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At least 1,171 records · Page 65

Large-𝑁 SU(4) Schwinger boson theory for coupled-dimer antiferromagnets

Here, we develop a systematic large-𝑁 expansion based on the Schwinger boson representation of SU(4) coherent states of dimers for the paradigmatic spin-1/2 bilayer square lattice Heisenberg antiferromagnet. This system exhibits a quantum phase transition between a quantum paramagnetic state and a Néel order state, driven by the coupling constant 𝑔 = 𝐽′/𝐽, which is defined as the ratio between the interdimer 𝐽′ and intradimer 𝐽 exchange interactions. We demonstrate that this approach accurately describes static and dynamic properties on both sides of the quantum phase transition. The critical coupling constant 𝑔 𝑐 ≈ 0.42 and the dynamic spin structure factor reproduce quantum Monte Carlo results with high precision. Notably, the 1/𝑁 corrections reveal the longitudinal mode of the magnetically ordered phase along with the overdamping caused by its decay into the two-magnon continuum. The present large-𝑁 SU(4) Schwinger boson theory can be extended to more general cases of quantum paramagnets that undergo a quantum phase transition into magnetically ordered states.

Schwinger boson method↗

phosaa14SB and phosaa19SB: Updated Amber Force Field Parameters for Phosphorylated Amino Acids

Phosphorylated amino acids are involved in many cell regulatory networks; proteins containing these post-translational modifications are widely studied both experimentally and computationally. Simulations are used to investigate a wide range of structural and dynamic properties of biomolecules, such as ligand binding, enzyme-reaction mechanisms, and protein folding. However, the development of force field parameters for the simulation of proteins containing phosphorylated amino acids using the Amber program has not kept pace with the development of parameters for standard amino acids, and it is challenging to model these modified amino acids with accuracy comparable to proteins containing only standard amino acids. In particular, the popular ff14SB and ff19SB models do not contain parameters for phosphorylated amino acids. Here, the dihedral parameters for the side chains of the most common phosphorylated amino acids are trained against reference data from QM calculations adopting the ff14SB approach, followed by validation against experimental data. Finally, library files and corresponding parameter files are provided, with versions that are compatible with both ff14SB and ff19SB.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

Twist-Angle-Dependent Ultrafast Charge Transfer in MoS 2 -Graphene van der Waals Heterostructures

Vertically stacked transition metal dichalcogenide-graphene heterostructures provide a platform for novel optoelectronic applications with high photoresponse speeds. Photoinduced nonequilibrium carrier and lattice dynamics in such heterostructures underlie these applications but have not been understood. In particular, the dependence of these photoresponses on the twist angle, a key tuning parameter, remains elusive. Here, using ultrafast electron diffraction, we report the simultaneous visualization of charge transfer and electron–phonon coupling in MoS 2 -graphene heterostructures with different stacking configurations. We find that the charge transfer timescale from MoS 2 to graphene varies strongly with twist angle, becoming faster for smaller twist angles, and show that the relaxation timescale is significantly shorter in a heterostructure as compared to a monolayer. These findings illustrate that twist angle constitutes an additional tuning knob for interlayer charge transfer in heterobilayers and deepen our understanding of fundamental photophysical processes in heterostructures, of importance for future applications in optoelectronics and light harvesting.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

The DECam MAGIC Survey: Investigating the Jet Stellar Stream with Photometric Metallicities

Stellar streams are dynamically fragile structures formed by the tidal disruption of dwarf galaxies and stellar clusters. These objects are valuable tracers of the gravitational potential and accretion history of the Milky Way, and are key probes for the presence and interactions of starless dark matter subhalos. The Jet stream is a $\sim 30^\circ$-long stellar stream that is situated at 30.4 kpc and originates from a disrupted globular cluster. It consists of metal-poor stars that follow a retrograde orbit, reducing the impulse imparted from the Milky Way bar and making it especially sensitive to gravitational perturbations from dark matter subhalos. This paper investigates the known extent of the Jet stream by leveraging photometric metallicities derived from a narrowband filter centered on the Ca II H&K lines at $\sim$3950A on the Dark Energy Camera (DECam), as part of the Mapping the Ancient Galaxy in CaHK (MAGIC) survey. The wide field-of-view of DECam enables the efficient derivation of photometric metallicities for stars across the full extent of the stream, allowing for a metallicity-based selection to identify likely members. We demonstrate the efficacy of photometric metallicities in isolating stream members when used with Gaia DR3 proper motions, identifying a sample of 213 candidate Jet stream member stars. This then allows for the study of stream morphology, through which we identify a clear fanning of the stream toward the end farther from the Milky Way bar. We provide a list of candidate members, enabling spectroscopic follow-up of the Jet stream to facilitate further studies of its dynamics.

