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At least 559 records · Page 31

Light-Driven Expansion of Spiropyran Hydrogels

The incorporation of molecular switches in organic structures is of great interest in the chemical design of stimuli-responsive materials that mimic the complex functions of living systems. Merocyanine dyes that convert to spiropyran moieties upon exposure to visible light have been extensively studied as they can be incorporated in hydrated covalent networks that will expel water when this conversion occurs and induce a volumetric shrinkage. We report here on a sulfonatebased water soluble photoswitch that in contrast to the well-known system triggers a volumetric expansion in hydrogels upon exposure to photons. Contraction is in turn observed under dark conditions in a highly reversible manner. The novel behavior of the photoswitch incorporated in the covalent network was also predicted by coarse grain simulations of the system’s chemical structure. Using pH control and polymeric structures that differ in lower critical solution temperature we were able to develop hydrogels with highly tunable volumetric expansion. Furthermore, the novel molecular function of the systems developed here led to materials with the negative phototaxis observed in plants, and can expand the potential use of hydrogels as sensors, soft robots, and actuators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fingerprinting Brownian Motions of Polymers under Flow

Here, we present a quantitative approach to the self-dynamics of polymers under steady flow by employing a set of complementary reference frames and extending the spherical harmonic expansion technique to dynamic density correlations. Application of this method to nonequilibrium molecular dynamics simulations of polymer melts reveals a number of universal features. For both unentangled and entangled melts, the center-of-mass motions in the flow frame are described by superdiffusive, anisotropic Gaussian distributions, whereas the isotropic component of monomer self-dynamics in the center-of-mass frame is strongly suppressed. Spatial correlation analysis shows that the heterogeneity of monomer self-dynamics increases significantly under flow.

36 MATERIALS SCIENCE↗

Characterizing sample degradation from synchrotron based X-ray measurements of ultra-thin exfoliated flakes

It is undeniable that novel 2D devices and heterostructures will have a lasting impact on the advancement of future technologies. However, the inherent instability of many exfoliated van der Waals (vdW) materials is a well-known hurdle yet to be overcome. Thus, the sustained interest in exfoliated vdW materials underscores the importance of understanding the mechanisms of sample degradation to establish proactive protective measures. Here, the impact of prolonged synchrotron-based X-ray beam exposure on exfoliated flakes of two contemporary vdW materials, NiPS 3 and α-RuCl 3 , is explored using resonant inelastic X-ray scattering (RIXS) and total fluorescence yield X-ray absorption spectroscopy (XAS). In NiPS 3 , the resulting RIXS and XAS spectra show a suppression, then vanishing, of NiS 6 multiplet excitations coupled with an upward shift of the peak energy of the XAS as a function of X-ray dose. In α-RuCl 3 , the signs of beam damage from the RIXS spectra are less evident. However, the post-experiment characterization of both materials using Raman spectroscopy exhibits signals of an amorphous and disordered system compared to pristine flakes; in addition, energy-dispersive X-ray spectroscopy of NiPS 3 shows evidence of ligand vacancies. As synchrotron radiation is fast becoming a required probe to study 2D vdW materials, these findings lay the groundwork for the development of future protective measures for synchrotron-based prolonged X-ray beam exposure, as well as for X-ray free electron laser.

2D magnetism↗

Long-range magnetic order with disordered spin orientations in a high-entropy antiferromagnet

Disorder in magnetic systems typically suppresses long-range order, promoting short-range states such as spin glasses and magnetic clusters. This is particularly prominent in high-entropy materials, characterized by the random distributions of local magnetic entities and exchange interactions. However, in rare exceptions, long-range magnetic order can persist in high-entropy systems, while the microscopic characters and underlying mechanisms remain elusive, especially the magnetic behaviors of individual elements. Here, combining neutron diffraction and resonant soft x-ray scattering, we have conducted an element-specific investigation into the magnetic order of a high-entropy honeycomb-lattice van der Waals material (Mn 1/4 Fe 1/4 Co 1/4 Ni 1/4 )PS 3 . Despite significant atomic disorder, long-range zigzag antiferromagnetic order is observed below 72 K, with all four transition-metal elements participating in a unified phase transition. However, the spin orientations of various elements are distinct, attributed to the competition between single-ion anisotropies and exchange interactions. Our findings showcase a novel form of long-range magnetic order with disordered spin orientations, which is synergically stabilized by distinct magnetic elements in a high entropy magnet, offering a new paradigm for understanding complex magnetic systems.

