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At least 1,495 records · Page 83

Density functional thermodynamic description of spin, phonon and displacement degrees of freedom in antiferromagnetic-to-paramagnetic phase transition in YNiO 3

This work herein demonstrates a direct density functional description of the finite-temperature thermodynamic properties of solids exhibiting phase transitions through positional and spin symmetry breaking degrees of freedom. A classic example addressed here is the rare-earth (R) nickelates RNiO 3 where the ground state is characterized by crystallographic and magnetic (e.g., antiferromagnetic) long-range order (LRO), whereas the higher temperature paramagnetic phase manifests a range of local spin and positional symmetry breaking motifs with short-range order (SRO). Unlike time-dependent simulations of spin and positional degrees of freedom, in the present work, phases are described via a superposition of static configurations constructed by populating a periodic base lattice supercell allowing for the formation of energy lowing distribution of positional and spin local motifs. The thermal populations of the configurations in such a superposition phase are obtained from the energy-minimized Density Functional Theory (DFT)-calculated partition functions at different temperatures. This approach offers flexible inclusion of different physical contributions to the free energy, such as elastic, electronic and phonon free energies, all obtained from the same underlying DFT total energy calculations of periodic structures. The thermodynamic and magnetic properties of both LRO and SRO crystallographic and spin phases, including antiferromagnetic (AFM) to paramagnetic (PM) Néel phase transition in YNiO3 are studied. Including spin and phonon contributions, we find a DFT-calculated Néel temperature to be 144 K in satisfactory agreement with the experimental value of 145 K; whereas omitting the phonon contribution, one obtains a Néel temperature of 81 K. We present phonon contributions to the DFT-calculated temperature-dependent SRO, heat capacities, and the polymorphous distribution of nonzero local magnetic moments in the PM phase. This approach thus extends to finite temperatures the symmetry-broken DFT description of both the AFM and PM phases, demonstrating that a thermodynamic superposition approach based on symmetry broken configurations evaluated by a mean-field like DFT is sufficient to obtain a consistent description of the thermal physics of the AFM, PM phases and their interconversion in 3d oxides illustrated by YNiO 3 .

36 MATERIALS SCIENCE↗

High-purity germanium semiconductor modeling in the detector response function toolkit

In this study, we have extended the detector response function toolkit (DRiFT) to provide modeling capabilities of semiconductor sensors. DRiFT provides realistic nuclear instrumentation response by post-processing Monte-Carlo N-particle (MCNP®) radiation transport outputs. MCNP® is capable of modeling radiation transport in complex environments, but has limited detector physics and readout electronics modeling capabilities. Semiconductor detector response can be calculated with a high-fidelity for a flexible range of environments by utilizing MCNP® to simulate radiation interactions inside of detector volumes, and then using DRiFT to model charge transport and signal formation in the semiconductor, as well as the readout electronics. DRiFT models charge transport in the semiconductor, the preamplifier, shaping amplifier, pulse pile-up, and electronic noise to generate detector response. The semiconductor application in DRiFT can model a range of semiconductor materials, shapes, and sizes; and is demonstrated here for a large volume coaxial high-purity germanium (HPGe) detector. Here, we compare detector response functions of a coaxial HPGe detector with measurement of 60 Co, 133 Ba, and 137 Cs at varying count rates, and we conduct a parameter study to demonstrate the effect of changing parameters in the DRiFT simulation. The HPGe detector response function shows excellent agreement with measurements of difference sources with varying dead times and count rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Interpolation of computed gamma-ray detector response functions

Gamma-ray spectra measured by traditional detectors contain features that result from a combination of the effects of detector materials/geometry, the incident gamma-ray energy, and the angle of entry. The features, such as the full-energy photopeak, Compton continuum, annihilation peak, and escape peaks, are governed by simple relationships depending on incident energy and have been known for a long time. Monte Carlo computer simulations of gamma rays interacting with a detector will show these features, and with a resolution function applied, the results should look similar to real measurements. The traditional approach to creating a detector response function requires many separate simulations of monoenergetic gamma rays striking the detector. This paper presents a new approach to developing computed detector response functions. The new approach involves a much smaller number of monoenergetic gamma-ray simulations and uses interpolation to quickly generate the responses of gamma rays that were not simulated. During the interpolation process, the underlying physics equations are used to accurately compute the response of a given energy gamma ray from the small set of simulations. Such work enables accelerated generation of synthetic radiation detector data.