Do, Ha Q. [Chicago U., Astron. Astrophys. Ctr.] (O↗

Network analysis uncovers the communication structure of SARS-CoV-2 spike protein identifying sites for immunogen design

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has triggered myriad efforts to understand the structure and dynamics of this complex pathogen. The spike glycoprotein of SARS-CoV-2 is a significant target for immunogens as it is the means by which the virus enters human cells, while simultaneously sporting mutations responsible for immune escape. These functional and escape processes are regulated by complex molecular-level interactions. Our study presents quantitative insights on domain and residue contributions to allosteric communication, immune evasion, and local- and global-level control of functions through the derivation of a weighted graph representation from all-atom MD simulations. Focusing on the ancestral form and the D614G-variant, we provide evidence of the utility of our approach by guiding the selection of a mutation that alters the spike’s stability. Taken together, the network approach serves as a valuable tool to evaluate communication “hot-spots” in proteins to guide design of stable immunogens.

60 APPLIED LIFE SCIENCES↗

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗

Bayesian-based response expansion and uncertainty quantification using sparse measurement sets

Systems subjected to dynamic loads often require monitoring of their vibrational response, but limitations on the total number and placement of the measurement sensors can hinder the data-collection process. Here, we present an indirect approach to estimate a system’s full-field dynamic response, including all uninstrumented locations, using response measurements from sensors sparsely located on the system. This approach relies on Bayesian inference that utilizes a system model to estimate the full-field response and quantify the uncertainty in these estimates. By casting the estimation problem in the frequency domain, this approach utilizes the modal frequency response functions as a natural, frequency-dependent weighting scheme for the system mode shapes to perform the expansion. This frequency-dependent weighting scheme enables an accurate expansion, even with highly correlated mode shapes that may arise from spatial aliasing due to the limited number of sensors, provided these correlated modes do not have natural frequencies that are closely spaced. Furthermore, the inherent regularization mechanism that arises in this Bayesian-based procedure enables the utilization of the full set of system mode shapes for the expansion, rather than any reduced subset. This approach can produce estimates when considering a single realization of the measured responses, and with some modification, it can also produce estimates for power spectral density matrices measured from many realizations of the responses from statistically stationary random processes. A simply supported beam provides an initial numerical validation, and a cylindrical test article excited by acoustic loads in a reverberation chamber provides experimental validation.

42 ENGINEERING↗

Reproducibility of protein x-ray diffuse scattering and potential utility for modeling atomic displacement parameters

Protein structure and dynamics can be probed using x-ray crystallography. Whereas the Bragg peaks are only sensitive to the average unit-cell electron density, the signal between the Bragg peaks—diffuse scattering—is sensitive to spatial correlations in electron-density variations. Although diffuse scattering contains valuable information about protein dynamics, the diffuse signal is more difficult to isolate from the background compared to the Bragg signal, and the reproducibility of diffuse signal is not yet well understood. We present a systematic study of the reproducibility of diffuse scattering from isocyanide hydratase in three different protein forms. Both replicate diffuse datasets and datasets obtained from different mutants were similar in pairwise comparisons (Pearson correlation coefficient ≥0.8). The data were processed in a manner inspired by previously published methods using custom software with modular design, enabling us to perform an analysis of various data processing choices to determine how to obtain the highest quality data as assessed using unbiased measures of symmetry and reproducibility. The diffuse data were then used to characterize atomic mobility using a liquid-like motions (LLM) model. This characterization was able to discriminate between distinct anisotropic atomic displacement parameter (ADP) models arising from different anisotropic scaling choices that agreed comparably with the Bragg data. Our results emphasize the importance of data reproducibility as a model-free measure of diffuse data quality, illustrate the ability of LLM analysis of diffuse scattering to select among alternative ADP models, and offer insights into the design of successful diffuse scattering experiments.

59 BASIC BIOLOGICAL SCIENCES↗

Nanotubes Growth by Self-Assembly of DNA Strands at Room Temperature

Artificial biomolecular nanotubes are a promising approach to building materials mimicking the capacity of the cellular cytoskeleton to grow and self-organize dynamically. Nucleic acid nanotechnology has demonstrated a variety of self-assembling nanotubes with programmable, robust features and morphological similarities to actual cytoskeleton components. However, their production typically requires thermal annealing, which not only poses a general constraint on their potential applications but is also incompatible with physiological conditions. Here, we demonstrate that DNA nanotubes can self-assemble from a simple mixture of five short DNA strands at constant room temperature, growing for extended periods of time in bulk conditions as well as under confinement. Assembly is achieved using a monovalent salt buffer, which ensures a faithful nanoscale arrangement and avoids nanotube aggregation. We observe the formation of individual nanotubes up to 20 days with a diameter of 22 ± 4 nm and length of several tens of micrometers. We finally encapsulate the strands in microsized compartments, such as water-in-oil microdroplets and giant unilamellar vesicles serving as simple cell models. Notably, nanotubes not only isothermally self-assemble directly inside the microcompartments but also self-organize into dynamic higher-order structures resembling rings and dynamic networks. Our study provides an advantageous method for in situ assembly of programmable biomolecular scaffolds and materials using synthetic DNA strands without requirements of thermal treatment.

