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At least 667 records · Page 37

Multifunctional fiber-reinforced composites for passive sensing and energy harvesting with enhanced mechanical performance

Fiber-reinforced polymer composites (FRPCs) are valid alternatives to metals, especially in the aerospace industry, for their superior strength-to-weight ratio. FRPCs are generally manufactured by stacking layers of fibers and infusing them with epoxy-based adhesives to result in laminates. Such layer-by-layer structure often ensues a poor interlaminar property of the composites. Additionally, FRPCs can sustain complex damage modes because of their inherent anisotropic characteristics. For example, delamination can occur due to low-velocity impact at a subsurface level, which can result in premature catastrophic failures if undetected. Thus, structural monitoring is crucial to identify such damage. Point-based sensors (e.g., strain gauges, accelerometers, among many) can be embedded in the FRPCs for structural monitoring. However, their electrical power demand often embroils their usage. Therefore, the main objective of this research is to design and implement multifunctional composites that can simultaneously perform passive sensing and energy harvesting while exhibiting better mechanical performance. Previous research efforts have demonstrated that a continuous feed-through deposition of functional materials on fiber surfaces simultaneously enhanced the mechanical and sensing properties of the FRPCs. This study explores a similar approach to encode passive sensing and energy harvesting properties in the FRPCs by integrating ferroelectric microparticles on the fiber surfaces. Upon ensuring their superior interlaminar shear strength, sensing and energy harvesting properties were characterized through experimental studies. The outcome is a multifunctional composite fabricated by coating the fibers with functional microparticles through a high throughput, scalable, and low-cost approach that enables passive sensing, energy harvesting, and improved mechanical performance.

Gupta, Sumit↗

Laser-Induced Enhancement of Acoustic Mode Quality Factor Revealed by Correlated Single-Particle Optical and Electron Microscopy

Acoustic modes in plasmonic nanostructures provide fundamental insights into their optomechanical behavior at the nanoscale, enabling emerging applications in plasmon-enhanced optomechanics, ultrasensitive sensing, and nanoscale energy transduction. Here we explore the modulation of acoustic phonon dynamics in lithographically fabricated gold nanodisks via laser-induced photothermal annealing. Using a correlated approach that utilizes both single-particle transient extinction spectroscopy and advanced electron microscopy, we directly link nanoscale structural transformations to changes in mechanical properties as probed through the coherence of the excited acoustic modes. Specifically, ultrafast pump–probe microscopy reveals an enhancement in the acoustic mode quality factor of annealed gold nanodisks, indicative of reduced damping and improved vibrational coherence. Structural characterization via scanning electron microscopy and electron backscatter diffraction confirms that photoinduced annealing results in smoother surface morphology and overall enhanced crystallinity. The improved crystalline order reduces defect and crystal boundary scattering, which we suggest as the reason underlying the lower quality factor before annealing. Furthermore, these findings demonstrate that targeted structural engineering at the nanoscale offers a powerful strategy for optimizing the optomechanical performance of plasmonic nanostructures, with broad implications for the design of next-generation nanophotonic and optomechanical systems.

Annealing (metallurgy)↗

Origin of Disorder Tolerance in Piezoelectric Materials and Design of Polar Systems

Current high-performing piezoelectric materials are dominated by perovskites that rely on soft optical phonon modes stabilized by disorder near a morphotropic phase boundary and a unique resilience of the polar response to that disorder. To identify structural families with similar resilience, in this study we develop a first-principles sensitivity analysis approach to determine the effect of disorder on the piezoelectric response for structures in the Materials Project database. In well-known piezoelectric systems, the lattice dynamics, rather than internal strain or dielectric, control the polar response. Additionally, multiple stable optical phonon modes are found to contribute to the piezoelectric response, providing a fingerprint for disorder tolerance. A multiple-phonon mode criterion is used to evaluate candidate materials for disorder-tolerant piezoelectric prototype systems. Five promising structures are altered through chemical substitution, generating potential MPB end points with large piezoelectric responses beyond perovskites including Akermanite Sr 2 x Ca 2 – 2 x CoSi 2 O 7 , which exhibits a nearly 20% increase in response at the 50% composition.

