisely measured total system masses of 0.025 M{sub Sun} and 0.034 M{sub Sun }, and projected separations of 0.31 AU and 0.19 AU, making them the lowest-mass and tightest field BD binaries known. The discovery of a population of such binaries indicates that BD binaries can robustly form at least down to masses of {approx}0.02 M{sub Sun }. Future microlensing surveys will measure a mass-selected sample of BD binary systems, which can then be directly compared to similar samples of stellar binaries.

79 ASTRONOMY AND ASTROPHYSICS↗

Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions

Abstract To generate material models with fewer limiting assumptions while maintaining closed-form, interpretable solutions, we propose using genetic programming based symbolic regression (GPSR), a machine learning (ML) approach that describes data using free-form symbolic expressions. To maximize interpretability, we start from an analytical, derived material model, the Gurson model for porous ductile metals, and systematically relax inherent assumptions made in its derivation to understand each assumption’s contribution to the GPSR model forms. We incorporate transfer learning methods into the GPSR training process to increase GPSR efficiency and generate models that abide by known mechanics of the system. The results show that regularizing the GPSR fitness function is critical for generating physically valid models and illustrate how GPSR allows a high level of interpretability compared with other ML approaches. The method of systematic assumption relaxation allows the generation of models that address limiting assumptions found in the Gurson model, and the symbolic forms allow conjecture of decreased material strength due to void interaction and non-symmetric void shapes.

36 MATERIALS SCIENCE↗

2D-FFTLog: efficient computation of real-space covariance matrices for galaxy clustering and weak lensing

ABSTRACT Accurate covariance matrices for two-point functions are critical for inferring cosmological parameters in likelihood analyses of large-scale structure surveys. Among various approaches to obtaining the covariance, analytic computation is much faster and less noisy than estimation from data or simulations. However, the transform of covariances from Fourier space to real space involves integrals with two Bessel integrals, which are numerically slow and easily affected by numerical uncertainties. Inaccurate covariances may lead to significant errors in the inference of the cosmological parameters. In this paper, we introduce a 2D-FFTLog algorithm for efficient, accurate, and numerically stable computation of non-Gaussian real-space covariances for both 3D and projected statistics. The 2D-FFTLog algorithm is easily extended to perform real-space bin-averaging. We apply the algorithm to the covariances for galaxy clustering and weak lensing for a Dark Energy Survey Year 3-like and a Rubin Observatory’s Legacy Survey of Space and Time Year 1-like survey, and demonstrate that for both surveys, our algorithm can produce numerically stable angular bin-averaged covariances with the flat sky approximation, which are sufficiently accurate for inferring cosmological parameters. The code CosmoCov for computing the real-space covariances with or without the flat-sky approximation is released along with this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Functional form of the superconducting critical temperature from machine learning

Predicting the critical temperature $T_c$ of new superconductors is a notoriously difficult task, even for electron-phonon paired superconductors, for which the theory is relatively well understood. Early attempts to obtain a simple $T_c$ formula consistent with strong-coupling theory, by McMillan and by Allen and Dynes, led to closed-form approximate relations between $T_c$ and various measures of the phonon spectrum and the electron-phonon interaction appearing in Eliashberg theory. Here we propose that these approaches can be improved with the use of machine-learning algorithms. As an initial test, we train a model for identifying low-dimensional descriptors using the $T_c$ < 10 K dataset by Allen and Dynes, and show that a simple analytical expression thus obtained improves upon the Allen-Dynes fit. Furthermore, the prediction for the recently discovered high-$T_c$ material H 3 S at high pressure is quite reasonable. Interestingly, $T_c$'s for more recently discovered superconducting systems with a more two-dimensional electron-phonon coupling, which do not follow Allen and Dynes's expression, also do not follow our analytic expression. Thus, this machine-learning approach appears to be a powerful method for highlighting the need for a new descriptor beyond those used by Allen and Dynes to describe their set of isotropic electron-phonon coupled superconductors. Finally, we argue that this machine-learning method, and its implied need for a descriptor characterizing Fermi-surface properties, represents a promising approach to superconductor materials discovery which may eventually replace the serendipitous discovery paradigm begun by Kamerlingh Onnes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Superfluid density in overdoped cuprates: Thin films versus bulk samples

