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Active nematics are a paradigmatic active matter system which generate micron-scale patterns and flows. Here we show that their control can be enabled by model-free techniques such as reinforcement learning.
The interaction among multiple intense ultrashort laser pulses and solids is known to provide a regular nanoscale surface corrugation. A coupled mechanism has been identified that operates in a specific range of fluences in GaAs that exhibits transient loss of the imaginary part of the dielectric function and Χ 2 , which produces a unique corrugation known as high spatial frequency laser induced periodic surface structures (HSFL). The final structures have 180 nm periods, and their alignment perpendicular to the laser polarization is first observed in an intermediate morphology with correlation distances of 150±40 nm. Quantum molecular dynamics simulations suggest that HSFL self-assembly is initiated when the intense laser field softens the interatomic binding potential, which leads to an ultrafast generation of point defects. The morphological evolution begins as self-interstitial diffusion, driven by stress relaxation, to the surface producing 1–2 nm tall islands. An ab initio calculation of excited electron concentration combined with a Drude-Lorentz model of the excited GaAs dielectric function is used to determine that the conditions for SPP coupling at HSFL formation fluences are both satisfied and occur at wavelengths that are imprinted into the observed surface morphologies. The evolution of these morphologies is reported on as the interplay between surface plasmon polaritons that localize defect generation within the structures present on the previous laser exposure and stress relaxation driven defect diffusion.
Optical and phonon interactions of Ga 2 O 3 thin films with nanocrystalline morphology were studied at extreme temperatures. The films were grown using a sputtering technique and analyzed via temperature response transmission, Raman scattering, and high-resolution deep-UV photoluminescence (PL). Raman modes indicated that the structure corresponds to the β-phase. The optical-gap at the range of 77–620 K exhibited a redshift of ~200 meV, with a temperature coefficient of ~0.4 meV/K. The optical-gap at room-temperature is 4.85 eV. The electron–phonon interaction model at that temperature range pointed to a low energy phonon, ~31 meV, that is involved in the thermal properties of the optical-gap. Detailed Urbach energy analysis indicated that defects are the dominant mechanism controlling the band-edge characteristics even at an elevated temperature regime where phonon dominance is usually expected. Defects are attributed to the disordered forms of graphite that were detected via Raman scattering and to the granular morphology of the film. A deep-UV laser with an above bandgap exaction line of 5.1 eV was employed to map the PL of the films. The highly resolved spectra, even at room-temperature, show a strong emission of ~3.56 eV attributed to self-trapped holes (STHs). The STH is discussed and modeled in terms of the self-trapped exciton. Moreover, a very distinct but low-intensity emission was found at 4.85 eV that agrees with the value of the optical-gap and is attributed to bandgap recombination. The intensity ratio between the STH and that of the bandgap was found to be 6:1.
Highlights: • Ectopic expression of DTNKS induces wing and eye defects. • DTNKS positively regulates cell apoptosis. • DTNKS regulates apoptosis by controlling JNK signaling activity. Programmed cell death (PCD), or apoptosis, plays essential roles in various cellular and developmental processes, and dysregulation of apoptosis causes many diseases. Thus, regulation of apoptotic process is very important. Drosophila tankyrase (DTNKS) is an evolutionarily conserved protein with poly(ADP-ribose) polymerase activity. In mammalian cells, tankyrases (TNKSs) have been reported to regulate cell death. To determine whether DTNKS plays function in inducing apoptosis in in vivo development, we used Drosophila as a model system and generated transgenic flies expressing DTNKS. We show that ectopic expression of DTNKS promotes caspase-dependent apoptosis and knockdown of DTNKS by RNAi dramatically alleviates apoptotic defect caused by ectopic expression of pro-apoptotic protein hid or rpr in the adult eye. Moreover, our result shows that ectopic expression of DTNKS triggers the activation of c-Jun N-terminal kinase (JNK) signaling, which is required for DTNKS-mediated apoptosis. Taken together, our finding identifies the role of DTNKS in regulating apoptosis by activating JNK signaling in Drosophila.