Detector response↗

Plant-microbial interplay for organic nitrogen mediated by functional specificity of root compartments

The organic form of nitrogen (N) is a critical intermediate in mutualistic and competitive root-microbial interactions, mediated by extracellular enzymes. Visualization of the hotspots of organic N and proteolytic activity might be valuable for revealing root functional specificity in N acquisition and transformation at the level of individual roots and compartments. For the first time, we used time-lapse amino-mapping and zymography to co-localize and map the spatial distribution of amino-N and leucine aminopeptidase (LAP) activity in the soil and different root parts of maize (Zea mays L.). Amino-N distribution was mainly associated with seminal roots and root tips, where it overlapped with LAP activity hotspots. In the lateral roots and bulk soil, however, LAP activity was decoupled from amino-N. Distinct functional traits revealed themselves as the highest amino-N content and LAP activity in seminal root tips and as the largest relative extent of the rhizosphere in lateral root tips. Co-localized amino-N and LAP activities highlighted different nutrient acquisition strategies mediated by root-microbe interactions, depending on the root compartment. Seminal roots and their tips appeared to adopt mutualistic strategies, potentially attracting root-associated microorganisms through releasing oligo- and polypeptides. In contrast, lateral roots, with amino-N detected only at their tips, demonstrated stronger N competition, relying on the enzyme activity of the rhizosphere microbial community for N acquisition. These insights emphasized the role of root functional specialization in shaping plant-microbe interactions, offering pathways to enhance nutrient use efficiency.

Maize (Zea mays L.)↗

Revisiting diffusion-based moisture functions: why do they fail?

Microbial activities in soil are controlled by the balance between physical and biological mechanisms that are currently implied by soil moisture-respiration relationships, but not explicitly represented. Diffusion based moisture functions focus on physical controls, while substrate kinetics based models primarily address biological drivers. How to harmonize these two types of models for robust predictions of soil respiration and other processes has not been addressed. Here we derived a generalizable analytical solution of diffusion-limited nonlinear microbial uptake kinetics, in which microbial metabolic rates were governed by both physical and biological drivers via substrate diffusion and microbial affinity. We proposed a soil trait concept to integrate both physical and biological perspectives into one unified function, and tested it using both laboratory and field based observations from a variety of soils. This approach provides a tractable and scalable approach that incorporates soil heterogeneity and functional complexity in macroscopic model descriptions.

59 BASIC BIOLOGICAL SCIENCES↗

Neurons die with heightened but functional macro- and chaperone mediated autophagy upon increased amyloid-ß induced toxicity with region-specific protection in prolonged intermittent fasting

Highlights: • Macroautophagy (MA) is strongly engaged upon APP overexpression and remains high over time. • APP colocalization with macroautophagy components remains increased until late, promoting continuous recruitment to the autophagy machinery. • Robust chaperone-mediated autophagy (CMA) engagement is observed in late APP overexpression. • Macroautophagic flux during APP overexpression is preserved, even at late time points, suggesting functional autophagy in the face of apoptosis onset. • Macroautophagy impairment increases markers of amyloidogenesis and further exacerbates the onset of apoptotic cell death. Alzheimer's disease (AD) is a devastating neurodegenerative condition with significant socio-economic impact that is exacerbated by the rapid increase in population aging, particularly impacting already burdened health care systems of poorly resourced countries. Accumulation of the amyloid-β (Aβ) peptide, generated through amyloid precursor protein (APP) processing, manifesting in senile plaques, is a well-established neuropathological feature. Aβ plays a key role in driving synaptic dysfunction, neuronal cell loss, glial cell activation and oxidative stress associated with the pathogenesis of AD. Thus, the enhanced clearance of Aβ peptide though modulation of the mechanisms that regulate intracellular Aβ metabolism and clearance during AD progression have received major attention. Autophagy, a lysosome-based major proteolytic pathway, plays a crucial role in intracellular protein quality control and has been shown to contribute to the clearance of Aβ peptide. However, to what extent autophagy activity remains upregulated and functional in the process of increasing Aβ neurotoxicity is largely unclear. Here, we investigated the extent of neuronal toxicity in vitro by characterising autophagic flux, the expression profile of key amyloidogenic proteins, and proteins associated with prominent subtypes of the autophagy pathway to dissect the interplay between the engagement of proteolytic pathways and cell death onset in the context of APP overexpression. Moreover, we assessed the neuroprotective effects of a caloric restriction regime in vivo on the modulation of autophagy in specific brain regions. Our results reveal that autophagy is upregulated in the presence of high levels of APP and Aβ and remains heightened and functional despite concomitant apoptosis induction, suggestive of a mismatch between autophagy cargo generation and clearance capacity. These findings were confirmed when implementing a prolonged intermittent fasting (IF) intervention in a model of paraquat-induced neuronal toxicity, where markers of autophagic activity were increased, while apoptosis onset and lipid peroxidation were robustly decreased in brain regions associated with neurodegeneration. This work highlights that especially caloric restriction mimetics and controlled prolonged IF may indeed be a highly promising therapeutic strategy at all stages of AD-associated pathology progression, for a cell-inherent and cell specific augmentation of Aβ clearance through the powerful engagement of autophagy and thereby robustly contributing to neuronal protection.

