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At least 487 records · Page 27

Shape-Preserved Transformation of Biological Cells into Synthetic Hydrogel Microparticles

The synthesis of materials that can mimic the mechanical, and ultimately functional, properties of biological cells can broadly impact the development of biomimetic materials, as well as engineered tissues and therapeutics. Yet, it is challenging to synthesize, for example, microparticles that share both the anisotropic shapes and the elastic properties of living cells. Here in paper, a cell-directed route to replicate cellular structures into synthetic hydrogels such as polyethylene glycol (PEG) is described. First, the internal and external surfaces of chemically fixed cells are replicated in a conformal layer of silica using a sol–gel process. The template is subsequently removed to render shape-preserved, mesoporous silica replicas. Infiltration and cross-linking of PEG precursors and dissolution of the silica result in a soft hydrogel replica of the cellular template as demonstrated using erythrocytes, HeLa, and neuronal cultured cells. The elastic modulus can be tuned over an order of magnitude (≈10–100 kPa) though with a high degree of variability. Furthermore, synthesis without removing the biotemplate results in stimuli-responsive particles that swell/deswell in response to environmental cues. Overall, this work provides a foundation to develop soft particles with nearly limitless architectural complexity derived from dynamic biological templates.

59 BASIC BIOLOGICAL SCIENCES↗

Continuous Encodable Reshaping of Gold Nanocrystals through Facet Modulation

Shape control of nanocrystals (NCs) is crucial for tuning their assembly behavior and functional properties, yet the precise manipulation of facet composition remains challenging. Here, we present a nanocrystal reshaping strategy to control and modulate the facets of gold (Au) NCs. Our one-pot approach, conducted at room temperature, requires only initial Au NCs, Au 3+ ions, and surfactants, distinguishing it from conventional reduction-mediated “etching-and-regrowth” methods. Detailed structural studies using electron microscopy, small-angle X-ray scattering (SAXS), and UV−vis spectroscopy reveal the surfactant-encoded pathway for NC transformation from shaped particles to spheres and then into various polyhedral shapes while preserving the individual particles' volume. The proposed reshaping mechanism involves the dissolution of surface Au atoms into Au + complexes in the presence of Au 3+ and surfactant, followed by surfactant-guided redeposition and formation of facets with different atomic planes. Using the ethanol oxidation reaction (EOR) as a probe, we observe a quasi-linear decrease in onset potential and an increase in activity with increasing {100} facet exposure. This work broadens synthetic strategies by offering precise NC reshaping and facet control.

36 MATERIALS SCIENCE↗

An ultrafast symmetry switch in a Weyl semimetal

Topological quantum materials exhibit fascinating properties with important applications for dissipationless electronics and fault-tolerant quantum computers. Manipulating the topological invariants in these materials would allow the development of topological switching applications analogous to switching of transistors. Lattice strain provides the most natural means of tuning these topological invariants because it directly modifies the electron–ion interactions and potentially alters the underlying crystalline symmetry on which the topological properties depend. However, conventional means of applying strain through heteroepitaxial lattice mismatch and dislocations are not extendable to controllable time-varying protocols, which are required in transistors. Integration into a functional device requires the ability to go beyond the robust, topologically protected properties of materials and to manipulate the topology at high speeds. Here in this paper we use crystallographic measurements by relativistic electron diffraction to demonstrate that terahertz light pulses can be used to induce terahertz-frequency interlayer shear strain with large strain amplitude in the Weyl semimetal WTe 2 , leading to a topologically distinct metastable phase. Separate nonlinear optical measurements indicate that this transition is associated with a symmetry change to a centrosymmetric, topologically trivial phase. We further show that such shear strain provides an ultrafast, energy-efficient way of inducing robust, well separated Weyl points or of annihilating all Weyl points of opposite chirality. This work demonstrates possibilities for ultrafast manipulation of the topological properties of solids and for the development of a topological switch operating at terahertz frequencies.

36 MATERIALS SCIENCE↗

Mechanistic insight into the effects of A-site doping in perovskite nanorods on interfacial Li-ion and Na-ion transport in polymer–perovskite composite electrolytes

