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At least 595 records · Page 33

Liquid-induced topological transformations of cellular microstructures

The fundamental topology of cellular structures—the location, number and connectivity of nodes and compartments—can profoundly affect their acoustic, electrical5, chemical, mechanical and optical properties, as well as heat, fluid and particle transport. Approaches that harness swelling, electromagnetic actuation and mechanical instabilities in cellular materials have enabled a variety of interesting wall deformations and compartment shape alterations, but the resulting structures generally preserve the defining connectivity features of the initial topology. Achieving topological transformation presents a distinct challenge for existing strategies: it requires complex reorganization, repacking, and coordinated bending, stretching and folding, particularly around each node, where elastic resistance is highest owing to connectivity. Here we introduce a two-tiered dynamic strategy that achieves systematic reversible transformations of the fundamental topology of cellular microstructures, which can be applied to a wide range of materials and geometries. Our approach requires only exposing the structure to a selected liquid that is able to first infiltrate and plasticize the material at the molecular scale, and then, upon evaporation, form a network of localized capillary forces at the architectural scale that ‘zip’ the edges of the softened lattice into a new topological structure, which subsequently restiffens and remains kinetically trapped. Reversibility is induced by applying a mixture of liquids that act separately at the molecular and architectural scales (thus offering modular temporal control over the softening–evaporation–stiffening sequence) to restore the original topology or provide access to intermediate modes. Guided by a generalized theoretical model that connects cellular geometries, material stiffness and capillary forces, we demonstrate programmed reversible topological transformations of various lattice geometries and responsive materials that undergo fast global or localized deformations. In conclusion, we then harness dynamic topologies to develop active surfaces with information encryption, selective particle trapping and bubble release, as well as tunable mechanical, chemical and acoustic properties.

42 ENGINEERING↗

Binary vector copy number engineering improves Agrobacterium -mediated transformation

The copy number of a plasmid is linked to its functionality, yet there have been few attempts to optimize higher-copy-number mutants for use across diverse origins of replication in different hosts. We use a high-throughput growth-coupled selection assay and a directed evolution approach to rapidly identify origin of replication mutations that influence copy number and screen for mutants that improve Agrobacterium-mediated transformation (AMT) efficiency. By introducing these mutations into binary vectors within the plasmid backbone used for AMT, we observe improved transient transformation of Nicotiana benthamiana in four diverse tested origins (pVS1, RK2, pSa and BBR1). For the best-performing origin, pVS1, we isolate higher-copy-number variants that increase stable transformation efficiencies by 60–100% in Arabidopsis thaliana and 390% in the oleaginous yeast Rhodosporidium toruloides. Our work provides an easily deployable framework to generate plasmid copy number variants that will enable greater precision in prokaryotic genetic engineering, in addition to improving AMT efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

Ion irradiation induced phase transformation in gold nanocrystalline films

Gold is a noble metal typically stable as a solid in a face-centered cubic (FCC) structure under ambient conditions; however, under particular circumstances aberrant allotropes have been synthesized. In this work, we document the phase transformation of 25 nm thick nanocrystalline (NC) free-standing gold thin-film via in situ ion irradiation studied using atomic-resolution transmission electron microscopy (TEM). Utilizing precession electron diffraction (PED) techniques, crystallographic orientation and the radiation-induced relative strains were measured and furthermore used to determine that a combination of surface and radiation-induced strains lead to an FCC to hexagonal close packed (HCP) crystallographic phase transformation upon a 10 dpa radiation dose of Au 4+ ions. Contrary to previous studies, HCP phase in nanostructures of gold was stabilized and did not transform back to FCC due to a combination of size effects and defects imparted by damage cascades.

36 MATERIALS SCIENCE↗

Generation, analysis, and transformation of macro-chloroplast Potato (Solanum tuberosum) lines for chloroplast biotechnology