Predicting the onset and characteristics of brittle fracture is important for a wide range of engineering and geological material applications. In this paper, we study important aspects of brittle fracture in α-quartz by phase-field modeling and experiments using a top-down approach. In the modeling framework, the work term in the Griffith energy balance is replaced with internal energy contributions that represent surface energy, thermal energy, and elastic strain energy stored in defects. This allows parametrization of individual energy contributions in terms of internal state variables and keeps track of energy partitioning after the onset of fracture. The path and history dependence of fracture is included in evolution laws for internal state variables, e.g., entropy evolution, while the energy remains a true potential. In the experimental part, dynamic compression experiments coupled with X-ray phase contrast imaging are performed on cube-like samples with a hole. In the top-down analysis, dynamic compression and three point bending experiments from the literature are simulated with the developed phase-field damage model. In conclusion, the fitted model highlights the strain rate, size, and stress state dependence of damage nucleation and evolution in single crystal α-quartz.
In this work, the creep behavior of HT9 steel in both thermal and irradiation environments is predicted using an integrated modeling framework. Multiple physical mechanisms such as diffusional creep and dislocation climb are incorporated into crystal plasticity calculations using the Visco-Plastic Self-Consistent (VPSC) approach. Climb velocities are informed by mean field rate theory laws in place of empirical power law formulations. More interestingly, the climb velocities explicitly consider the contribution of irradiation-induced point defects, i.e., stress induced preferential absorption (SIPA) effect. The developed expressions are shown to apply under conventional thermal creep and to the more complex irradiation conditions as well. This physically-informed, mechanism-based model is used to simulate the creep strain evolution of HT9 pressurized tubes under various loading conditions. Furthermore, it is demonstrated that the experimental behavior of this material reported in the literature is well described by this theoretical framework. The role of each relevant mechanism is discussed.
In this paper, we present the first demonstration of single-step gear manufacturing via an innovative in-situ friction stir forging approach. This novel process is a natural extension to the friction stir processing technique and relies on shear and normal stresses to form the complex shapes. Friction stir welding pin tool with shoulder is plunged at high revolutions per minute (rpm) into the sample to heat it to the desired temperature and enable plastic flow. Then, the tool is forged at high plunge rate to form the desired structurally-sound and defect free complex shapes. To better visualize the process the experiments are complemented by a 3D thermomechanically coupled, smoothed particle hydrodynamics (SPH) model to understand the material flow pattern both radially and through thickness in the gear teeth, plastic strain distribution, and temperature profile. We have demonstrated application of I-FSF to inherently poor formable AZ31 Mg, AA 7075-T6, and AA5083–10 vol% TiB 2 composite and fabricated 14-tooth spur gears from these materials with minimal farther machining. In conclusion, microstructure of the forged gears exhibited a directional material flow pattern due to the normal forging action and refinement of grains to 6–13 μm through dynamically recrystallization across the radial, through-thickness direction, which is in good agreement with the corresponding SPH simulation results.
Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.
Utilization of core–shell rather than monometallic nanocrystals (NCs) facilitates fine-tuning of NC properties for applications. However, compositional evolution via intermixing can degrade these properties prompting recent experimental studies. We develop an atomistic-level stochastic model for vacancy-mediated intermixing exploiting a formalism which allows incorporation at an ab initio density functional theory level of not just the thermodynamics of vacancy formation, but also relevant diffusion barriers for a vast number of possible local environments (in the core and in the shell, at the interface, and in the intermixed phase). This facilitates a predictive treatment and comprehensive understanding of intermixing on the relevant time scale (e.g., 10 1 –10 3 s). In contrast, previous modeling at the atomistic level utilized only unrealistic generic prescriptions of barriers or employed simplified continuum treatments. For Au@Ag octahedral core–cubic shell NCs, our modeling not only captures the experimentally observed rate or time scale for intermixing of ~100 s at 450 °C for 60 nm NCs, but also elucidates the underlying rate controlling processes and the effective intermixing barrier.
Abstract The nucleation and propagation of dislocations is an ubiquitous process that accompanies the plastic deformation of materials. Consequently, following the first visualization of dislocations over 50 years ago with the advent of the first transmission electron microscopes, significant effort has been invested in tailoring material response through defect engineering and control. To accomplish this more effectively, the ability to identify and characterize defect structure and strain following external stimulus is vital. Here, using X-ray Bragg coherent diffraction imaging, we describe the first direct 3D X-ray imaging of the strain field surrounding a line defect within a grain of free-standing nanocrystalline material following tensile loading. By integrating the observed 3D structure into an atomistic model, we show that the measured strain field corresponds to a screw dislocation.