Composite polymer electrolytes (CPEs) offer a promising pathway to safer and higher energy density electrochemical energy storage yet optimizing interfacial ion transport remains a critical challenge due to high resistances and a lack of understanding of the complex interfacial electrostatic interactions. This work investigates the mechanistic origins of the interfacial ion transport enhancement in single-ion conducting (SIC) polymer electrolytes filled with A-site disordered perovskite LaxMyTiOz (LMTO) (M = Li, Na, K) nanorods. By integrating Density Functional Theory (DFT) with broadband dielectric spectroscopy (BDS) and pulsed-field-gradient NMR (PFG-NMR), we analyze the ion transport behavior in Li-based and Na-based SIC systems containing compositionally distinct LMTO fillers (LMTO800 and LMTO900). Specifically, we introduce the site-to-site energy difference (ΔE) descriptor, which extends beyond single-site descriptors such as adsorption energy and ion binding energies. We demonstrate that ΔE together with ion binding energies provide a more comprehensive picture of the energy landscape at the polymer–ceramic interface. The combined DFT and experimental results show that A-site doping in the ceramic filler can effectively modulate ΔE and ion binding energies, creating a favorable potential energy landscape that promotes enhanced ion transport along the interface. This comprehensive study illustrates the impact of ceramic compositional tuning on interfacial ion transport and provides materials design rules towards real-world applications.

B shepard, Lauren [Pennsylvania State University]↗

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗

Modes of Disorder in Poly(carbon monofluoride)

Poly(carbon monofluoride), or (CF) n , is a layered fluorinated graphite material consisting of nanosized platelets. In this work, we present experimental multidimensional solid-state NMR spectra of (CF)n, supported by density functional theory (DFT) calculations of NMR parameters, which overhauls our understanding of structure and bonding in the material by elucidating many ways in which disorder manifests. We observe strong 19 F NMR signals conventionally assigned to elongated or “semi-ionic” C–F bonds and find that these signals are in fact due to domains where the framework locally adopts boat-like cyclohexane conformations. We calculate that C–F bonds are weakened but are not elongated by this conformational disorder. Exchange NMR suggests that conformational disorder avoids platelet edges. We also use a new J-resolved NMR method for disordered solids which provides molecular-level resolution of highly fluorinated edge states. Strings of consecutive difluoromethylene groups at edges are relatively mobile. Topologically distinct edge features, including zigzag edges, crenellated edges, and coves are resolved in our samples by solid-state NMR. Disorder should be controllable in a manner dependent on synthesis, affording new opportunities for tuning the properties of graphite fluorides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dual‐Functional High‐Entropy Polymer Exhibiting Giant Cross‐Energy Couplings at Low Fields

A key component of cooling devices is the transfer of entropy from the cold load to heat sink. An electrocaloric (EC) polymer capable of generating both large electrocaloric effect (ECE) and substantial electroactuation can enable EC cooling devices to pump heat without external mechanisms, resulting in compact designs and enhanced efficiency. However, achieving both high ECE and significant electroactuation remains challenging. Herein, it is demonstrated that poly(vinylidene fluoride‐trifluoroethylene‐chlorofluoroethylene‐double bond) [P(VDF‐TrFE‐CFE‐DB)] tetrapolymers can simultaneously generate high electrocaloric effects and electroactuations under low fields. These P(VDF‐TrFE‐CFE‐DB) tetrapolymers are synthesized through the dehydrochlorination of P(VDF‐TrFE‐CFE) terpolymer. By facile tuning the composition of the initial terpolymer to avoid pure relaxor state, tetrapolymers with optimal DB compositions are achieved, near the critical endpoint of normal ferroelectric phase with diffused phase transition. The nearly vanishing energy barriers between the nonpolar to polar phases result in a strong electrocaloric response and significant electroactuation. Specifically, the P(VDF‐TrFE‐CFE‐DB) tetrapolymer exhibits an EC entropy change Δ S of 100 J kg −1 K −1 under 100 MV m −1 : comparable to state‐of‐the‐art (SOA) EC polymers, while delivering nearly twice the electroactuation of the SOA EC polymers. This work presents a general strategy for developing EC materials that combine large electrocaloric effect and electroactuation at low electric fields.

36 MATERIALS SCIENCE↗

Evidence for electronic signature of a magnetic transition in the topological magnet HoSbTe

Topological insulators with intrinsic magnetic order are emerging as an exciting platform to realize fundamentally new excitations from topological quantum states of matter. To study these systems and their physics, people have proposed a variety of magnetic topological insulator systems, including HoSbTe, an antiferromagnetic weak topological insulator candidate. Here, in this work, we use scanning tunneling microscopy to probe the electronic structure of HoSbTe with antiferromagnetic and ferromagnetic orders that are tuned by applying an external magnetic field. Although around the Fermi energy we find minor differences between the quasiparticle interferences under the ferromagnetic and antiferromagnetic orders, deep inside the valance region, a quasiparticle interference signal emerges with ferromagnetism. This observation is consistent with our first-principles calculations indicating the magnetism-driven transition of the electronic states in this spin-orbit coupled topological magnet.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Scrambling versus relaxation in Fermi and non-Fermi liquids