Abstract Chloroplast biotechnology is a route for novel crop metabolic engineering. The potential bio-confinement of transgenes, the high protein expression and the possibility to organize genes into operons represent considerable advantages that make chloroplasts valuable targets in agricultural biotechnology. In the last 3 decades, chloroplast genomes from a few economically important crops have been successfully transformed. The main bottlenecks that prevent efficient transformation in a greater number of crops include the dearth of proven selectable marker gene-selection combinations and tissue culture methods for efficient regeneration of transplastomic plants. The prospects of increasing organelle size are attractive from several perspectives, including an increase in the surface area of potential targets. As a proof-of-concept, we generated Solanum tuberosum (potato) macro-chloroplast lines overexpressing the tubulin-like GTPase protein gene FtsZ1 from Arabidopsis thaliana . Macro-chloroplast lines exhibited delayed growth at anthesis; however, at the time of harvest there was no significant difference in height between macro-chloroplast and wild-type lines. Macro-chloroplasts were successfully transformed by biolistic DNA-delivery and efficiently regenerated into homoplasmic transplastomic lines. We also demonstrated that macro-chloroplasts accumulate the same amount of heterologous protein than wild-type organelles, confirming efficient usage in plastid engineering. Advantages and limitations of using enlarge compartments in chloroplast biotechnology are discussed.

Occhialini, Alessandro (ORCID:000000021162798X)↗

Uncovering phase transformation, morphological evolution, and nanoscale color heterogeneity in tungsten oxide electrochromic materials

Controlling the electrochemical interfacial processes that govern the durability of electrochromic devices represents a key challenge in developing sustainable and cost-effective smart windows. Here, we revisit the classical tungsten trioxide (WO 3 ) materials as a platform to uncover the previously unknown interrelationship between phase transformation, morphological evolution, and nanoscale color heterogeneity in these materials. Through synchrotron/electron spectroscopic and imaging analyses, we report that the WO 3 –electrolyte interface is influenced by the tungsten dissolution and redeposition during the electrochemical cycling. The tungsten redeposition provokes the in situ crystal growth, which ultimately leads to the phase transformation from the semicrystalline WO 3 to a nanoflake-shaped, proton-trapped tungsten trioxide dihydrate (H x WO 3 · 2 H 2 O). The multidimensional quantification of the electronic structure reveals that the tungsten reduction caused by the proton trapping is heterogeneous at the nanometric scale and is responsible for the nanoscale color heterogeneity. The interplay between phase transformation, morphological evolution, and nanoscale color heterogeneity results in degraded optical modulation, switching kinetics, coulombic efficiency, and bleached-state transparency. Our results highlight that the high interfacial reactivity near the electrode surface may be the underlying mechanism for undesired bulk structural changes of electrochromic materials, and calls for fundamental studies in probing and controlling the electrode–electrolyte interfacial processes in electrochromic devices.

36 MATERIALS SCIENCE↗

Formation and transformation of iron oxy-hydroxide precursor clusters to ferrihydrite

Iron (Fe) oxy-hydroxide minerals such as ferrihydrite (Fh) are ubiquitous in Earth-surface environments and important in biogeochemical element cycling. Recent research has suggested that their formation is preceded by the precipitation of ultrasmall (~1 nm) Keggin-like Fe oxy-hydroxide clusters. However, relatively little is understood about the structure of the precursor clusters and the impacts of pH and time on their growth and transformation to more stable phases. Here, we used a new method that involves mixed flow reactors (MFR) to synthesize these Fe oxy-hydroxide precursor clusters at pH 1.0, 1.5, 2.5, and 4.5. In situ and ex situ synchrotron scattering measurements and laboratory small-angle X-ray scattering (SAXS) were used to study the structure and size of Fe oxy-hydroxide clusters and their transformation products, respectively. Results show that with increasing pH, the particle size and structural order of samples increase, forming solids that resemble 2-line Fh at pH 4.5. The experimental data were compared with X-ray pair distribution functions (PDF) calculated for a range of Fe(III) oxyhydroxide clusters, including Fe 13 Keggin isomers computed previously using density functional theory (DFT), which yielded at best only partial agreement at short range (<5 Å). Aging of the clusters synthesized at pH 1.5 and 2.5 results in growth and transformation via Ostwald ripening to mixtures of goethite (Gt) and lepidocrocite (Lp). This process was inhibited by immediately reacting the early-formed clusters with phosphate (PO 4 3– ), suggesting that oxyanion surface complexes can stabilize the initial clusters by preventing growth and crystallization to more stable phases.

