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The electro-chemo-mechanical coupling at the solid-liquid interfaces and its applications to electrocatalysis

DENG Qibo, JIA Hanxing, YANG Bo, QI Zhengpan, ZHANG Zheyi, LEE Alamusi, HU Ning

2022, 52(2): 221-252. doi: 10.6052/1000-0992-21-042

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Abstract:
Many advanced catalysts have considered the positive effect of surface mechanics during their design and preparation, in which the high active atoms on the surface are under different strain states. Strain can directly change the bandgap of a metal, which has a significant impact on the electrochemical reaction that occurred at the electrocatalyst surface. It is a new idea and effective strategy to improve the electrocatalytic activity of materials. Traditional strain engineering based on material strategies is difficult to accurately quantify the strain value of an active layer, which results in the unclear recognition of the relation between strain and electrocatalytic activity. The strain induced by the alternating load has the advantages of tunable amplitude and frequency as well as continuous modulation. From the classical thermodynamic of solid-liquid interface, this review briefly introduces the electro-chemo-mechanical coupling in electrocatalytic systems, and summarizes the experimental methods and the analysis methods in use for studying the effect of strain on electrocatalytic reactivity. It is also discussed in detail on the mechanism of strain on the electrocatalytic reaction at the metal surface under alternating load. Finally, the development and application of surface mechanics in electrochemical systems are prospected from the perspective of mechanics.

Advances in flexible multibody dynamics of human musculoskeletal systems

GUO Jianqiao, WANG Yanbing, TIAN Qiang, REN Gexue, HU Haiyan

2022, 52(2): 253-310. doi: 10.6052/1000-0992-21-056

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The human system consists of bones, skeletal muscles, and joints, so the system model in mechanics is a typical flexible multi-body system. The study on musculoskeletal multi-body dynamics mainly aims to determine muscle forces and joint moments together with the effect of their actions during human locomotion. Thus, it is a multi-disciplinary subject between dynamics and biomechanics. Musculoskeletal multi-body models have seen successful applications in many fields, such as clinical research, sports engineering, military training, and ergonomics. The simulation results of these models can provide important data for improving physical performances, reducing joint loading and energy consumption, preventing sports injuries, and accelerating rehabilitation processes. In turn, the achievement of these human-related techniques provides the study of musculoskeletal dynamics with numerous new challenges. This review surveys the literature on the multi-body dynamics modeling of human musculoskeletal systems. Its contents include the functional anatomy and biomechanical models of the skeletal muscle, neuromuscular control strategies, and the computational frameworks for musculoskeletal modeling. The paper also reviews several typical applications of musculoskeletal modeling in the fields of gait analysis, anti-G straining maneuver of pilots, and mandibular surgical planning. Compared with classical mechanical systems in mechanical engineering, the human musculoskeletal system has the characteristics of active force and redundancy control. However, existing muscle models cannot simultaneously consider the anatomical structures and three-dimensional geometries of the muscles together with their biochemical force-generating mechanism. Meanwhile, most studies have utilized the static optimization assumption to deal with muscle recruitments, neglecting the equilibrium between musculotendon forces and contraction dynamics. So far, It is still a challenging task to build subject-specific musculoskeletal models based on non-invasive in vivo measurements. Future studies on musculoskeletal multi-body dynamics will achieve a more precise, intelligent, and subject-specific modeling framework, which leads to a hot research topic involving interdisciplinary collaborations of dynamics and biomechanics.

A review on the mechanical stability of flexible perovskite solar cells

ZHANG Meihe, LI Zhihao, LI Honggang, ZHANG Chao

2022, 52(2): 311-338. doi: 10.6052/1000-0992-21-057

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Perovskite solar cells (PSCs) attract great attention from the scientific community due to their low cost, high performance, and rapid increase in photoelectric conversion efficiency (PCE) from 3.8% to 25.5%. Compared with rigid perovskite solar cells, flexible perovskite solar cells (FPSCs) deposited on polymer substrates are considered to be more suitable for commercial application with their intrinsic advantages in lightweight and bendability. However, a gap presents between the photovoltaic performance of FPSCs and rigid PSCs, and the mechanical instability of FPSCs is still a critical concern for commercial application. In this review, the recent research progress on improving the mechanical stability of FPSCs is summarized and discussed through two main aspects: particle regulation and structure innovation, which could provide valuable suggestions for future research efforts in this area and the engineering application of FPSCs. On the other hand, the research advances in FPSCs-based self-powering sensors are introduced and discussed, illustrating the next-stage breakthroughs, possible innovation designs, and future developments of FPSCs.

