Twinning in crystalline materials plays an important role in many transformation and deformation processes, where underlying mechanisms can be strongly influenced by the structural, energetic and kinetic properties of associated twin boundaries (TBs). While these properties are well characterized in common cases, the possibility that TBs can display multiple complexions with distinct properties, and phase transitions between them, has not been widely explored, even though such phenomena are established in a few more general grain boundaries. We report experimental findings that {11-24} TBs in titanium display a thick interfacial region with crystalline structure distinct from the bulk. First-principles calculations establish that this complexion is linked to a metastable polymorph of titanium, and exhibits behavior consistent with a solid-state wetting transition with compressive strain, and a first-order structural transition under tension. The findings document rich TB complexion behavior in an elemental metal, with important implications for mechanical behavior and phase-transformation pathways.

Metastability

Phase boundary

10.48550/arxiv.2103.06194

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Research on global calibration method of large-scene multi-vision sensors in wheel alignment

Measurement Science and Technology (2022)

Limei Song Ruohan Wang Enze Chen Yangang Yang Xinjun Zhu

Abstract Wheel measurement and positioning technology is an important technology in vehicle production, and is of great importance for the safety of vehicles. At present, visual measurement and other methods are widely used in automotive production and inspection, but these methods are limited to the measurement of regular-sized vehicles. There is no effective solution to the problem of wheel alignment for large special-purpose vehicles with multiple tires. In order to solve the wheel positioning problem of large-size special-purpose vehicles, this paper designs a vision measurement system for wheel parameters in large scenes by combining vision sensors with linear motion guides to extend the vision measurement range and complete the global calibration of multiple-vision sensors with the help of laser trackers and self-researched stereo targets. This paper proposes an Elementary–Advance global calibration algorithm to improve the accuracy of coordinate system conversion during global calibration. This paper establishes a correction model for the measurement errors that exist in the initial global calibration process, and iterates the objective function to optimize the coordinate system conversion parameters between multiple vision sensors to improve the measurement accuracy of the system. The experimental results show that the goodness of fit and the accuracy of fit for the feature cylinder are 98.31% and 99.03% based on the global calibration method of this paper. The standard deviation of measurements for the standard ruler of the Inva alloy is less than 0.391 mm in the large dimensional range of 6050 mm × 3500 mm × 800 mm. Finally, by comparing the measurement results with the TrukCam four-wheel alignment instrument, the feasibility of the visual measurement system designed in this paper for large scenarios of wheel parameters is verified, and the measurement accuracy requirements for four-wheel alignment of special-purpose vehicles are met.

Machine Vision

Laser tracker

10.1088/1361-6501/ac7c5a

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Multiscale modelling of back-stress during equal-channel angular pressing

REVIEWS ON ADVANCED MATERIALS SCIENCE (2010)

Enze Chen Laurent Duchêne Anne Habraken Bert Verlinden

Equal-channel angular pressing (ECAP) is a well known process to produce ultrafine- grained materials. The mechanical properties of these materials, including a compression- tension asymmetry and a transient hardening saturation in the beginning of the flow curve, largely depend on the evolution of the microstructure during ECAP. Consequently, the back- stress induced by the dislocation microstructure exhibits kinematic hardening at the macroscopic scale. In this paper, commercial purity aluminium AA1050 is processed by ECAP route C. Tensile and compression specimens are machined from the post-ECAP samples. The back-stress level is estimated from the different yielding strengths of tensile tests and compression tests. Then two different models, a macroscopic phenomenological Teodosiu-type model and a microscopic dislocation-based multi-layer model, are used to predict the back-stress values. A cUdBVC4b4)UdUbcVBbGUBTBcYeuc)BTU?YcYTUAdYVYUTVbB)cY)C?UcXU4bdUcdc�64ecSXYAWUbdUcdc and orthogonal tests. The dislocation-based multi-layer model is based on the Estrin-To th TYc?BS4dYBA)BTU?4ATF4ej4iucYAdb4Wb4Ae?4bR4S(�cdbUcc)BTU?�GXUCbUTYSdUT4ATUhCUbY)UAd4? back-stresses due to ECAP are compared and critically evaluated.

Hardening (computing)

Flow stress

Work hardening

Source

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Charge Prediction by Constitutive Elements Matching of Crimes

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (2022)

Jie Zhao Ziyu Guan Cai Xu Wei Zhao Enze Chen

Charge prediction is to automatically predict the judgemental charges for legal cases. To convict a person/unit of a charge, the case description must contain matching instances of the constitutive elements (CEs) of that charge. This knowledge of CEs is a valuable guide for the judge in making final decisions. However, it is far from fully exploited for charge prediction in the literature. In this paper we propose a novel method named Constitutive Elements-guided Charge Prediction (CECP). CECP mimics human's charge identification process to extract potential instances of CEs and generate predictions accordingly. It avoids laborious labeling of matching instances of CEs by a novel reinforcement learning module which progressively selects potentially matching sentences for CEs and evaluates their relevance. The final prediction is generated based on the selected sentences and their relevant CEs. Experiments on two real-world datasets show the superiority of CECP over competitive baselines.

Relevance

Identification

10.24963/ijcai.2022/627

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Hierarchy of defects in near-Σ5 tilt grain boundaries in copper studied by length-scale bridging electron microscopy

Acta Materialia (2025)

Hui Ding Ahmad Akbari Enze Chen Harald Rösner Timofey Frolov

10.1016/j.actamat.2025.120778

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Transferable Kinetic Monte Carlo Models with Thousands of Reactions Learned from Molecular Dynamics Simulations

The Journal of Physical Chemistry A (2019)

Enze Chen Qian Yang Vincent Dufour-Décieux Carlos Sing‐Long Rodrigo Freitas

Molecular dynamics (MD) simulation of complex chemistry typically involves thousands of atoms propagating over millions of time steps, generating a wealth of data. Traditionally these data are used to calculate some aggregate properties of the system and then discarded, but we propose that these data can be reused to study related chemical systems. Using approximate chemical kinetic models and methods from statistical learning, we study hydrocarbon chemistries under extreme thermodynamic conditions. We discover that a single MD simulation can contain sufficient information about reactions and rates to predict the dynamics of related yet different chemical systems using kinetic Monte Carlo (KMC) simulation. Our learned KMC models identify thousands of reactions and run 4 orders of magnitude faster than MD. The transferability of these models suggests that we can viably reuse data from existing MD simulations to accelerate future simulation studies and reduce the number of new MD simulations required.

Kinetic Monte Carlo

Transferability

10.1021/acs.jpca.8b09947

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Citations (13)