88 research outputs found

    Solid Solution Strengthened Fe Alloys

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    Iron (Fe)-based alloys (such as steel) are widely used structural materials in industry. Numerous methods have been applied to improve their mechanical properties. In this study, we used a technique know as magnetron sputtering to deposit various Fe-based binary alloy coatings to investigate the influence of solutes on solid solution hardening. Several factors contribute to the solid solution hardening of the alloys, such as composition, atomic radius, modulus, and lattice parameter. After preliminary calculations and analysis, we selected several solutes, including molybdenum (Mo), niobium (Nb), and zirconium (Zr). The compositions of solutes were varied to be 2.5, 5, 8 atomic %. Our nanoindentation hardness measurements show that among the three solid solution alloys, Fe-Zr has the highest hardness. The influences of solutes on microstructural and hardness evolution in these solid solution alloys are discussed

    Strengthening mechanisms of highly textured Cu/Co and Ag/Al nanolayers with high density twins and stacking faults

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    Metallic nanolayers have attracted increasing attention as they provide unique opportunity to investigate the influence of layer interfaces on mechanical properties of metallic nanocomposites. High strength is often achieved at small (several nm) individual layer thickness (h). Recently, we discovered high-density stacking faults in FCC Co in highly (100) textured Cu/Co multilayers. In contrast in (111) textured Cu/Co nanolayers, Co remained its stable HCP structure at large h. The two Cu/Co systems have very different size dependent strengthening behavior. HCP Cu/Co has much greater peak strength than FCC Cu/Co. The large discrepancy in their strengthening mechanisms is discussed and compared to those of highly textured Cu/Ni multilayer systems. In another highly textured nanolayers system, Ag/Al, epitaxial interfaces were observed across various h (1‑200 nm). High-density nanotwins and stacking faults appear in both Ag and Al layers, and stacking fault density in Al increases sharply with decreasing h. At smaller h, hardness of Ag/Al nanolayers increases monotonically and no softening was observed. These studies allow us to investigate the influence of layer interfaces, stacking faults and nanotwins on strengthening mechanisms of metallic nanolayers. This research is funded by DOE–OBES

    End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning

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    The availability of tera-byte scale experiment data calls for AI driven approaches which automatically discover scientific models from data. Nonetheless, significant challenges present in AI-driven scientific discovery: (i) The annotation of large scale datasets requires fundamental re-thinking in developing scalable crowdsourcing tools. (ii) The learning of scientific models from data calls for innovations beyond black-box neural nets. (iii) Novel visualization and diagnosis tools are needed for the collaboration of experimental and theoretical physicists, and computer scientists. We present Phase-Field-Lab platform for end-to-end phase field model discovery, which automatically discovers phase field physics models from experiment data, integrating experimentation, crowdsourcing, simulation and learning. Phase-Field-Lab combines (i) a streamlined annotation tool which reduces the annotation time (by ~50-75%), while increasing annotation accuracy compared to baseline; (ii) an end-to-end neural model which automatically learns phase field models from data by embedding phase field simulation and existing domain knowledge into learning; and (iii) novel interfaces and visualizations to integrate our platform into the scientific discovery cycle of domain scientists. Our platform is deployed in the analysis of nano-structure evolution in materials under extreme conditions (high temperature and irradiation). Our approach reveals new properties of nano-void defects, which otherwise cannot be detected via manual analysis

    PREPARATION OF HIGH-STRENGTH NANOMETER SCALE TWINNED COATING AND FOIL

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    Very high strength single phase stainless steel coating has been prepared by magnetron sputtering onto a substrate. The coating has a unique microstructure of nanometer spaced twins that are parallel to each other and to the substrate surface. For cases where the coating and substrate do not bind strongly, the coating can be peeled off to provide foil

    SInViG: A Self-Evolving Interactive Visual Agent for Human-Robot Interaction

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    Linguistic ambiguity is ubiquitous in our daily lives. Previous works adopted interaction between robots and humans for language disambiguation. Nevertheless, when interactive robots are deployed in daily environments, there are significant challenges for natural human-robot interaction, stemming from complex and unpredictable visual inputs, open-ended interaction, and diverse user demands. In this paper, we present SInViG, which is a self-evolving interactive visual agent for human-robot interaction based on natural languages, aiming to resolve language ambiguity, if any, through multi-turn visual-language dialogues. It continuously and automatically learns from unlabeled images and large language models, without human intervention, to be more robust against visual and linguistic complexity. Benefiting from self-evolving, it sets new state-of-the-art on several interactive visual grounding benchmarks. Moreover, our human-robot interaction experiments show that the evolved models consistently acquire more and more preferences from human users. Besides, we also deployed our model on a Franka robot for interactive manipulation tasks. Results demonstrate that our model can follow diverse user instructions and interact naturally with humans in natural language, despite the complexity and disturbance of the environment