Shen, Yao [Chinese Academy of Sciences (CAS), Beij↗

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material is highly nonlinear in nature, as is common in biological tissue. In this work, we identify unknown material properties in continuum solid mechanics via physics-informed neural networks (PINNs). To improve the accuracy and efficiency of PINNs, we develop efficient strategies to nonuniformly sample observational data. We also investigate different approaches to enforce Dirichlet-type boundary conditions (BCs) as soft or hard constraints. Finally, we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space. The estimated material parameters achieve relative errors of less than 1%. As such, this work is relevant to diverse applications, including optimizing structural integrity and developing novel materials.

97 MATHEMATICS AND COMPUTING↗

Effect of the Segmental Structure of Thermoplastic Polyurethane (Hardness) on the Interfacial Adhesion of Textile-Grade Carbon Fiber Composites

In polymer composites, the fiber–matrix interface is primarily influenced by the surface treatment of the fibers and polymer morphology. Previous studies have investigated the effect of surface treatment of carbon fiber on the mechanical properties of the resulting composites. However, very few studies have explored the chemical structural modification of polymer effect on the fiber–matrix adhesion. In this work, the interfaces of soft thermoplastic polyurethane (S-TPU) and hard-segmented TPU (H-TPU) were investigated through surface, thermal, and mechanical characterization. A textile-grade carbon fiber (TCF) with 1% concentration of epoxy sizing (an emerging material for nonaerospace applications with 450 K filament tows) was used as a reinforcement to investigate the structure–property relationship at the interface. Atomic force microscopy results showed 39% higher surface roughness for S-TPU than for H-TPU. X-ray photoelectron spectroscopy results revealed a 550% increase in C=O content, which can provide multiple hydrogen bonding networks in H-TPU, and these C=O bonds can produce a strong chemical bond at the fiber–matrix interface. Additionally, dynamic mechanical analysis and differential scanning calorimetry results confirmed the presence of hydrogen bonding that enhances the cross-linked density by 232% in H-TPU compared to S-TPU. The improved mechanical properties of H-TPU composites, such as flexural, impact and tensile by 30, 50, and 130% compared to S-TPU composites, prove that the crystallinity and hydrogen bonding significantly increase the load bearing capacity due to the strong interface. The mechanical properties of TCF–TPU composites validate the formation of chemical bonds through a nucleophilic addition reaction at the interface and improve the bond strength of the composites. Thus, tailoring the polyurethane structure broadens the performance of segmented TPU in conjunction with TCF reinforcement, which has implications for cost-effective, high-strength composites.

36 MATERIALS SCIENCE↗

Dual-scale folding in cutting of commercially pure aluminum alloys

We examine a, hitherto, little-studied and curious machining chip morphology, with tell-tale signs of folding at two different length scales, that is common in cutting of certain ductile and highly strain-hardening metals like soft aluminum alloys, tantalum and niobium. This chip morphology does not appear in the usual catalogues of common chip types. The mechanics of formation of the “dual-scale folded chip” is studied in model material systems of commercially pure aluminum alloys (AA 1100 and AA 8040), that prominently exhibit this chip morphology. The flow, folding and associated plastic instabilities are investigated using micro/macro structure observations of the chip in a plane-strain cutting framework, with high-speed in situ imaging and image analysis of material flow; and force measurements. The smaller-scale folding is shown to develop in the primary deformation zone while the larger-scale folding occurs as the chip traverses the rake face of the tool. The resulting chip is composed of irregularly-spaced large folds, superimposed onto which are the quasi periodic small folds. The representative wavelengths of the two folds differ on average by an order of magnitude, 0.1 mm vs. 2 mm. The observations reveal a direct coupling between the material flow and chip morphology, and how specific attributes of the dual-scale folded chip arise from the flow mechanism. Plastic buckling is found to play a key role in the folding at both length scales. The small-scale folds are characteristic of a sinuous plastic flow mode, while the large-scale folding is characterized by buckling and stick-slip along the tool rake face, triggered by adhesive pinning of the chip to the tool. Important consequences of the dualscale folding are very large cutting forces, and force oscillations of large amplitude, despite the alloys being very soft, only ~ 25 HV. Here, the dual-scale folding is why many of these alloys are classified as “gummy” to machine. Since the dual-scale folded chip is associated with large cutting forces and poor surface quality, there is much to be gained by disrupting this flow type in practical machining applications. Methods for controlling the folding to improve machining performance with the gummy alloys are briefly discussed.