In this work, we compute the Lyapunov exponent characterizing quantum scrambling in a family of generalized Sachdev- Ye-Kitaev models, which can be tuned between different low temperature states from Fermi liquids, through non-Fermi liquids, to fast scramblers. The analytic calculation, controlled by a small coupling constant and large $\textit{N}$, allows us to clarify the relations between the quasiparticle relaxation rate $\textit{1/τ}$ and the Lyapunov exponent $λ_L$ characterizing scrambling. In the Fermi liquid states we find that the quasiparticle relaxation rate dictates the Lyapunov exponent. In non-Fermi liquids, where $1/τ \gg T$, we find that $λ_L$ is always $\textit{T}$ linear with a prefactor that is independent of the coupling constant in the limit of weak coupling. Instead it is determined by a scaling exponent that characterizes the relaxation rate. $λ_L$ approaches the general upper bound 2$\textit{πT}$ at the transition to a fast scrambling state. Finally, in a marginal Fermi liquid state the exponent is linear in temperature with a prefactor that vanishes as a nonanalytic function ~$g\text{ln}(1/g)$ of the coupling constant $\textit{g}$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Imaging the Meissner effect in hydride superconductors using quantum sensors

By directly altering microscopic interactions, pressure provides a powerful tuning knob for the exploration of condensed phases and geophysical phenomena. Here, the megabar regime represents an interesting frontier, in which recent discoveries include high-temperature superconductors, as well as structural and valence phase transitions. However, at such high pressures, many conventional measurement techniques fail. Here we demonstrate the ability to perform local magnetometry inside a diamond anvil cell with sub-micron spatial resolution at megabar pressures. Our approach uses a shallow layer of nitrogen-vacancy colour centres implanted directly within the anvil; crucially, we choose a crystal cut compatible with the intrinsic symmetries of the nitrogen-vacancy centre to enable functionality at megabar pressures. We apply our technique to characterize a recently discovered hydride superconductor, CeH 9 . By performing simultaneous magnetometry and electrical transport measurements, we observe the dual signatures of superconductivity: diamagnetism characteristic of the Meissner effect and a sharp drop of the resistance to near zero. By locally mapping both the diamagnetic response and flux trapping, we directly image the geometry of superconducting regions, showing marked inhomogeneities at the micron scale. Our work brings quantum sensing to the megabar frontier and enables the closed-loop optimization of superhydride materials synthesis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The throughput calibration of the VERITAS telescopes

Context. The response of imaging atmospheric Cherenkov telescopes to incident γ -ray-initiated showers in the atmosphere changes as the telescopes age due to exposure to light and weather. These aging processes affect the reconstructed energies of the events and γ -ray fluxes. Aims. This work discusses the implementation of signal calibration methods for the Very Energetic Radiation Imaging Telescope Array System (VERITAS) to account for changes in the optical throughput and detector performance over time. Methods. The total throughput of a Cherenkov telescope is the product of camera-dependent factors, such as the photomultiplier tube gains and their quantum efficiencies, and the mirror reflectivity and Winston cone response to incoming radiation. This document summarizes different methods to determine how the camera gains and mirror reflectivity have evolved over time and how we can calibrate this changing throughput in reconstruction pipelines for imaging atmospheric Cherenkov telescopes. The implementation is validated against seven years of observations with the VERITAS telescopes of the Crab Nebula, which is a reference object in very-high-energy astronomy. Results. Regular optical throughput monitoring and the corresponding signal calibrations are found to be critical for the reconstruction of extensive air shower images. The proposed implementation is applied as a correction to the signals of the photomultiplier tubes in the telescope simulation to produce fine-tuned instrument response functions. This method is shown to be effective for calibrating the acquired γ -ray data and for recovering the correct energy of the events and photon fluxes. At the same time, it keeps the computational effort of generating Monte Carlo simulations for instrument response functions affordably low.