Recent study of overdoped La 2–x Sr x CuO 4 cuprate superconductor thin films by Božovic et al. has revealed several unexpected findings, most notably the violation of the BCS description which was believed to adequately describe overdoped cuprates. In particular, it was found that the superfluid density in La 2–x Sr x CuO 4 films decreases on the overdoped side as a linear function of critical temperature T c , which was taken as evidence for the violation of Homes' law. Here we show explicitly that the law is indeed violated, and as the main reason for violation we find that the superfluid density in Božovic's films is suppressed more strongly than in bulk samples. Based on the existing literature data, we show that the superfluid density in bulk cuprate samples does not decrease with doping, but instead tends to saturate on the overdoped side. The result is also supported by our recent measurement of a heavily overdoped bulk La 2–x Sr x CuO 4 sample. Moreover, this saturation of superfluid density might not be limited to cuprates, as we find evidence for similar behavior in two pnictide superconductor families. We argue that quantum phase fluctuations play an important role in suppressing the superfluid density in thin films.

2-dimensional systems↗

Crystal structures of 40- and 71-substitution variants of hydroxynitrile lyase from rubber tree

Hydroxynitrile lyase fromHevea brasiliensis(HbHNL) and the esterase SABP2 fromNicotiana tabacumshare the α/β-hydrolase fold, a Ser–His–Asp catalytic triad and 44% sequence identity, yet catalyze different reactions. Prior studies showed that three active-site substitutions inHbHNL conferred weak esterase activity. To investigate how regions beyond the active site influence catalytic efficiency and active-site geometry, we engineeredHbHNL variants with increasing numbers of substitutions to match SABP2. Variant HNL16 has all amino acids within 6.5 Å of the active site identical to SABP2, HNL40 those within 10 Å and HNL71 those within 14 Å. HNL16 exhibited poor esterase activity, whereas both HNL40 and HNL71 showed efficient esterase catalysis, demonstrating that residues beyond the immediate active site are critical for functional conversion. X-ray structures of HNL40 and HNL71 reveal a progressive shift in backbone positions toward those of SABP2, with r.m.s.d. values of 0.51 Å (HNL40) and 0.41 Å (HNL71) over the C α atoms, and even smaller r.m.s.d.s within the active-site region. Both HNL40 and HNL71 show a restored oxyanion hole and an additional tunnel connecting the active site to the protein surface. This work demonstrates the essential role of distant, indirectly acting residues to catalysis in α/β-hydrolase enzymes.

Biochemistry & Molecular Biology↗

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

A metric framework for evaluating the resilience contribution of hydropower to the grid

This paper will describe a proposed framework for expressing the resilience of hydropower generation and provide initial case studies for three classes of hydropower, run-of-river hydropower, hydropower with reservoirs, and pumped storage hydropower. Hydropower has great flexibility to provide support during and after natural and man-made events that can disrupt critical infrastructure functionality. The concept of the framework provides for consideration of policy and rules, constraints of the water shed and other allocations of water, storage and plant capabilities to produce real and reactive power, and the strength of the delivery network. The paper details a resilience response metric that has inputs of state of storage and plant level constraints on real and reactive power production. Using the definition of resilience, based on maintaining a minimally normal operations, we provide a qualitative assessment of hydropower’s ability to address the various time scales comprising the “R”s of resilience.

13 HYDRO ENERGY↗

The role of CenKR in the coordination of Rhodobacter sphaeroides cell elongation and division