36 MATERIALS SCIENCE↗

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗

On the effect of strain rate during the cyclic compressive loading of liquid crystal elastomers and their 3D printed lattices

Nematic liquid crystal elastomers (LCEs) are a unique class of network polymers with the potential for enhanced mechanical energy absorption and dissipation capacity over conventional network polymers because they exhibit both conventional viscoelastic behavior and soft-elastic behavior (nematic director changes under shear loading). This additional inelastic mechanism makes them appealing as candidate damping materials in a variety of applications from vibration to impact. The lattice structures made from the LCEs provide further mechanical energy absorption and dissipation capacity associated with packing out the porosity under compressive loading. Understanding the extent of mechanical energy absorption, which is the work per unit mass (or volume) absorbed during loading, versus dissipation, which is the work per unit mass (or volume) dissipated during a loading cycle, requires measurement of both loading and unloading response. Here, in this study, a bench-top linear actuator was employed to characterize the loading-unloading compressive response of polydomain and monodomain LCE polymers and polydomain LCE lattice structures with two different porosities (nominally, 62% and 85%) at both low and intermediate strain rates at room temperature. As a reference material, a bisphenol-A (BPA) polymer with a similar glass transition temperature (9 °C) as the nematic LCE (4 °C) was also characterized at the same conditions for comparing to the LCE polymers. Based on the loading-unloading stress-strain curves, the energy absorption and dissipation for each material at different strain rates (0.001, 0.1, 1, 10 and 90 s -1 ) were calculated with considerations of maximum stress and material mass/density. The strain-rate effect on the mechanical response and energy absorption and dissipation behaviors was determined. The energy dissipation ratio was also calculated from the resultant loading and unloading stress-strain curves. All five materials showed significant but different strain rate effects on energy dissipation ratio. The solid LCE and BPA materials showed greater energy dissipation capabilities at both low (0.001 s -1 ) and high (above 1 s -1 ) strain rates, but not at the strain rates in between. The polydomain LCE lattice structure showed superior energy dissipation performance compared with the solid polymers especially at high strain rates.

36 MATERIALS SCIENCE↗

Field-Driven Out-of-Equilibrium Collective Patterns for Swarm Micro-Robotics

Soft robotics has been rapidly advancing, offering significant improvements over traditional rigid robotic systems through the use of compliant materials that enhance adaptability and interaction with the environment. However, current approaches face critical challenges, including the reliance on complex “top-down” fabrication techniques and the difficulty of wireless powering and control at the microscale. Swarm robotics introduces a paradigm shift, leveraging collective dynamics to achieve cooperative and adaptable behaviors among multiple robotic units. Inspired by nature, this “bottom-up” approach enables swarm robots to execute task-specific reconfigurations, enhancing flexibility and robustness. Field-driven active colloids emerge as a promising platform for swarm microrobotics, capable of self-propulsion and self-organization into dynamic collective patterns under external field excitation and manipulation. These systems mimic biologically inspired swarm behaviors, such as flocking and vortex formation, providing a versatile foundation for designing innovative swarm microrobots. Here, this review discusses the principles of electric and magnetic field-driven collective self-organization, focusing on the particle dynamics, the emergence of collective swarm patterns, and illustrative examples of functional swarm microrobots. It concludes with future perspectives on harnessing these systems for adaptive, scalable, and multifunctional microrobotic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Enhanced superconductivity and ferroelectric quantum criticality in plastically deformed strontium titanate