58 GEOSCIENCES↗

ATAT: Astronomical Transformer for time series and Tabular data

Context. The advent of next-generation survey instruments, such as theVera C. RubinObservatory and its Legacy Survey of Space and Time (LSST), is opening a window for new research in time-domain astronomy. The Extended LSST Astronomical Time-Series Classification Challenge (ELAsTiCC) was created to test the capacity of brokers to deal with a simulated LSST stream. Aims. Our aim is to develop a next-generation model for the classification of variable astronomical objects. We describe ATAT, the Astronomical Transformer for time series And Tabular data, a classification model conceived by the ALeRCE alert broker to classify light curves from next-generation alert streams. ATAT was tested in production during the first round of the ELAsTiCC campaigns. Methods. ATAT consists of two transformer models that encode light curves and features using novel time modulation and quantile feature tokenizer mechanisms, respectively. ATAT was trained on different combinations of light curves, metadata, and features calculated over the light curves. We compare ATAT against the current ALeRCE classifier, a balanced hierarchical random forest (BHRF) trained on human-engineered features derived from light curves and metadata. Results. When trained on light curves and metadata, ATAT achieves a macro F1 score of 82.9 ± 0.4 in 20 classes, outperforming the BHRF model trained on 429 features, which achieves a macro F1 score of 79.4 ± 0.1. Conclusions. The use of transformer multimodal architectures, combining light curves and tabular data, opens new possibilities for classifying alerts from a new generation of large etendue telescopes, such as theVera C. RubinObservatory, in real-world brokering scenarios.

Astronomy & Astrophysics↗

Shock-reshock of zirconium to explore the effect of microstructure on the alpha-omega phase transformation

Phase transformations play an important role in the mechanical behavior of materials subjected to extreme loading conditions. A series of shock-reshock experiments were fielded to determine whether the phase transitions in materials are significantly enhanced or inhibited by preexisting microstructural features. Polycrystalline zirconium samples were shock loaded using gas-gun plate impact and soft recovered to examine microstructure using electron backscatter diffraction (EBSD). Drive conditions were varied to study the (hcp) alpha to (hexagonal) omega solidsolid phase transformation. Recovered samples were then subjected to a second shock loading event to determine the change in material behavior as a function of pre-shock microstructure. Crystallography of phase fragments in the final microstructure showed that prior twinning (formed during the shock to a peak stress below the transition threshold) appeared to suppress omega formation/retention after reshock. Conversely, when a material was initially shocked into the omega phase field, retained-omega was not found to have a large impact on subsequent omega formation during reshock. This suggests that nucleation and growth of omega phase are important processes, and the relative activity of nucleation vs. growth processes is modified by a pre-existing substructure. Additionally, orientation relationships reveal a reverse transformation pathway (omega to alpha) dominates the final microstructure, suggesting significant grain growth in the omega phase field is possible even for dynamic timescales.

36 MATERIALS SCIENCE↗

Multiphase phase-field approach for solid–solid phase transformations via propagating interfacial phase in HMX

In this study, a thermodynamically consistent multiphase phase-field theory has been formulated to describe temperature-induced solid–solid phase transformations via an interfacial phase. This theory satisfies all thermodynamic equilibrium and stability conditions. It allows us to formulate the analytical solutions of the interface profile, energy, width, and velocity for each of the propagating solid–melt and solid–solid interfaces. The formation of the intermediate melt during solid–solid phase transformation has been studied hundreds of degrees below melting temperature in the HMX energetic crystal. The effect of the penalizing term in the phase-field model and two nanoscale material parameters on the appearance and degree of disordering of intermediate melt has been analyzed for the non-equilibrium interface. The developed approach is applicable to phase transitions in geological, pharmaceutical, ferroelectric, colloidal, and superhard materials where phase transformations occur via the intermediate phase.

Roy, Arunabha M. (ORCID:000000034790726X)↗

Nonlinear spectral analysis of ion acoustic solitons arising from a streaming charged object using the numerical inverse scattering transform

Observations of nonlinear coherent plasma phenomena in spacecraft and terrestrial experiments often rely on visual identification of solitary modes because nonlinear coherent modes are broadband in a Fourier transform based analysis. We implement an alternative spectral decomposition known as the inverse scattering transform and demonstrate its ability to successfully isolate nonlinear modes on the homogeneous and forced Korteweg–De Vries equation which models these nonlinear modes. We also demonstrate for the first time that this decomposition is useful when forcing is applied. This is because the stable modes generated by localized forcing are similar to the homogeneous solutions where the inverse scattering transform is a rigorous decomposition. This spectral technique is then applied to simulations of ion acoustic waves generated by a 10 mm spherical debris object interacting with the ionospheric plasma orbiting at 2000 km altitude. The algorithm is found to successfully detect the resultant solitons. This demonstrates the feasibility of using this spectral technique as a real time analysis tool for screening spacecraft data for nonlinear solitary modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Measurement bias in self-heating x-ray free electron laser experiments from diffraction studies of phase transformation in titanium