36 MATERIALS SCIENCE↗

Vibrational metrics for the evaluation of internal conditions in a scaled nuclear dry storage cask

In many countries, permanent repositories for high burnup spent nuclear fuel assemblies have yet to be established. As a result, much of the spent fuel from nuclear reactors is contained within dry storage casks, with many being beyond their designed service life. The assessment of the internal structural integrity of these casks and the fuel assemblies contained therein is of critical importance for both extended storage and transport to permanent repositories. The large size, structural complexity, and inaccessibility of the interior of the casks make this task challenging. To address these difficulties, a 1:6 scaled model based closely on the design of a Transnuclear (TN-32) dry storage cask was fabricated to facilitate controlled studies of these structures in the laboratory. Vibrational spectroscopy was used to evaluate the state of the cargo and internal structures within the cask utilizing only measurements on the outer surface. Using modes identified through Finite Element modeling corresponding to those previously measured on a full-scale TN-32 cask, we report on the development of amplitude- and phase-based metrics that are sensitive to internal conditions in the lab cask. Steel rod bundles and steel shot were used as surrogates for intact and damaged fuel assemblies, and various internal configurations of these materials were investigated. Finally, the metrics were based on acquired spectra involving the (1, 2) global bending mode and the (2, 1) radial-with-shearing mode. The results show that the metrics are sensitive to the condition of a single assembly and have some ability to determine the locations of damaged and empty slots.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sub-THz passive detector performance evaluation with RadiaBeam photoinjector

Wakefield accelerators, based on THz and mm-wave structures, promise to reach the highest energies in record small footprints. However, operation at such frequencies is associated with strong generation of dipole modes that can destroy the beams, which requires controlling the electron beam position at the micron scale. The existing conventional techniques for electron beam position monitoring are not applicable for sub-THz structures due to the space constraints. Here, on the other hand, if dipole modes amplitudes can be measured precisely at different planes, one can derive beam position relative to the central axis. For such a technique a reliable and cost-effective sensor capable of operating in high repletion rate regime is required. In this paper we review the experimental evaluation of a passive sensor candidate for such applications using RadiaBeam 4.5 MeV photoinjector.

Accelerator↗

Neuroevolutionary Learning of Particles and Protocols for Self-Assembly

Within simulations of molecules deposited on a surface we show that neuroevolutionary learning can design particles and time-dependent protocols to promote self-assembly, without input from physical concepts such as thermal equilibrium or mechanical stability and without prior knowledge of candidate or competing structures. Furthermore, the learning algorithm is capable of both directed and exploratory design: it can assemble a material with a user-defined property, or search for novelty in the space of specified order parameters. In the latter mode it explores the space of what can be made, rather than the space of structures that are low in energy but not necessarily kinetically accessible.

74 ATOMIC AND MOLECULAR PHYSICS↗

Probing Distinctive Redox Mechanism in Ni-Rich Cathode Via Real-Time Quick X-Ray Absorption Spectroscopy

X-ray radiation damage on the measuring system has been a critical issue regularly for a long-time exposure to X-ray beam during the in operando characterizations, which is particularly severe when the applied X-ray energy is near the absorption edges (M, L, K, etc.) of the interest element. Here, to minimize the negative effects raised by beam radiation, we employ quick X-ray absorption spectroscopy (QXAS) to study the electrochemical reaction mechanism of a Ni-rich layered structure cathode for lithium-ion batteries. With the advanced QXAS technique, the electronic structure and local coordination environment of the transition metals (TMs) are monitored in-operando with limited radiation damage. Compared to the conventional step-mode X-ray absorption spectroscopy, the QXAS can provide more reliable oxidation state change and more detailed local structure evolutions surrounding TMs (Ni and Co) in Ni-rich layered oxides. By leveraging these advantages of QXAS, we demonstrated that the Ni dominates the electrochemical process with the Co being almost electrochemically inactive. Reversible Ni ions movement between TMs sites and Li sites is also revealed by the time-resolved QXAS technique.

25 ENERGY STORAGE↗

Neural network model of the multi-mode anomalous transport module for accelerated transport simulations

Here, a neural network version of the Multi-Mode Anomalous Transport Module, known as MMMnet, has been developed to calculate plasma turbulent diffusivities in DIII-D with a calculation time suitable for control applications. MMMnet uses a simple artificial neural network structure to predict the ion thermal, electron thermal, and toroidal momentum diffusivities while reproducing Multi-Mode Model (MMM) data with good accuracy and keeping the calculation time as a fraction of that associated with MMM. Model-based control techniques require models with fast calculation times, making many existing physics-oriented predictive codes unsuitable. The control-oriented predictive code COTSIM (Control Oriented Transport SIMulator) calculates the most significant plasma dynamics in response to the different actuators while running at a speed useful for control design. In order to achieve this calculation speed, COTSIM often relies on scaling laws and control-level models. Replacing some of these scaling laws and control-level models with neural network versions of more complex physics-level models has the potential of increasing the range of validity and the level of accuracy of COTSIM without compromising its computational speed. In this work, MMMnet is integrated into COTSIM to improve the turbulent diffusivity predictions, which will in turn improve the prediction accuracy associated with the dynamics of many plasma properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Structure and sequence evolution in the pennycress ( Thlaspi arvense ) pangenome