79 ASTRONOMY AND ASTROPHYSICS↗

Electronic structure of boron and aluminum δ -doped layers in silicon

Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum δ-doped layers in silicon with densities above the solid solubility limit. For this study, we use density functional theory to predict the band structure and effective mass values of such δ layers, first modeling them as ordered supercells. Structural relaxation is found to have a significant impact on the impurity band energies and effective masses of the boron layers, but not the aluminum layers. However, disorder in the δ layers is found to lead to a significant flattening of the bands in both cases. We calculate the local density of states and doping potential for these δ-doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor δ-doped layers exhibit different electronic structure features dependent on both the dopant atom and spatial ordering. This suggests prospects for controlling the electronic properties of these layers if the local details of the incorporation chemistry can be fine-tuned.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GdWN 3 is a nitride perovskite

Nitride perovskites ABN3 are an emerging and highly underexplored class of materials that are of interest due to their intriguing calculated ferroelectric, optoelectronic, and other functional properties. Incorporating novel A-site cations is one strategy to tune and expand such properties; for example, Gd 3+ is compelling due to its large magnetic moment, potentially leading to multiferroic behavior. However, the theoretically predicted ground state of GdWN 3 was a non-perovskite monoclinic structure. Here, we experimentally show that GdWN 3-y crystallizes in a perovskite structure. High-throughput combinatorial sputtering with activated nitrogen is employed to synthesize thin films of Gd 2-x W x N 3-y O y with oxygen content y < 0.05. Ex situ annealing crystallizes a polycrystalline perovskite phase in a narrow composition window near x = 1. LeBail fits of synchrotron grazing incidence wide angle x-ray scattering data are consistent with a perovskite ground-state structure. Refined density functional theory calculations that included antiferromagnetic configurations confirm that the ground-state structure of GdWN 3 is a distorted Pnma perovskite with antiferromagnetic ordering, in contrast to prior predictions. Initial property measurements find that GdWN 3-y is paramagnetic down to T = 2 K with antiferromagnetic correlations and that the absorption onset depends on cation stoichiometry. This work provides an important path toward both the rapid expansion of the emerging family of nitride perovskites and understanding their potential multiferroic properties.

14 SOLAR ENERGY↗

The Kokkos Ecosystem [Brief]

In 2016/2017, the field of High-Performance Computing (HPC) entered a new era driven by fundamental physics challenges to produce ever more energy and cost-efficient processors. Since the convergence on the Message-Passing Interface (MPI) standard in the mid-1990s, application developers enjoyed a seemingly static view of the underlying machine — that of a distributed collection of homogeneous nodes executing in collaboration. However, after almost two decades of dominance, the sole use of MPI to derive parallelism acted as a limiter to improved future performance. While MPI is widely expected to continue to function as the basic mechanism for communication between compute nodes for the immediate future, additional parallelism is required on the computing node itself if high performance and efficiency goals are to be realized. When reviewing the architectures of the top HPC systems today, the change in paradigm is clear: the compute nodes of the leading machines in the world are either powered by many-core chips with a few dozen cores each, or use heterogeneous designs, where traditional CPUs marshal work to massively parallel compute accelerators which has as many as 200,000 processing threads in flight simultaneously. Complicating matters further for application developers, each processor vendor has its own preferred way of writing code for their architecture.The Kokkos EcoSystem was released by Sandia in 2017 to address this new era in HPC system design by providing a vendor independent performance portable programming system for scientific, engineering, and mathematical software applications written in the C++ programming language. Using Kokkos, application developers can be more productive because they will not have to create and maintain separate versions of their software for each architecture, nor will they have to be experts in each architecture's peculiar requirements. Instead, they will have a single method of programming for the diverse set of modern HPC architectures. While Kokkos started in 2011 as a programming model only, it soon became clear that complex applications needed more. It is also critical to have a portable mathematical functions and developers need tools to debug their applications, gain insight into the performance characteristics of their codes and tune algorithm performance parameters through automated processes. The Kokkos EcoSystem addresses those needs through its three main components: the Kokkos Core programming model, the Kokkos Kernels math library, and the Kokkos Tools project.

97 MATHEMATICS AND COMPUTING↗

Revealing Mesoscale Ionomer Membrane Structure by Tender Resonant X-ray Scattering

Nafion, a perfluorosulfonic acid ionomer, has been well-studied for decades due to its key role as an ion-conductive membrane in electrochemical energy conversion and storage applications. When hydrated, this membrane phase separates into a complex hierarchical nanostructure with hydrophilic domains that facilitate ion transport. Hard X-ray scattering has been a powerful technique in understanding Nafion due to its capabilities in capturing the ionomer’s nanophase separated structure, which gives rise to contrast between polymer and water domains. More recently, resonant X-ray scattering, which tunes to elemental absorption edges to provide specificity on constituent elements, has been explored to highlight key interactions related to the sulfonic acid groups within its structure. Here, in this work, we study the Nafion nanostructure by combining hard X-ray scattering and tender resonant X-ray scattering (TReXS) at the sulfur K-edge to reveal a mesoscopic feature corresponding to a correlation length of approximately 40 nm that has been challenging to resolve with hard X-ray studies. Additionally, we study the effect of the dispersion solvent composition that plays a key role in the formation of this mesoscale feature. Notably, TReXS can attain high contrast to decipher this mesoscale morphology even for dry polymer membranes under a vacuum, which typically have reduced contrast for hard X-rays. We find that the correlation length of this mesoscale feature decreases with increasing water fraction in the dispersion, which is the opposite trend exhibited by the smaller intercrystalline feature in the same membranes. This study showcases the utility of TReXS to uncover multiscale morphological details in functional polymers that are not always revealed by other methods like hard X-ray scattering. We illustrate this with Nafion, which is a relevant ion-conducting polymer for electrochemical technologies.