ABSTRACT Cell elongation and division are essential aspects of the bacterial life cycle that must be coordinated for viability and replication. The impact of misregulation of these processes is not well understood as these systems are often not amenable to traditional genetic manipulation. Recently, we reported on the CenKR two-component system (TCS) in the Gram-negative bacterium Rhodobacter sphaeroides that is genetically tractable, widely conserved in α-proteobacteria, and directly regulates the expression of components crucial for cell elongation and division, including genes encoding subunit of the Tol-Pal complex. In this work, we show that overexpression of cenK results in cell filamentation and chaining. Using cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), we generated high-resolution two-dimensional (2D) images and three-dimensional (3D) volumes of the cell envelope and division septum of wild-type cells and a cenK overexpression strain finding that these morphological changes stem from defects in outer membrane (OM) and peptidoglycan (PG) constriction. By monitoring the localization of Pal, PG biosynthesis, and the bacterial cytoskeletal proteins MreB and FtsZ, we developed a model for how increased CenKR activity leads to changes in cell elongation and division. This model predicts that increased CenKR activity decreases the mobility of Pal, delaying OM constriction, and ultimately disrupting the midcell positioning of MreB and FtsZ and interfering with the spatial regulation of PG synthesis and remodeling. IMPORTANCE By coordinating cell elongation and division, bacteria maintain their shape, support critical envelope functions, and orchestrate division. Regulatory and assembly systems have been implicated in these processes in some well-studied Gram-negative bacteria. However, we lack information on these processes and their conservation across the bacterial phylogeny. In R. sphaeroides and other α-proteobacteria, CenKR is an essential two-component system (TCS) that regulates the expression of genes known or predicted to function in cell envelope biosynthesis, elongation, and/or division. Here, we leverage unique features of CenKR to understand how increasing its activity impacts cell elongation/division and use antibiotics to identify how modulating the activity of this TCS leads to changes in cell morphology. Our results provide new insight into how CenKR activity controls the structure and function of the bacterial envelope, the localization of cell elongation and division machinery, and cellular processes in organisms with importance in health, host-microbe interactions, and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗

A Viral Ecogenomics Framework To Uncover the Secrets of Nature’s “Microbe Whisperers”

Microbes drive critical ecosystem functions and affect global nutrient cycling along with human health and disease. They do so under strong constraints exerted by viruses, which shape microbial communities’ structure and shift host cell metabolism during infection. While the majority of viruses and their associated impacts remain poorly characterized, a number of mechanisms by which viruses alter microbial cells and ecosystems have already been revealed. Here I outline how a comprehensive host-resolved mapping of viral sequence space will enable a thorough characterization of virus-encoded mechanisms for microbial manipulation. With soon-to-be millions of virus genomes obtained from metagenomes, one of the major challenges resides in the development of methods for high-throughput and high-resolution virus-host pairing, before multi-omics approaches can be leveraged to fully decipher virus-host dynamics in nature. Beyond novel fundamental biological knowledge, these studies will likely provide new molecular tools enabling a precise engineering of microbial cells and communities.

59 BASIC BIOLOGICAL SCIENCES↗

G2Aero: A Python package for separable shape tensors

G2Aero is a Python package for the design and deformation of discrete planar curves and tubular surfaces using a geometric data-driven approach. G2Aero utilizes a topology of product manifolds: the Grassmannian, $\mathcal{G}$($\mathcal{n}$, 2) - the set of 2-dimensional subspaces in $\mathbb{R}$ $\mathcal{n}$ - and the symmetric positive-definite (SPD) manifold, $\mathcal{S}^{2}_{++}$ - the set of 2x2 SPD matrices. The package provides a novel framework for representing separable deformations to shapes, which consist of stretching, scaling, rotating, and translating - also known as affine deformations - and a set of complementary deformations - which we refer to as undulation-type deformations. We focus on airfoil and blade design applications to emphasize the utility of the methods in an environment where the separation of affine and undulation-type deformations is critical. Notable functionalities of the framework for blade design include: 1) generating novel 2D (airfoil) shapes informed by a database of physically relevant airfoils, 2) building 3D blades by interpolating sequences of 2D airfoil cross-sections, and 3) generating blades with consistent perturbations along the blade span. We discuss the framework and provide examples in the context of wind energy applications, specifically wind turbine blade design. Figure 1 shows the wire frame obtained by interpolating airfoils defining the IEA 15-MW wind turbine blade and applying affine transformations corresponding to twist, chordal scaling, and bending. This, and all other figures in the paper, can be reproduced following examples and referencing supporting documentation provided in the G2Aero package.