Eukaryotic genomes harbor many forms of variation, including nucleotide diversity and structural polymorphisms, which experience natural selection and contribute to genome evolution and biodiversity. Harnessing this variation for agriculture hinges on our ability to detect, quantify, catalog, and deploy genetic diversity. Here, we explore seven complete genomes of the emerging biofuel crop pennycress ( Thlaspi arvense ) drawn from across the species' current genetic diversity to catalog variation in genome structure and content. Across this new pangenome resource, we find contrasting evolutionary modes in different genomic zones. Gene-poor, repeat-rich pericentromeric regions experience frequent rearrangements, including repeated centromere repositioning. By contrast, conserved gene-dense chromosome arms maintain large-scale synteny across accessions even in fast-evolving NOD-like receptor immune genes, where microsynteny breaks down across species, but gene cluster positioning macrosynteny is maintained. Our findings highlight that multiple elements of the genome experience dynamic evolution that conserves functional content on the chromosome scale but allows repositioning and presence–absence variation on a local scale. This diversity is invisible to classical reference-based strategies and highlights the strength and utility of pangenomic resources. These results provide a valuable case study of rapid genomic structural evolution within a species and powerful resources for crop development in an emerging biofuel crop.

Thlaspi arvense↗

In cellulo crystallization of Trypanosoma brucei IMP dehydrogenase enables the identification of genuine co-factors

Sleeping sickness is a fatal disease caused by the protozoan parasite Trypanosoma brucei (Tb). Inosine-5’-monophosphate dehydrogenase (IMPDH) has been proposed as a potential drug target, since it maintains the balance between guanylate deoxynucleotide and ribonucleotide levels that is pivotal for the parasite. Here we report the structure of TbIMPDH at room temperature utilizing free-electron laser radiation on crystals grown in living insect cells. The 2.80 Å resolution structure reveals the presence of ATP and GMP at the canonical sites of the Bateman domains, the latter in a so far unknown coordination mode. Consistent with previously reported IMPDH complexes harboring guanosine nucleotides at the second canonical site, TbIMPDH forms a compact oligomer structure, supporting a nucleotide-controlled conformational switch that allosterically modulates the catalytic activity. The oligomeric TbIMPDH structure we present here reveals the potential of in cellulo crystallization to identify genuine allosteric co-factors from a natural reservoir of specific compounds.

36 MATERIALS SCIENCE↗

Evolution of microscopic heterogeneity and dynamics in choline chloride-based deep eutectic solvents

Deep eutectic solvents (DESs) are an emerging class of non-aqueous solvents that are potentially scalable, easy to prepare and functionalize for many applications ranging from biomass processing to energy storage technologies. Predictive understanding of the fundamental correlations between local structure and macroscopic properties is needed to exploit the large design space and tunability of DESs for specific applications. Here, we employ a range of computational and experimental techniques that span length-scales from molecular to macroscopic and timescales from picoseconds to seconds to study the evolution of structure and dynamics in model DESs, namely Glyceline and Ethaline, starting from the parent compounds. We show that systematic addition of choline chloride leads to microscopic heterogeneities that alter the primary structural relaxation in glycerol and ethylene glycol and result in new dynamic modes that are strongly correlated to the macroscopic properties of the DES formed.

36 MATERIALS SCIENCE↗

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer–particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental–theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Here, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

36 MATERIALS SCIENCE↗

New Insights into Physical Aging‐Induced Structure Evolution in Carbon Molecular Sieve Membranes

Abstract Carbon molecular sieve (CMS) membranes offer the best available combination of scalable economical processability with excellent separation performance. Physical aging of CMS membranes causes pore structure changes over time that affect CMS membrane performance. To provide fundamental insights into the structure evolution in CMS membranes during physical aging, a combined dual‐mode sorption and transport model is used in this study to characterize the diffusion coefficients of gas molecules in fresh and 7‐day vacuum aged CMS membranes. The results show physical aging of CMS membrane is primarily “diffusion related” and such aging behavior simultaneously causes ultramicropore changes in the continuous phase and Langmuir phase of CMS membrane. The new insights offered in this study suggest strategies to control the physical aging of CMS membranes and even use it as a valuable tool to tune the separation performance of CMS membranes for demanding gas separations.

Liu, Zhongyun↗

The evolution of the GAL actose utilization pathway in budding yeasts

The Leloir galactose utilization or GAL pathway of budding yeasts, including that of the baker’s yeast Saccharomyces cerevisiae and the opportunistic human pathogen Candida albicans, breaks down the sugar galactose for energy and biomass production. Here, the GAL pathway has long served as a model system for understanding how eukaryotic metabolic pathways, including their modes of regulation, evolve. More recently, the physical linkage of the structural genes GAL1, GAL7, and GAL10 in diverse budding yeast genomes has been used as a model for understanding the evolution of gene clustering. In this review, we summarize exciting recent work on three different aspects of this iconic pathway’s evolution: gene cluster organization, GAL gene regulation, and the population genetics of the GAL pathway.