Abstract Elastic nonlinearity observed in consolidated granular media can be attributed to the combination of slow and fast effects, which give rise to hysteresis and relaxation of both modulus and damping after the sample is perturbed. A consequence is a high level of complexity in the measurements of the sample linear and nonlinear elastic parameters. The results of experiments are dependent on the experimental protocol that is adopted to measure the relevant quantities and it is hard to quantify parameters with accuracy and repeatability. Here we focus on examining Nonlinear Resonant Ultrasound Spectroscopy, showing experimentally the role of slow dynamics in the process and quantifying/discussing its influence on the quantification of nonlinearity. We also propose a model to describe the process, which shows that different contributions to nonlinearity (e.g., classical and hysteretic) could be due to physical features (defects) relaxing with different relaxation times.
We present a perspective on recent observations of the photoinduced phase separation of halides in multi-component lead-halide perovskites. The spontaneous phase separation of an initial homogeneous solid solution under steady-state illumination conditions is found experimentally to be reversible, stochastic, weakly dependent on morphology, yet strongly dependent on composition and thermodynamic state. Regions enriched in a specific halide species that form upon phase separation are self-limiting in size, pinned to specific compositions, and grow in number in proportion to the steady-state carrier concentration until saturation. These empirical observations of robustness rule out explanations based on specific defect structures and point to the local modulation of an existing miscibility phase transition in the presence of excess charge carriers. A model for rationalizing existing observations based on the coupling between composition, strain, and charge density fluctuations through the formation of polarons is reviewed.
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X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.
We report on the use of atom probe tomography (APT), scanning transmission electron microscopy (STEM), and secondary ion mass spectroscopy (SIMS) to characterize doping profiles in the base region of SiGe HBT devices. We compare SIMS profiles obtained from large regions (400 um 2 ) of the device wafer to profiles obtained from individual devices of different emitter window widths (0.25 and 0.18 um 2 ) using APT. From this comparison we show how APT can provide a deeper insight into evaluating the fabrication process and its effects on electrical models of device performance and enabling the building of higher performance systems. We also demonstrate that APT can be used to characterize defects within the intrinsic regions of a device.
Here, the motion of line defects (dislocations) has been studied for more than 60 years, but the maximum speed at which they can move is unresolved. Recent models and atomistic simulations predict the existence of a limiting velocity of dislocation motion between the transonic and subsonic ranges at which the self-energy of dislocation diverges, though they do not deny the possibility of the transonic dislocations. We used femtosecond x-ray radiography to track ultrafast dislocation motion in shock-compressed single-crystal diamond. By visualizing stacking faults extending faster than the slowest sound wave speed of diamond, we show the evidence of partial dislocations at their leading edge moving transonically. Understanding the upper limit of dislocation mobility in crystals is essential to accurately model, predict, and control the mechanical properties of materials under extreme conditions.
The paper deals with the initiation, growth, and possible arrest of fracture in shell structures containing initial defects which may be approximated by an isolated part-through crack. The main study is restricted to the structures in which the net section of the shell wall around the defect zone is fully yielded. The problem is solved by using an 8th order shallow shell theory with a conventional plastic strip model to account for the plastic deformations. Using the critical COD or the plastic instability as fracture criterion, the results are applied to the fracture propagation and arrest in shells. The calculated results are then compared with those obtained from the experiments on zircaloy, aluminum, and steel pipes.
A two-dimensional model for in-plane vibrations of a cantilever plate with a non-symmetrical damage is used in the context of defect identification in materials with piezoelectric ceramic patches bonded to their surface. These patches can act both as actuators and sensors in a self-analyzing fashion, which is a characteristic of smart materials. A Galerkin method is used to approximate the dynamic response of these structures. The natural frequency shifts due to the damage are estimated numerically and compared to experimental data obtained from tests on cantilever aluminum plate-like structures damaged at different locations with defects of different depths. The damage location and extent are determined by an enhanced least square identification method. Efficacy of the frequency shift based algorithms is demonstrated using experimental data.