The properties of quantum materials are commonly tuned using experimental variables such as pressure, magnetic field and doping. Here we explore a different approach using irreversible, plastic deformation of single crystals. We show that compressive plastic deformation induces low-dimensional superconductivity well above the superconducting transition temperature (Tc) of undeformed SrTiO3, with evidence of possible superconducting correlations at temperatures two orders of magnitude above the bulk Tc. The enhanced superconductivity is correlated with the appearance of self-organized dislocation structures, as revealed by diffuse neutron and X-ray scattering. We also observe deformation-induced signatures of quantum-critical ferroelectric fluctuations and inhomogeneous ferroelectric order using Raman scattering. Our results suggest that strain surrounding the self-organized dislocation structures induces local ferroelectricity and quantum-critical dynamics that strongly influence Tc, consistent with a theory of superconductivity enhanced by soft polar fluctuations. Our results demonstrate the potential of plastic deformation and dislocation engineering for the manipulation of electronic properties of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multiscale Mechanisms of Twisted Carbon Nanotube Yarns Probed In Situ by Soft X-rays during Tensile Loading

Piecing together carbon nanotubes (CNTs) into assemblies has so far failed to achieve the same elite strength performance metrics as individual CNTs, highlighting a critical deficiency in understanding the effects that the processing of individual nanostructures have on the performance of their derived macroscale assemblies, thereby hindering the development of a process-structure-performance map for these materials. Here, in this work, we propose a method to decouple the distribution orientation of nanoscale tortuosity and the microscale twist of CNT dry-spun yarns under applied loads via in situ soft X-ray probing at high energy (1200 eV) and low energy (280 eV), respectively. With this decoupling enabled by in situ soft X-ray scattering, we acquired a deeper understanding of the deformation mechanisms of these yarns. We found that for untreated yarns, the twist angle of collective CNT bundles at the macroscale is more sensitive to applied stress than the nanoscale alignment distribution. We also found that increasing nominal twist densities of yarns as well as increased strengthening via plasma treatments and polymer infiltration act to decrease the yarns’ sensitivity to realignment at the nanoscale and prevent failure by the slip mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supersoft Norbornene–Based Thermoplastic Elastomers with High Strength and Upper Service Temperature

With over 6 million tons produced annually, thermoplastic elastomers (TPEs) have become ubiquitous in modern society, due to their unique combination of elasticity, toughness, and reprocessability. Nevertheless, industrial TPEs display a tradeoff between softness and strength, along with low upper service temperatures, typically ≤100 °C. This limits their utility, such as in bio-interfacial applications where supersoft deformation is required in tandem with strength, in addition to applications that require thermal stability (e.g., encapsulation of electronics, seals/joints for aeronautics, protective clothing for firefighting, and biomedical devices that can be subjected to steam sterilization). Thus, combining softness, strength, and high thermal resistance into a single versatile TPE has remained an unmet opportunity. Through de novo design and synthesis of novel norbornene-based ABA triblock copolymers, this gap is filled. Ring-opening metathesis polymerization is employed to prepare TPEs with an unprecedented combination of properties, including skin-like moduli (<100 kPa), strength competitive with commercial TPEs (>5 MPa), and upper service temperatures akin to high-performance plastics (≈260 °C). Here, the materials are elastic, tough, reprocessable, and shelf stable (≥2 months) without incorporation of plasticizer. Structure–property relationships identified herein inform development of next-generation TPEs that are both biologically soft yet thermomechanically durable.

36 MATERIALS SCIENCE↗

Inferring colloidal interaction from scattering by machine learning

A machine learning solution for the potential inversion problem in elastic scattering is outlined. The inversion scheme consists of two major components, a generative network featuring a variational autoencoder which extracts the targeted static two-point correlation functions from experimentally measured scattering cross sections, and a Gaussian process framework which probabilistically infers the relevant structural parameters from the inverted correlation functions. Via a case study of charged colloidal suspensions, the feasibility of this approach for quantitative study of molecular interaction is critically benchmarked and its merit over existing deterministic approaches, in terms of numerical accuracy and computationally efficiency, is demonstrated.