X-ray self-heating is a common by-product of X-ray Free Electron Laser (XFEL) techniques that can affect targets, optics, and other irradiated materials. Diagnosis of heating and induced changes in samples may be performed using the x-ray beam itself as a probe. However, the relationship between conditions created by and inferred from x-ray irradiation is unclear and may be highly dependent on the material system under consideration. Here, we report on a simple case study of a titanium foil irradiated, heated, and probed by a MHz XFEL pulse train at 18.1 keV delivered by the European XFEL using measured x-ray diffraction to determine temperature and finite element analysis to interpret the experimental data. We find a complex relationship between apparent temperatures and sample temperature distributions that must be accounted for to adequately interpret the data, including beam averaging effects, multivalued temperatures due to sample phase transitions, and jumps and gaps in the observable temperature near phase transformations. The results have implications for studies employing x-ray probing of systems with large temperature gradients, particularly where these gradients are produced by the beam itself. Finally, this study shows the potential complexity of studying nonlinear sample behavior, such as phase transformations, where biasing effects of temperature gradients can become paramount, precluding clear observation of true transformation conditions.

Crystallography↗

Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data

Abstract Recent advances in machine learning, specifically transformer architecture, have led to significant advancements in commercial domains. These powerful models have demonstrated superior capability to learn complex relationships and often generalize better to new data and problems. This paper presents a novel transformer-powered approach for enhancing prediction accuracy in multi-modal output scenarios, where sparse experimental data is supplemented with simulation data. The proposed approach integrates transformer-based architecture with a novel graph-based hyper-parameter optimization technique. The resulting system not only effectively reduces simulation bias, but also achieves superior prediction accuracy compared to the prior method. We demonstrate the efficacy of our approach on inertial confinement fusion experiments, where only 10 shots of real-world data are available, as well as synthetic versions of these experiments.

97 MATHEMATICS AND COMPUTING↗

Charge-induced atomic strain as a predictor of structural phase transformation in rare-earth intermetallics

We present a descriptor based on charge-induced atomic strain in crystalline lattices for predicting structural phase transformations in rare-earth intermetallic compounds containing lanthanides and transition metals. The charge-induced local atomic strain was obtained from structural optimization of experimentally known crystalline phases using state of the art density-functional theory methods. The predictive power of the descriptor was evaluated on 𝑅⁢𝐸 2 ⁢In (𝑅𝐸 = rare earth) compounds, a class known for diverse phase transformations. We show that incorporating quantum-mechanical effects—such as local charge distribution, bonding, symmetry, and electronic structure—enhances the robustness of the descriptor. To gain further insight, we analyzed phononic and electronic behavior in Y 2 ⁢In and demonstrated that experimental phase transformations are captured only when atomic strain effects are included. The descriptor was further used to predict structural phase changes in (Y⁢b 1–𝑥 ⁢E⁢r 𝑥 ) 2 ⁢In and G⁡d 2 ⁡(I⁢n 1–𝑥⁢ A⁢l 𝑥 ), with predictions confirmed by x-ray powder diffraction. Here, while the current study is focused on lanthanide-based intermetallics, the underlying principles of the descriptor suggest potential applicability to other closely related classes of rare-earth intermetallics.

Density functional theory↗

Transformer-based operator learning framework for self-energy in strongly correlated systems

We introduce Σ-Attention, a transformer-based operator-learning framework for approximating the self-energy operator of strongly correlated electronic systems. By creating a batched dataset that combines results from three complementary approaches, i.e., many-body perturbation theory, strong-coupling expansion, and exact diagonalization, each effective in specific parameter regimes, Σ-Attention is applied to learn an accurate approximation for the self-energy operator that is valid across a wide range of parameter regimes. This hybrid strategy leverages the strengths of existing methods while relying on the transformer's ability to generalize beyond individual limitations. More importantly, the scalability of the transformer architecture allows the learned self-energy to be extended to systems with larger sizes, leading to much improved computational scaling. Using the one-dimensional Hubbard model, we demonstrate that Σ-Attention can accurately predict the Matsubara Green's function of large systems with a wide range of coupling strength. Our framework offers a promising and scalable pathway for studying strongly correlated systems with many possible generalizations.