    Interface Effects on He Ion Irradiation in Nanostructured Materials

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    In advanced fission and fusion reactors, structural materials suffer from high dose irradiation by energetic particles and are subject to severe microstructure damage. He atoms, as a byproduct of the (n) transmutation reaction, could accumulate to form deleterious cavities, which accelerate radiation-induced embrittlement, swelling and surface deterioration, ultimately degrade the service lifetime of reactor materials. Extensive studies have been performed to explore the strategies that can mitigate He ion irradiation damage. Recently, nanostructured materials have received broad attention because they contain abundant interfaces that are efficient sinks for radiation-induced defects. In this review, we summarize and analyze the current understandings on interface effects on He ion irradiation in nanostructured materials. Some key challenges and research directions are highlighted for studying the interface effects on radiation damage in nanostructured materials

    High strength, deformable nanotwinned Al–Co alloys

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    Aluminum (Al) alloys have been widely used in the transportation industry. However, most highstrength Al alloys to date have limited mechanical strength, on the order of a few hundred MPa, which is much lower than the flow stress of high-strength steels. In this study, we show the fabrication of nanocrystalline Al alloys with high-density growth twins enabled by a few atomic percent of Co solute. In situ uniaxial compression tests show that the flow stress of Al–Co solid solution alloys exceeds 1.5 GPa, while good work hardening capability is maintained. This study provides a new perspective on the design of high-strength Al alloys for various applications

    Vision-Language Foundation Models as Effective Robot Imitators

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    Recent progress in vision language foundation models has shown their ability to understand multimodal data and resolve complicated vision language tasks, including robotics manipulation. We seek a straightforward way of making use of existing vision-language models (VLMs) with simple fine-tuning on robotics data. To this end, we derive a simple and novel vision-language manipulation framework, dubbed RoboFlamingo, built upon the open-source VLMs, OpenFlamingo. Unlike prior works, RoboFlamingo utilizes pre-trained VLMs for single-step vision-language comprehension, models sequential history information with an explicit policy head, and is slightly fine-tuned by imitation learning only on language-conditioned manipulation datasets. Such a decomposition provides RoboFlamingo the flexibility for open-loop control and deployment on low-performance platforms. By exceeding the state-of-the-art performance with a large margin on the tested benchmark, we show RoboFlamingo can be an effective and competitive alternative to adapt VLMs to robot control. Our extensive experimental results also reveal several interesting conclusions regarding the behavior of different pre-trained VLMs on manipulation tasks. We believe RoboFlamingo has the potential to be a cost-effective and easy-to-use solution for robotics manipulation, empowering everyone with the ability to fine-tune their own robotics policy.Comment: Fix typos. Project page: https://roboflamingo.github.i

    Field-induced mass transport phenomena in flash sintered high temperature ceramics explored by in situ SEM and TEM

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    Flash sintering has attracted significant attention lately as its remarkable rapid densification process at low sintering temperature leads to the retention of fine grains and enhanced dielectric properties. However, the underlying mechanism of flash sintering and mechanical behaviors of flash-sintered ceramics remain poorly understood. Here, we report the microstructure of flash-sintered yttria-stabilized zirconia (YSZ) and TiO2 by transmission electron microscope (TEM) and their high temperature in-situ micropillar compression studies inside a scanning electron microscope (SEM). Our studies on flash-sintered YSZ show that YSZ exhibits high inelastic strain (~ 8%) primarily due to phase transformation toughening below 400°C. At higher temperatures, crack nucleation and propagation are significantly retarded and prominent plasticity arises mainly from dislocation activities. The holding time and current density limit after the onset of flash for flash-sintered TiO2 significantly affect the microstructure and mechanical behavior. High dislocation density and stacking faults have been observed in the flash-sintered TiO2 under TEM. The presence of high-density defects generated during flash sintering plays a major role in the overall microstructure and mechanical behavior of ceramics

    Anisotropic optical and magnetic response in self-assembled TiN-CoFe\u3csub\u3e2\u3c/sub\u3e nanocomposites

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    Transition metal nitrides (e.g., TiN) have shown tremendous promise in optical metamaterials for nanophotonic devices due to their plasmonic properties comparable to noble metals and superior high temperature stability. Vertically aligned nanocomposites (VANs) offer a great platform for combining two dissimilar functional materials with a one-step deposition technique toward multifunctionality integration and strong structural/property anisotropy. Here we report a two-phase nanocomposite design combining ferromagnetic CoFe2 nanosheets in the plasmonic TiN matrix as a new hybrid plasmonic metamaterial. The hybrid metamaterials exhibit obvious anisotropic optical and magnetic responses, as well as a pronounced magneto-optical coupling response evidenced by MOKE measurement, owing to the novel vertically aligned structure. This work demonstrates a new TiN-based metamaterial with anisotropic properties and multi-functionality towards optical switchable spintronics, magnetic sensors and integrated optic
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