36 MATERIALS SCIENCE↗

Sulfonated Aromatic Polypentenamers: Scope of the Acetyl Sulfate Reaction

A precision polymer featuring one phenyl pendant at every fifth carbon on a polyethylene backbone was modified to varying degrees of sulfonation (DS = 33–98%) using acetyl sulfate with standard conditions by varying reaction times (up to 48 h). This soft, homogeneous method allows for evenly distributed phenylsulfonic acid groups with minimal side reactions and results in light brown, transparent materials with glass transition temperatures of 33–78 °C that increase with DS and parent polymer molar mass. The DS was accurately determined through well-resolved 1 H NMR (DSHNMR) signals of the regularly spaced phenyl groups and corroborated by inverse-gated decoupling 13 C NMR analysis. These analyses were compared to a series of other commonly accepted methods for DS determination including titration and elemental analysis (EA). The DS by titration (DS titr ) also increased with reaction time but was consistently lower than those determined by NMR. Significant discrepancies between theoretical and measured sulfur mass were observed for several samples through EA. Qualitative methods, such as infrared spectroscopy and thermal analyses, were also performed and correlated well with the DS determined by NMR. Here, this study presents a promising method to achieve a complete scope of homogeneous sulfonation from mild reaction conditions and presents a case to determine DS through multiple methods, with spectroscopic analyses, such as NMR, being potentially the most valuable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Facile Oxide to Chalcogenide Conversion for Actinides Using the Boron–Chalcogen Mixture Method

Actinide chalcogenides are of interest for fundamental studies of the behavior of 5f electrons in actinides located in a soft ligand coordination environment. As actinides exhibit an extremely high affinity for oxygen, the synthesis of phase pure actinide chalcogenide materials free of oxide impurities is a great challenge and, moreover, requires the availability and use of oxygen free starting materials. Herein, we report a new method, the Boron-Chalcogen Mixture (BCM) method, for the synthesis of phase pure uranium chalcogenides based on the use of a boron/chalcogen mixture, where boron functions as an “oxygen sponge” to remove oxygen from an oxide precursor and where the elemental chalcogen effects transformation of the oxide precursor into an oxygen free chalcogenide reagent. Here, the boron oxide can be separated from the reaction mixture that is left to react to form the desired chalcogenide product. Several syntheses are presented that demonstrate the broad functionali-ty of the technique and thermodynamic calculations that show the underlying driving force are discussed. Specifically, three classes of chalcogenides that include both new (rare earth uranium sulfides and alkali-thorium thiophosphates) and previously reported compounds were prepared to validate the approach: binary uranium and thorium sulfides, oxide to sulfide transfor-mation in solid state reactions, and in situ generation of actinide chalcogenides in flux crystal growth reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tunable and Cooperative Thermomechanical Properties of Protein-Metal-Organic Frameworks

We recently introduced protein-metal-organic frameworks (protein-MOFs) as chemically designed protein crystals, composed of ferritin nodes that predictably assemble into 3D lattices upon coordination of various metal ions and ditopic, hydrox-amate-based linkers. Owing to their unique tripartite construction, protein-MOFs possess extremely sparse lattice connectivi-ty, suggesting that they might display unusual thermomechanical properties. Leveraging the synthetic modularity of ferritin-MOFs, we investigated the temperature-dependent structural dynamics of six distinct frameworks. Our results show that the thermostabilities of ferritin-MOFs can be tuned through the metal component or the presence of crowding agents. Our stud-ies also reveal a framework that undergoes a reversible and isotropic first-order phase transition near-room temperature, corre-sponding to a 4% volumetric change within ≤1 deg C and a hysteresis window of ~10 deg C. Here, this highly cooperative crystal-to-crystal transformation, which stems from the soft crystallinity of ferritin-MOFs, illustrates the advantage of modular con-struction strategies in discovering tunable–and unpredictable–material properties.

36 MATERIALS SCIENCE↗