Chemistry↗

Active motion of multiphase oil droplets: emergent dynamics of squirmers with evolving internal structure

Synthetic soft matter systems, when driven beyond equilibrium by active processes, offer the potential to achieve dynamical states and functions of a complexity found in living matter. Emulsions offer the basis of a simple yet versatile system for identification of the physicochemical principles underlying active soft matter, but how multiple internal phases within emulsion droplets (e.g., Janus morphologies) organize to impact emergent dynamics is not understood. Here, we create multiphase oil droplets with ultralow interfacial tensions but distinct viscosities, and drive them into motion in aqueous micellar solutions. Preferential solubilization of select components of the oil both drives the droplet motion and yields a progression of internal phase morphological states with distinct symmetries. In this work, we find the active droplets to exhibit five dynamical states during morphogenesis. By quantifying microscopic flow fields, we show that it is possible to map the diverse droplet behaviors to squirmer models of spherical microswimmers in Stokes flow, thus showing that multiphase droplets offer the basis of a versatile platform with which to study and engineer the hydrodynamics of microswimmers.

36 MATERIALS SCIENCE↗

Multimodal Characterization of Crystal Structure and Formation in Rubrene Thin Films Reveals Erasure of Orientational Discontinuities

Abstract Multimodal multiscale characterization provide opportunities to study organic semiconducting thin films with multiple length scales, across multiple platforms, to elucidate crystallization mechanisms of the various microstructures that impact functionality. With polarized scanning transmission X‐ray and 4D‐scanning transmission electron microscopy, hybrid crystalline structures in rubrene thin films in which large crystalline domains surround a common nucleus and transition to a spherulite morphology at larger radii is observed. These high‐resolution techniques reveal how azimuthal orientational discontinuities at smaller radii are erased as spherulite morphology takes hold. In situ crystallization in the films with optical microscopy is also captured, discovering the importance of considering the initial temperature increase of a film during thermal annealing over the crystallization timescale. This kinetic information of the radial crystallization rate and of corresponding film heating kinetics is used to estimate the temperature at which the larger crystalline regions transition into a spherulite. By combining the results obtained from the different characterization modes, it is learned that thermal conditions can sensitively affect the crystallization of rubrene and other organic thin films. The observations suggest opportunities for more complex temperature‐dependent processing to maximize hybrid structures’ functionality in organic thin films and demonstrate that multimodal studies deepen the understanding of structure‐function dynamics.

Tan, Jenna A.↗

Domain Nucleation and Growth in an Epitaxially Grown Wurtzite Ferroelectric

Ferroelectric domain nucleation and growth in epitaxial (Al, B, Sc)N films grown on n-GaN substrates are explored using a combination of ferroelectric property measurements and scanning transmission electron microscopy, including novel in situ switching studies. The films are electrically switched to nitrogen-polar (N-polar) and metal-polar (M-polar) configurations, attaining a remanent polarization of 120 µC cm −2 with coercive fields of ≈6 MV cm −1 . In the initial switching cycle, the ferroelectric domains nucleate near the bottom n-GaN electrode and develop domain walls with zigzag morphologies, while residual “dead layers” that do not switch from the as-deposited orientation persist at the top and bottom electrodes. The in situ microscopy experiments reveal that domain walls propagate fastest in the lateral direction, parallel to the electrode/film interface. These findings provide insights into the domain dynamics and structural evolution of wurtzite ferroelectrics, offering implications for next-generation electronic devices.