60 APPLIED LIFE SCIENCES↗

Isoform-specific functions of synaptopodin-2 variants in cytoskeleton stabilization and autophagy regulation in muscle under mechanical stress

Highlights: • Muscle cells express different synaptopodin-2 isoforms with individual functions. • Reduced SYNPO2 expression results in enhanced vulnerability of myofibrils. • SYNPO2e recruites BAG3 to mechanically stressed myofibrillar areas. • SYNPO2 is an organizer and regulator of BAG3-containing proteostasis systems. • BAG3 forms functionally distinct protein complexes with different SYNPO2 isoforms. Protein homeostasis (proteostasis) in multicellular organisms depends on the maintenance of force-bearing and force-generating cellular structures. Within myofibrillar Z-discs of striated muscle, isoforms of synaptopodin-2 (SYNPO2/myopodin) act as adapter proteins that are engaged in proteostasis of the actin-crosslinking protein filamin C (FLNc) under mechanical stress. SYNPO2 directly binds F-actin, FLNc and α-actinin and thus contributes to the architectural features of the actin cytoskeleton. By its association with autophagy mediating proteins, i.e. BAG3 and VPS18, SYNPO2 is also engaged in protein quality control and helps to target mechanical unfolded and damaged FLNc for degradation. Here we show that deficiency of all SYNPO2-isoforms in myotubes leads to decreased myofibrillar stability and deregulated autophagy under mechanical stress. In addition, isoform-specific proteostasis functions were revealed. The PDZ-domain containing variant SYNPO2b and the shorter, PDZ-less isoform SYNPO2e both localize to Z-discs. Yet, SYNPO2e is less stably associated with the Z-disc than SYNPO2b, and is dynamically transferred into FLNc-containing myofibrillar lesions under mechanical stress. SYNPO2e also recruits BAG3 into these lesions via interaction with the WW domain of BAG3. Our data provide evidence for a role of myofibrillar lesions as a transient quality control compartment essential to prevent and repair contraction-induced myofibril damage in muscle and indicate an important coordinating activity for SYNPO2 therein.

60 APPLIED LIFE SCIENCES↗

Structure and Function of BorB, the Type II Thioesterase from the Borrelidin Biosynthetic Gene Cluster

α/β hydrolases make up a large and diverse protein superfamily. In natural product biosynthesis, cis-acting thioesterase α/β hydrolases can terminate biosynthetic assembly lines and release products by hydrolyzing or cyclizing the biosynthetic intermediate. Thioesterases can also act in trans, removing aberrant intermediates and restarting stalled biosynthesis. Knockout of this "editing" function leads to reduced product titers. The borrelidin biosynthetic gene cluster from Streptomyces parvulus Tü4055 contains a hitherto uncharacterized stand-alone thioesterase, borB. In this work, we demonstrate that purified BorB cleaves acyl substrates with a preference for propionate, which supports the hypothesis that it is also an editing thioesterase. The crystal structure of BorB shows a wedgelike hydrophobic substrate binding crevice that limits substrate length. To investigate the structure-function relationship, we made chimeric BorB variants using loop regions from characterized homologues with different specificities. BorB chimeras slightly reduced activity, arguing that the modified region is a not major determinant of substrate preference. Overall, the structure-function relationships described here contribute to the process of elimination for understanding thioesterase specificity and, ultimately, engineering and applying trans-acting thioesterases in biosynthetic assembly lines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design and Function of α-Helix-Rich, Heme-Binding Peptide Materials

Peptide materials often employ short peptides that self-assemble into unique nanoscale architectures and have been employed across many fields relevant to medicine and energy. A majority of peptide materials are high in beta-sheet, secondary structure content, including heme-binding peptide materials. To broaden the structural diversity of heme-binding peptide materials, a small series of peptides were synthesized to explore the design criteria required for (1) folding into an alpha-helix structure, (2) assembling into a nanoscale material, (3) binding heme, and (4) demonstrating functions similar to that of heme proteins. One peptide was identified to meet all four criteria, including the heme protein function of CO binding and its microsecond-to-millisecond recombination rates, as measured by transient absorption spectroscopy. In conclusion, implications of new design criteria and peptide material function through heme incorporation are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Terminal Carboxyl Groups on the Structure and Reactivity of Functionalized m-Carboranethiolate Self-Assembled Monolayers