36 MATERIALS SCIENCE↗

Injection locking and coupling dynamics in superconducting nanowire-based cryogenic oscillators

Oscillators designed to function at cryogenic temperatures play a critical role in superconducting electronics and quantum computing by providing stable, low-noise signals with minimal energy loss. Here, in this work, we present a comprehensive numerical study of injection locking and mutual coupling dynamics in superconducting nanowire (ScNW)-based cryogenic oscillators. Using the design space of a standalone ScNW-based oscillator, we investigate two critical mechanisms that govern frequency synchronization and signal coordination in cryogenic computing architectures: (1) injection locking induced by an external AC signal with a frequency near the oscillator's natural frequency, and (2) the mutual coupling dynamics between two ScNW oscillators under varying coupling strengths. We identify key design parameters—such as shunt resistance, nanowire inductance, and coupling strength—that govern the locking range. Additionally, we examine how the amplitude of the injected signal affects the amplitude of the locked oscillation, offering valuable insights for power-aware oscillator synchronization. Furthermore, we analyze mutual synchronization between coupled ScNW oscillators using capacitive and resistive coupling elements. Our results reveal that the phase difference between oscillators can be controlled by tuning the coupling strength, enabling programmable phase-encoded information processing. These findings could enable building ScNW-based oscillatory neural networks, synchronized cryogenic logic blocks, and on-chip cryogenic resonator arrays.

Artificial neural networks↗

First observation of strange baryon enhancement with effective energy in pp collisions at the LHC

The production of (multi-)strange hadrons is measured at midrapidity in proton-proton collisions at $\sqrt{s}$ = 13 TeV as a function of the local charged-particle multiplicity in the pseudorapidity interval |η| < 0.5 and of the very-forward energy measured by the ALICE Zero-Degree Calorimeters. The latter provides information on the effective energy, i.e. the energy available for particle production in the collision once subtracted from the centre-of-mass energy. The yields of K$^{0}_{s}$, $Λ$ + $\overline{Λ}$, and $Ξ$ – + $\overline{Ξ}$ + per charged-particle increase with the effective energy. In addition, this work exploits a multi-differential approach to decouple the roles of local multiplicity and effective energy in such an enhancement. The results presented in this article provide new insights into the interplay between global properties of the collision, such as the initial available energy in the event, and the locally produced final hadronic state, connected to the charged-particle multiplicity at midrapidity. Notably, a strong increase of strange baryon production with effective energy is observed for fixed charged-particle multiplicity at midrapidity. These results are discussed within the context of existing phenomenological models of hadronisation implemented in different tunes of the PYTHIA 8 event generator.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Assessing electrogenetic activation via a network model of biological signal propagation

Introduction: Molecular communication is the transfer of information encoded by molecular structure and activity. We examine molecular communication within bacterial consortia as cells with diverse biosynthetic capabilities can be assembled for enhanced function. Their coordination, both in terms of engineered genetic circuits within individual cells as well as their population-scale functions, is needed to ensure robust performance. We have suggested that “electrogenetics,” the use of electronics to activate specific genetic circuits, is a means by which electronic devices can mediate molecular communication, ultimately enabling programmable control. Methods: Here, we have developed a graphical network model for dynamically assessing electronic and molecular signal propagation schemes wherein nodes represent individual cells, and their edges represent communication channels by which signaling molecules are transferred. We utilize graph properties such as edge dynamics and graph topology to interrogate the signaling dynamics of specific engineered bacterial consortia. Results: We were able to recapitulate previous experimental systems with our model. In addition, we found that networks with more distinct subpopulations (high network modularity) propagated signals more slowly than randomized networks, while strategic arrangement of subpopulations with respect to the inducer source (an electrode) can increase signal output and outperform otherwise homogeneous networks. Discussion: We developed this model to better understand our previous experimental results, but also to enable future designs wherein subpopulation composition, genetic circuits, and spatial configurations can be varied to tune performance. We suggest that this work may provide insight into the signaling which occurs in synthetically assembled systems as well as native microbial communities.

Chun, Kayla↗