Neurological disease and cognitive dynamics (I): Dynamics and control of epileptic seizures

HAN Fang, FAN Denggui, ZHANG Liyuan, WANG Qingyun

2022, 52(2): 339-396. doi: 10.6052/1000-0992-21-064

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Studies have shown that the process of epileptic seizures is closely related to the nonlinear dynamics of the nervous system itself. Therefore, the study of nonlinear network dynamics modeling and regulation of epileptic seizures is helpful in understanding the dynamic mechanism of clinical manifestations of epilepsy, locating the epileptic foci network, and then designing effective network regulation strategies. This article reviews the research progress in network dynamics and control of epileptic neurological diseases and systematically summarizes our research results in recent years in the modeling and analysis of epileptic seizure dynamics and their regulation. Firstly, based on the neuron network model of the hippocampal dentate gyrus-CA3 loop, the molecular and network structural factors that affect temporal lobe seizures were analyzed, and the dynamic mechanism of seizure transition was explained. Secondly, due to the cluster coding characteristics of the brain nervous system, based on the methods of both the neural field model and mean field model, the network dynamics framework of the basal ganglia-thalamocortical (BGCT) circuit was improved. Based on this framework, the dynamic bifurcation mechanism of absence epileptic seizure transition was analyzed, the transition path of different types of seizures was explored, and the multi-stable coexistence phenomenon of absence seizure transition was discovered. The effect of time delay on the synchronization seizures was also revealed. We also designed rich and effective deep brain stimulation (DBS) control strategies for epilepsy and gave a dynamic explanation of electrical stimulation to control absence epileptic seizures. Finally, based on the data-driven statistical modeling and the dynamics analysis of the neuronal population model, new theoretical methods for the foci localization of focal epileptics and finding the key network nodes for effectively controlling seizures were proposed. These results provide important theoretical support for understanding the dynamic nature of refractory seizures and their application in clinical diagnosis and treatment. Lastly, some suggestions are given for further research.

Numerical simulations for microstructure evolution during metal additive manufacturing

CHEN Zekun, LI Xiaoyan

2022, 52(2): 397-409. doi: 10.6052/1000-0992-22-021

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As an emerging manufacturing technology, metal additive manufacturing has broad application prospects in aerospace and aeronautics, transportation, and biomedical engineering. The mechanical properties and performances of materials produced through metal additive manufacturing are determined by their microstructures. It is of great importance to develop the numerical simulations for microstructure evolution during metal additive manufacturing. These simulations can guide and optimize the processing (especially the processing parameters), leading to fabricating the metallic materials with excellent properties and performances. Here, we develop a numerical method for metal additive manufacturing that integrates the heat conduction model with the cellular automaton method. This method can be used for the simulations of multilayers powder fabrication in metal additive manufacturing by utilizing the element birth and death technique and by considering both remelting and regrowth processes of grains. We use this method to predict the typical microstructures of nickel-based superalloy IN718, stainless steel 316L, and FeCoCrNiMn high-entropy alloys fabricated through metal additive manufacturing. The predictions from numerical simulations are consistent with the experimental results. Furthermore, we extend this method to simulate the three-dimensional microstructure evolution of nickel-based superalloy IN718 during metal additive manufacturing. Finally, we point out some important issues and challenges for future research on the numerical simulations for the process of metal additive manufacturing.

Perfect combination of lightness and ingenuity: secrets in the flight of Paratuposa placentis

ZHANG Xing

2022, 52(2): 410-413. doi: 10.6052/1000-0992-22-011

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By using experimental approach, three-dimensional morphological and kinematic models for the flight of Paratuposa placentis are reconstructed. The secrets in the high-performance flight of Paratuposa placentis are successfully unveiled through computational fluid dynamics (CFD) analysis.

2022 Vol. 52, No. 2

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