Zhu, Yuanran↗

Backpropagated frame transformation theory: A reformulation

In this work, the energy-dependent frame transformation theory of Gao and Greene [H. Gao and C. H. Greene, Phys. Rev. A 42, 6946 (1990)] is extended to yield a quantitatively accurate description of the dissociative recombination process. Evidence is presented to show that direct application of the original theory leads to inaccurate cross sections. A major revision, based on an interaction-free backpropagation of the Born-Oppenheimer solutions, markedly improves the frame transformation theory, reducing its average error by orders of magnitude. The original theory and its extension are tested on the previously explored two-dimensional (2D) model that is tailored to describe the singlet ungerade states of molecular hydrogen. The 2D model can be solved exactly (within the numerical accuracy) without implementing the Born-Oppenheimer approximation. These exact results then serve as a benchmark for the frame transformation theory developed in this paper.

74 ATOMIC AND MOLECULAR PHYSICS↗

X-ray diffraction study of phase transformation dynamics of Fe and Fe-Si alloys along the shock Hugoniot using an x-ray free electron laser

The x-ray free electron laser (XFEL) enables probing a highly compressed material response at the subnanosecond timescale. Here we exploit the ultrafast XFEL pulse to combine reflection x-ray diffraction and laser-driven shock compression to perform a study of the phase transformation and stability in Fe and Fe-Si alloys. Our approach enables us to observe that solid-solid phase transformations occur in Fe and Fe- Si 8.5 wt % in ≤ 130 ps at ~ 130 GPa; no transformation is observed in Fe- Si 16 wt % up to 110 GPa. Density functional theory calculations predict similar phase relations.

36 MATERIALS SCIENCE↗

Changes in electric field noise due to thermal transformation of a surface ion trap

Here, we aim to illuminate how the microscopic properties of a metal surface map to its electric field noise characteristics. In our system, prolonged heat treatments of a metal film can induce a rise in the magnitude of the electric field noise generated by the surface of that film. We refer to this heat-induced rise in noise magnitude as a thermal transformation. The underlying physics of this thermal transformation process is explored through a series of heating, milling, and electron treatments performed on a single surface ion trap. Between these treatments, 40 Ca + ions trapped 70 μm above the surface of the metal are used as detectors to monitor the electric field noise at frequencies close to 1 MHz. An Auger spectrometer is used to track changes in the composition of the contaminated metal surface. With these tools we investigate contaminant deposition, chemical reactions, and atomic restructuring as possible drivers of thermal transformations.

36 MATERIALS SCIENCE↗

Inference offers a metric to constrain dynamical models of neutrino flavor transformation

The multimessenger astrophysics of compact objects presents a vast range of environments where neutrino flavor transformation may occur and may be important for nucleosynthesis, dynamics, and a detected neutrino signal. Development of efficient techniques for surveying flavor evolution solution spaces in these diverse environments, which augment and complement existing sophisticated computational tools, could leverage progress in this field. To this end we continue our exploration of statistical data assimilation (SDA) to identify solutions to a small-scale model of neutrino flavor transformation. SDA is a machine learning formula wherein a dynamical model is assumed to generate any measured quantities. Specifically, we use an optimization formulation of SDA wherein a cost function is extremized via the variational method. Regions of state space in which the extremization identifies the global minimum of the cost function will correspond to parameter regimes in which a model solution can exist. Our example study seeks to infer the flavor transformation histories of two monoenergetic neutrino beams coherently interacting with each other and with a matter background. We require that the solution be consistent with measured neutrino flavor fluxes at the point of detection, and with constraints placed upon the flavor content at various locations along their trajectories, such as the point of emission, and the locations of the Mikheyev-Smirnov-Wolfenstein resonances. We show how the procedure efficiently identifies solution regimes and rules out regimes where solutions are infeasible. Overall, results in this work intimate the promise of this “variational annealing” methodology to efficiently probe an array of fundamental questions that traditional numerical simulation codes render difficult to access.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