59 BASIC BIOLOGICAL SCIENCES↗

Roles of D1-Glu189 and D1-Glu329 in O 2 Formation by the Water-Splitting Mn 4 Ca Cluster in Photosystem II

During the catalytic step that precedes O–O bond formation in Photosystem II, a water molecule deprotonates and moves next to the water-splitting Mn 4 Ca cluster’s O5 oxo bridge. The relocated oxygen, known as O6 or Ox, may serve as a substrate, combining with O5 to form O 2 during the final step in the catalytic cycle, or may be positioned to become a substrate during the next catalytic cycle. Recent serial femtosecond X-ray crystallographic studies show that the flexibility of D1-E189 plays a critical role in facilitating the relocation of O 6 /Ox. In this study, the D1-E189G and D1-E189S mutations were characterized with FTIR difference spectroscopy. The data show that both mutations support Mn 4 Ca cluster assembly, substantially inhibit advancement beyond the S 2 state, and alter the network of H bonds that surrounds the Mn 4 Ca cluster. Previously, the D1-E189Q, D1-E189K, and D1-E189R mutations were shown to have little impact on the activity, electron transfer rates, or spectral properties of Photosystem II. A rationale for this behavior is presented. The residue D1-E329 interacts with water molecules in the O1 water network that has been suggested recently to supply substrate during the catalytic cycle. Characterization of the D1-E329A mutant with FTIR difference spectroscopy shows that this mutation does not substantially perturb the structure of PSII or the water molecules whose O–H stretching modes change during the catalytic cycle. Furthermore, this result provides additional evidence that the water molecules whose vibrational properties change during the S 1 to S 2 transition are confined approximately to the region bounded by D1-N87, D1-N298, and D2-K317.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Discovery of Pyridopyrimidinones that Selectively Inhibit the H1047R PI3Kα Mutant Protein

The H1047R mutation of PIK3CA is highly prevalent in breast cancers and other solid tumors. Selectively targeting PI3Kα H1047R over PI3Kα WT is crucial due to the role that PI3Kα WT plays in normal cellular processes, including glucose homeostasis. Currently, only one PI3Kα H1047R -selective inhibitor has progressed into clinical trials, while three pan mutant (H1047R, H1047L, H1047Y, E542K, and E545K) selective PI3Kα inhibitors have also reached the clinical stage. Herein, we report the design and discovery of a series of pyridopyrimidinones that inhibit PI3Kα H1047R with high selectivity over PI3Kα WT , resulting in the discovery of compound 17. When dosed in the HCC1954 tumor model in mice, 17 provided tumor regressions and a clear pharmacodynamic response. X-ray cocrystal structures from several PI3Kα inhibitors were obtained, revealing three distinct binding modes within PI3Kα H1047R including a previously reported cryptic pocket in the C-terminus of the kinase domain wherein we observe a ligand-induced interaction with Arg1047.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Disentangling Electronic Transport and Hysteresis at Individual Grain Boundaries in Hybrid Perovskites via Automated Scanning Probe Microscopy

Underlying the rapidly increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) is the advancement in the understanding of the microstructure of polycrystalline MHP thin film. Over the past decade, intense efforts have been aimed at understanding the effect of microstructures on MHP properties, including chemical heterogeneity, strain disorder, phase impurity, etc. It has been found that grain and grain boundary (GB) are tightly related to lots of microscale and nanoscale behavior in MHP thin films. Atomic force microscopy (AFM) is widely used to observe grain and boundary structures in topography and subsequently to study the correlative surface potential and conductivity of these structures. For now, most AFM measurements have been performed in imaging mode to study the static behavior; in contrast, AFM spectroscopy mode allows us to investigate the dynamic behavior of materials, e.g., conductivity under sweeping voltage. However, a major limitation of AFM spectroscopy measurements is that they require manual operation by human operators, and as such only limited data can be obtained, hindering systematic investigations of these microstructures. Here, we designed a workflow combining the conductive AFM measurement with a machine learning (ML) algorithm to systematically investigate grain boundaries in MHPs. The trained ML model can extract GBs locations from the topography image, and the workflow drives the AFM probe to each GB location to perform a current–voltage (IV) curve automatically. Then, we are able to have IV curves at all GB locations, allowing us to systematically understand the property of GBs. Using this method, we discovered that the GB junction points are less conductive, potentially more photoactive, and can play critical roles in MHP stability, while most previous works only focused on the difference between GB and grains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