The structure and function of self-assembled monolayers (SAMs) at the nanoscale are determined by the steric and electronic effects of their building blocks. Carboranethiol molecules form pristine monolayers that provide tunable two-dimensional systems to probe lateral and interfacial interactions. Additional ω-functionality, such as carboxyl groups, can be introduced to change the properties of the exposed surfaces. Here, two geometrically similar isomeric m-carborane analogues of m-mercaptobenzoic acid, 1-COOH-7-SH-1,7-C 2 B 10 H 10 and racem-1-COOH-9-SH-1,7-C 2 B 10 H 10 , are characterized and their SAMs on Au{111} are examined. The latter isomer belongs to the rare group of chiral cage molecules and becomes, to our knowledge, the first example assembled on Au{111}. Although different in symmetry, molecules of both isomers assemble into similar hexagonal surface patterns. The nearest-neighbor spacing of 8.4 ± 0.4 Å is larger than that of non-carboxylated isomers, consistent with the increased steric demands of the carboxyl groups. Computational modeling reproduced this spacing and suggests a tilt relative to the surface normal. However, tilt domains are not observed experimentally, suggesting the presence of strong lateral interactions. Analyses of the influence of the functional groups through the pseudo-aromatic m-carborane skeleton showed that the thiol group attached to either carbon or boron atoms increases the carboxyl group acidity in solution. In contrast, the acidity of the exposed carboxyl group in the SAMs decreases upon surface attachment; computational analyses suggest that the driving force of this shift is the dielectric of the environment in the monolayer as a result of confined intermolecular interactions, proximity to the Au surface, and partial desolvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Design of Functional Polymers for Silica Scale Inhibition

Silica polymerization, which involves the condensation reaction of silicic acid, is a fundamental process with wide-ranging implications in biological systems, material synthesis, and scale formation. The formation of a silica-based scale poses significant technological challenges to energy-efficient operations in various industrial processes, including heat exchangers and water treatment membranes. Despite the common strategy of applying functional polymers for inhibiting silica polymerization, the underlying mechanisms of inhibition remain elusive. In this study, we synthesized a series of nitrogen-containing polymers as silica inhibitors and elucidated the role of their molecular structures in stabilizing silicic acids. Polymers with both charged amine and uncharged amide groups in their backbones exhibit superior inhibition performance, retaining up to 430 ppm of reactive silica intact for 8 h under neutral pH conditions. In contrast, monomers of these amine/amide-containing polymers as well as polymers containing only amine or amide functionalities present insignificant inhibition. Molecular dynamics simulations reveal strong binding between the deprotonated silicic acid and a polymer when the amine groups in the polymer are protonated. Notably, an extended chain conformation of the polymer is crucial to prevent proximity between the interacting monomeric silica species, thereby facilitating effective silica inhibition. Furthermore, the hydrophobic nature of alkyl segments in polymer chains disrupts the hydration shell around the polymer, resulting in enhanced binding with ionized silicic acid precursors compared to monomers. Finally, our findings provide novel mechanistic insights into the stabilization of silicic acids with functional polymers, highlighting the molecular design principles of effective inhibitors for silica polymerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis and Surface Attachment of Molecular Re(I) Complexes Supported by Functionalized Bipyridyl Ligands

Eleven 2,2'-bipyridine (bpy) ligands functionalized with attachment groups for covalent immobilization on silicon surfaces were prepared. Five of the ligands feature silatrane functional groups for attachment to metal oxide coatings on the silicon surfaces, while six contain either alkene or alkyne functional groups for attachment to hydrogen-terminated silicon surfaces. The bpy ligands were coordinated to Re(CO) 5 Cl to form complexes of the type Re(bpy)(CO) 3 Cl, which are related to known catalysts for CO 2 reduction. Six of the new complexes were characterized using X-ray crystallography. As proof of principle, four molecular Re complexes were immobilized on either a thin layer of TiO 2 on silicon or hydrogen-terminated silicon. The surface-immobilized complexes were characterized using X-ray photoelectron spectroscopy, IR spectroscopy, and cyclic voltammetry (CV) in the dark and for one representative example in the light. The CO stretching frequencies of the attached complexes were similar to those of the pure molecular complexes, but the CVs were less analogous. For two of the complexes, comparison of the electrocatalytic CO 2 reduction performance showed lower CO Faradaic efficiencies for the immobilized complexes than the same complex in solution under similar conditions. In particular, a complex containing a silatrane linked to bpy with an amide linker showed poor catalytic performance and control experiments suggest that amide linkers in conjugation with a redox-active ligand are not stable under highly reducing conditions and alkyl linkers are more stable. So a conclusion of this work is that understanding the behavior of molecular Re catalysts attached to semiconducting silicon is more complicated than related complexes, which have previously been immobilized on metallic electrodes.