36 MATERIALS SCIENCE↗

Solvent-Mediated Formation of Quasi-2D Dion-Jacobson Phases on 3D Perovskites for Inverted Solar Cells Over 23% Efficiency

2D-on-3D (2D/3D) perovskite heterostructures present a promising strategy to realize efficient and stable photovoltaics. However, their applicability in inverted solar cells is limited due to the quantum confinement of the 2D-layer and solvent incompatibilities that disrupt the underlying 3D layer, hampering electron transport at the 2D/3D interface. Herein, solvent-dependent formation dynamics and structural evolution of 2D/3D heterostructures are investigated via in situ X-ray scattering. In this study, it is revealed that solvent interaction with the 3D surface determines the formation sequence and spatial distribution of quasi-2D phases with n = 2–4. Isopropanol (IPA) reconstructs the perovskite into a PbI 2 -rich surface, forming a strata with smaller n first, followed by a thinner substratum of larger n. In contrast, 2,2,2-Trifluoroethanol (TFE) preserves the 3D surface, promoting the formation of uniformly distributed larger n domains first, and smaller n last. Leveraging these insights, Dion–Jacobson perovskites are used with superior charge transport properties and structural robustness to fabricate 2D/3D heterostructures dominated by n ≥ 3 and engineer a favorable energy landscape for electron tunneling. Inverted solar cells based on 3-Aminomethylpyridine and TFE achieve a champion efficiency of 23.60%, with V oc and FF of 1.19 V and 84.5%, respectively, and superior stabilities with t 94 of 960 h under thermal stress.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Influence of TMAO as co-solvent on the gelation of silica-PNIPAm core-shell nanogels at intermediate volume fractions

We study the structure and dynamics of poly(N-isopropylacrylamide) (PNIPAm) core-shell nanogels dispersed in aqueous trimethylamine N-oxide (TMAO) solutions by means of smallangle X-ray scattering and X-ray photon correlation spectroscopy (XPCS). Upon increasing the temperature above the lower critical solution temperature of PNIPAm at 33°C, a colloidal gel is formed as identified by an increase of I(q) at small q as well as a slowing down of sample dynamics by various orders of magnitude. With increasing TMAO concentration the gelation transition shifts linearly to lower temperatures. Above a TMAO concentration of approximately 0.40 mol/L corresponding to a 1:1 ratio of TMAO and NIPAm groups, collapsed PNIPAm states are found for all temperatures without any gelation transition. This suggests that reduction of PNIPAm-water hydrogen bonds due to the presence of TMAO results in a stabilisation of the collapsed PNIPAm state and suppresses gelation of the nanogel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Amphilic Water-Lean Carbon Capture Solvent Wetting Behavior through Decomposition by Stainless-Steel Interfaces

In this work, we report on a combined experimental and theoretical study of the wetting and reactivity of water-lean carbon capture solvents on the surface of common column packing materials. Paradoxically, we find that these solvents are equally able to wet hydrophobic and hydrophilic surfaces. The solvents are amphiphilic and are able to adapt to any interfacial environment due to their inherent heterogeneous molecular structure. Ab initio molecular dynamics indicates that these structures enable the formation of a strong adlayer on the surface of hydrophilic surfaces like oxidized steel which promotes solvent decomposition akin to hydrolysis from surface oxides and hydroxides. This decomposition passivates the surface, making it effectively hydrophobic, and the decomposed solvent promotes leaching of the iron into the bulk fluid. This study links the wetting behavior to the observed corrosion of the steels via decomposition of solvent at steel interfaces. The overall affect is strongly dependent on the chemical composition of the solvent, in that amines are stable, whereas imines and alcohols are not. We also observed that plastic packing shows little to no solvent degradation, but an equal degree of wetting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Behavioral patterns of bats at a wind turbine confirm seasonality of fatality risk

Abstract Bat fatalities at wind energy facilities in North America are predominantly comprised of migratory, tree‐dependent species, but it is unclear why these bats are at higher risk. Factors influencing bat susceptibility to wind turbines might be revealed by temporal patterns in their behaviors around these dynamic landscape structures. In northern temperate zones, fatalities occur mostly from July through October, but whether this reflects seasonally variable behaviors, passage of migrants, or some combination of factors remains unknown. In this study, we examined video imagery spanning one year in the state of Colorado in the United States, to characterize patterns of seasonal and nightly variability in bat behavior at a wind turbine. We detected bats on 177 of 306 nights representing approximately 3,800 hr of video and > 2,000 discrete bat events. We observed bats approaching the turbine throughout the night across all months during which bats were observed. Two distinct seasonal peaks of bat activity occurred in July and September, representing 30% and 42% increases in discrete bat events from the preceding months June and August, respectively. Bats exhibited behaviors around the turbine that increased in both diversity and duration in July and September. The peaks in bat events were reflected in chasing and turbine approach behaviors. Many of the bat events involved multiple approaches to the turbine, including when bats were displaced through the air by moving blades. The seasonal and nightly patterns we observed were consistent with the possibility that wind turbines invoke investigative behaviors in bats in late summer and autumn coincident with migration and that bats may return and fly close to wind turbines even after experiencing potentially disruptive stimuli like moving blades. Our results point to the need for a deeper understanding of the seasonality, drivers, and characteristics of bat movement across spatial scales.

17 WIND ENERGY↗