97 MATHEMATICS AND COMPUTING↗

National Grid Deep Energy Retrofit Pilot

Through discussion of five case studies (test homes), this project evaluates strategies to elevate the performance of existing homes to a level commensurate with best-in-class implementation of high-performance new construction homes. The test homes featured in this research activity participated in Deep Energy Retrofit (DER) Pilot Program sponsored by the electric and gas utility National Gridin Massachusetts and Rhode Island. Building enclosure retrofit strategies are evaluated for impact on durability and indoor air quality in addition to energy performance. Evaluation of strategies is structured around the critical control functions of water, airflow, vapor flow, and thermal control. The aim of the research project is to develop guidance that could serve as a foundation for wideradoption of high performance, 'deep' retrofit work. The project will identify risk factors endemic to advanced retrofit in the context of the general building type, configuration and vintage encountered in the National Grid DER Pilot. Results for the test homes are based on observation and performance testing of recently completed projects. Additional observation would be needed to fully gaugelong-term energy performance, durability, and occupant comfort.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluating the Effects of the Kingston Fly Ash Release on Fish Reproduction: Spring 2009 – 2010 Studies

On December 22, 2008, a dike containing fly ash and bottom ash at the Tennessee Valley Authority's (TVA) Kingston Fossil Plant in East Tennessee failed and released a large quantity of ash into the adjacent Emory River. Ash deposits from the spill extended 4 miles upstream of the facility to Emory River mile 6 and downstream to Tennessee River mile 564 ({approx}8.5 miles downstream of the confluence of the Emory River with the Clinch River, and {approx}4 miles downstream of the confluence of the Clinch River with the Tennessee River). A byproduct of coal combustion, fly ash contains a variety of metals and other elements which, at sufficient concentrations and in specific forms, can be harmful to biological systems. The ecological effects of fly ash contamination on exposed fish populations depend on the magnitude and duration of exposure, with the most significant risk considered to come from elevated levels of certain metals in the ash, particularly selenium, on fish reproduction and fish early life stages (Lemly 1993; Besser and others 1996). The ovaries of adult female fish in a lake contaminated by coal ash were reported to have an increased frequency of atretic oocytes (dead or damaged immature eggs) and reductions in the overall numbers of developing oocytes (Sorensen 1988) associated with elevated body burdens of selenium. Larval fish exposed to selenium through maternal transfer of contaminants to developing eggs in either contaminated bodies of water (Lemly 1999) or in experimental laboratory exposures (Woock and others 1987, Jezierska and others 2009) have significantly increased incidences of developmental abnormalities. Contact of fertilized eggs and developing embryos to ash in water and sediments may also pose an additional risk to the early life stages of exposed fish populations through direct uptake of metals and other ash constituents (Jezierska and others 2009). The establishment and maintenance of fish populations is intimately associated with the ability of individuals within a population to reproduce. Reproduction is thus generally considered to be the most critical life function affected by environmental contamination. From a regulatory perspective, the issue of potential contaminant-related effects on fish reproduction from the Kingston fly ash spill has particular significance because the growth and propagation of fish and other aquatic life is a specific classified use of the affected river systems. To address the potential effects of fly ash from the Kingston spill on the reproductive health of exposed fish populations, ORNL has undertaken a series of studies in collaboration with TVA that include: (1) a combined field study of metal bioaccumulation in ovaries and other fish tissues (Adams and others 2012) and the reproductive condition of sentinel fish species in reaches of the Emory and Clinch Rivers affected by the fly ash spill (the current report); (2) laboratory tests of the potential toxicity of fly ash from the spill area on fish embryonic and larval development (Greeley and others 2012); (3) additional laboratory experimentation focused on the potential effects of long-term exposures to fly ash on fish survival and reproductive competence (unpublished); and (4) a combined field and laboratory study examining the in vitro developmental success of embryos and larvae obtained from fish exposed in vivo for over two years to fly ash in the Emory and Clinch Rivers (unpublished). The current report focuses on the reproductive condition of adult female fish in reaches of the Emory and Clinch Rivers influenced by the fly ash spill at the beginning of the spring 2009 breeding season - the first breeding season immediately following the fly ash release - and during the subsequent spring 2010 breeding season. Data generated from this and related reproductive/early life stage studies provide direct input to ecological risk assessment efforts and complement and support other phases of the overall biomonitoring program associated with the fly ash spill.

01 COAL, LIGNITE, AND PEAT↗