14 SOLAR ENERGY↗

Binding Affinity Prediction by Pairwise Function Based on Neural Network

In this paper, we present a new approach to estimate the binding affinity from given three-dimensional poses of protein–ligand complexes. In this scheme, every protein–ligand atom pair makes an additive free-energy contribution. The sum of these pairwise contributions then gives the total binding free energy or the logarithm of the dissociation constant. The pairwise contribution is calculated by a function implemented via a neural network that takes the properties of the two atoms and their distance as input. The pairwise function is trained using a portion of the PDBbind 2018 data set. The model achieves good accuracy for affinity predictions when evaluated with PDBbind 2018 and with the CASF-2016 benchmark, comparing favorably to many scoring functions such as that of AutoDock Vina. The framework here may be extended to incorporate other factors to further improve its accuracy and power.

59 BASIC BIOLOGICAL SCIENCES↗

Atom Equivalent Energies for the Rapid Estimation of the Heat of Formation of Explosive Molecules from Density Functional Tight Binding Theory

Atom equivalent energies have been derived from which the gas-phase heat of formation of explosive molecules can be estimated from fast, semiempirical density functional tight binding total energy calculations. The root-mean-square deviation and maximum deviation of the heats of formation from the experimental values for the set of 45 energetic molecules compiled by Byrd and Rice [ J. Phys. Chem. A, 2006, 110, 1005–1013] are 10.4 and 25.5 kcal/mol, respectively, using 4 atom equivalent energies and 7.4 and 15.0 kcal/mol, respectively, using 7 atom equivalent energies. These errors are around a factor of 2–3 larger than those obtained from density functional theory calculations but are smaller than those obtained from other semiempirical electronic structure methods. Heats of formation calculated with density functional tight binding theory using the 4 and 7 atom equivalent energies, the Byrd and Rice scheme, and the atom pair contribution method for a new set of 531 energetic molecules that contain only carbon, hydrogen, nitrogen, and oxygen are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Real-time coupled-cluster approach for the cumulant Green's function

Green’s function methods within many-body perturbation theory provide a general framework for treating electronic correlations in excited states. Here we investigate the cumulant form of the one-electron Green’s function based on the coupled-cluster equation of motion approach in an extension of our previous study. The approach yields a non-perturbative expression for the cumulant in terms of the solution to a set of coupled first order, non-linear differential equations. The method thereby adds non-linear corrections to traditional cumulant methods linear in the self energy. The approach is applied to the core-hole Green’s function and illustrated for a number of small molecular systems. For these systems we find that the non-linear contributions lead to significant improvements both for quasiparticle properties such as core-level binding energies, as well as the satellites corresponding to inelastic losses observed in photoemission spectra.

Vila, Fernando D.↗

Random Phase Approximation Correlation Energy Using Real-Space Density Functional Perturbation Theory

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn–Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic-scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method’s accuracy by comparing with plane-wave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 s on 4608 processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗

Real-Space Quantification of Exciton Localization in Acene Crystals Using Wannier Function Decomposition

Here, we introduce the Wannier function decomposition of excitons (WFDX) method to quantify exciton localization in solids within the ab initio Bethe-Salpeter equation framework. By decomposing each Bloch exciton wave function into products of single-particle electron and hole maximally localized Wannier functions, this real-space approach provides well-defined orbital- and spatial-resolved measures of both Frenkel and charge-transfer excitons at low computational cost. We apply WFDX to excitons in acene crystals, quantifying how the number of rings, the exciton spin state, and the center-of-mass momentum affect spatial localization. Additionally, we show how this real-space representation reflects structural nonsymmorphic symmetries that are hidden in standard reciprocal-space descriptions. We demonstrate how the WFDX framework can be used to efficiently interpolate exciton expansion coefficients in reciprocal-space and outline how it may facilitate evaluation of observables involving position operators, highlighting its potential as a general tool for both analyzing and computing excitonic properties in solids.

Tao, Zui [University of California, Berkeley, CA (↗