4.8 Article

Augmented Reality Interfaces Using Virtual Customization of Microstructured Electronic Skin Sensor Sensitivity Performances

Journal

ADVANCED FUNCTIONAL MATERIALS
Volume 31, Issue 39, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202008650

Keywords

augmented reality; electronic skins; soft sensors; tele‐ medicine; virtual reality

Funding

  1. Singapore National Research Fellowship (NRFF) [2017-08]
  2. Singapore National Robotics Program [182 25 00053]
  3. National University of Singapore Start-up grant [2017-01]
  4. National Research Foundation Singapore under its AI Singapore Programme [AISG-GC-2019-002]
  5. Institute for Health Innovation and Technology
  6. N.1 Institute for Health, NUS
  7. NUS Engineering Research Scholarship

Ask authors/readers for more resources

The study proposes a system that customizes micropyramids for e-skin sensors, exploring the relationships between geometry parameters, material properties, and performance through numerical simulations, empirical characterizations, and analytical solutions. The experimentally validated models assist in determining sensor parameters for desired performance.
Electronic skins equip robots and biomedical devices with intuitive skin-like sensitivity. Performance-driven design of electronic skins is a critical need for electronic or biomedical applications. Prior research primarily focuses on investigating effects of microstructures on sensor performance at low pressure ranges. However, having predictive and tunable electro-mechanical responses across an extensive pressure range (>100 kPa) is paramount. Here, the authors propose a system that virtually customizes micropyramids for e-skin sensors. The associations between geometry parameters, material properties, and single-pyramid performance are systematically explored via numerical simulations, empirical characterizations, and analytical solutions. These experimentally validated models allow for the determination of the sensor parameters for the desired performance. An augmented reality interface system for surgery skills training by optimizing sensitivities that match varying tissue stiffnesses is further demonstrated. The platform enables greater effectiveness in rapidly iterating and designing micropyramidal e-skin for applications in augmented reality interfaces, robotics, and telehealthcare.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Multidisciplinary Sciences

Machine learning-aided real-time detection of keyhole pore generation in laser powder bed fusion

Zhongshu Ren, Lin Gao, Samuel J. Clark, Kamel Fezzaa, Pavel Shevchenko, Ann Choi, Wes Everhart, Anthony D. Rollett, Lianyi Chen, Tao Sun

Summary: Porosity defects in laser-based metal additive manufacturing could be a major obstacle. Researchers used synchrotron x-ray imaging and thermal imaging to study the phenomenon and developed a machine learning approach for detecting and predicting the generation of porosity. With the help of operando x-ray imaging, the approach can be adopted in commercial systems.

SCIENCE (2023)

Article Physics, Fluids & Plasmas

Design and Study of the Key Characteristics of a New DC Vacuum Interrupter With a High Peak and Low Residual Magnetic Field

Yiduo Xie, Xiaolong Huang, Tao Sun, Junhu Xie, Lihua Zhao, Yuezheng Wu, Wenjun Ning, Lijun Wang

Summary: With the development of multiterminal HVdc transmission systems, there is a need for high-speed and stable high-voltage dc circuit breakers. This paper proposes a new vacuum dc circuit breaker interrupter based on artificial zero-crossing technology, which can maintain high peak magnetic fields and low residual magnetic fields at high frequencies. The new interrupter exhibits low-temperature rise, uniformly distributed electric field, and high ability to cope with high-frequency current, making it suitable for high-speed and stable breaking.

IEEE TRANSACTIONS ON PLASMA SCIENCE (2023)

Article Materials Science, Multidisciplinary

Effect of Densification on the Impact Behavior of SiO2f/SiO2 Woven Ceramic Matrix Composites Filled with Silica Aerogel

Yawei Zhang, Shuqiang Xiong, Chongyin Zhang, Tao Sun, Zhiwei Gui, Shaozhi Zhang

Summary: Woven silica fiber-reinforced ceramic silica matrix composites with 2.5D dimensionality are commonly used in the aerospace industry and are prepared using the sol-gel process. The mechanical properties of the composites are influenced by the properties of the fiber, matrix, and interface. Increasing the contact area between the fiber and matrix can enhance the mechanical strength of the composites. Finite element analysis and compression tests can be used to predict and improve the impact resistance of the composites.

JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE (2023)

Article Energy & Fuels

Lithium Salt-Doped Organic Conjugated Hole Transport Layer for High-Performance PbS Quantum Dot Solar Cells

Jinpeng Yang, Chunyan Wu, Tengzuo Huang, Fayin Yu, Shuo Ding, Lei Qian, Tao Sun, Chaoyu Xiang

Summary: The impacts of doping the organic hole transport layer (HTL) PTB7-Th with lithium bis(trifluoromethanesulfonimide) (LiTSFI) on the performance of quantum dot solar cells were investigated, and a notable enhancement in fill factor was observed. Doping with LiTFSI significantly deepened the Fermi level of the HTL, improving charge separation ability and conductivity. By optimizing doping conditions, the doped device achieved a maximum power conversion efficiency of 12.68%. This doping strategy of organic HTL promotes the development of lead sulfide quantum dot solar cell techniques.

SOLAR RRL (2023)

Article Nanoscience & Nanotechnology

Stable Multicomponent Multiphase All Active Material Lithium-Ion Battery Anodes

Chen Cai, Lin Gao, Tao Sun, Gary M. Koenig Jr

Summary: Lithium-ion batteries are the leading energy storage technology due to their high energy density. The electrode architecture and microstructure can be engineered to further enhance the energy density, in addition to traditional improvements through materials chemistry. Active material (AAM) electrodes, which only consist of the electroactive material, have advantages over conventional composite electrodes in terms of mechanical stability and ion transport properties. However, the absence of binders and composite processing makes AAM electrodes more susceptible to volume changes in the electroactive material during cycling. The use of TiNb2O7 (TNO) and MoO2 (MO) as multicomponent AAM anodes shows promising results in terms of energy density, rate capability, and cycle life.

ACS APPLIED MATERIALS & INTERFACES (2023)

Article Chemistry, Multidisciplinary

Precisely tailoring pore structure in sunflower plate-derived N, O co-doped carbons for high-performance supercapacitors

Dong Liu, Tao Sun, Yuqin Hu, Yigang Ding, Baomin Fan, Haitao Wang

Summary: A versatile K2CO3 activation approach is proposed to adjust and control the pore structure of sunflower plate-derived hierarchical porous carbon materials. The specific surface area of the optimal material is 2526 m2/g, and it exhibits superior capacitance activity. The assembled supercapacitors also demonstrate high energy density in different electrolyte solutions.

JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY (2023)

Article Materials Science, Multidisciplinary

Experimental Study and Finite-Element Modeling of the Intermittent Cutting of Steel AISI 52100 with a PcBN Containing Tool

Fei Teng, A. S. Manokhin, Junjie Zhang, S. A. Klymenko, Tao Sun, S. An. Klymenko, Y. O. Melniychuk, O. O. Pasichny

Summary: This study presented experimental results on intermittent cutting of quenched steel AISI 52100 using a PcBN tool. The finite element method was used to analyze the machining process, considering the polycrystalline structure and composition of the tool. Experimental results showed that a PcBN tool with low PcBN content had comparable efficiency to a tool with high PcBN content when machining quenched steel AISI 52100 at a cutting speed of 210 m/min under intermittent cutting conditions. These findings demonstrate the potential and high performance of tools made from PcBN composites with different compositions under specific operational conditions.

JOURNAL OF SUPERHARD MATERIALS (2023)

Article Chemistry, Physical

Frictionless multiphasic interface for near-ideal aero-elastic pressure sensing

Wen Cheng, Xinyu Wang, Ze Xiong, Jun Liu, Zhuangjian Liu, Yunxia Jin, Haicheng Yao, Tak-Sing Wong, John S. Ho, Benjamin C. K. Tee

Summary: The authors designed a pressure sensor that utilizes solid-liquid-liquid-gas multiphasic interfaces and a trapped air layer to modulate capacitance changes with pressure, achieving near-friction-free contact line motions and near-ideal pressure sensing performance. The sensor possesses outstanding linearity, ultralow hysteresis, and very high sensitivity, making it suitable for operation in complex fluid environments.

NATURE MATERIALS (2023)

Article Green & Sustainable Science & Technology

Modelling and Control Tank Testing Validation for Attenuator Type Wave Energy Converter - Part III: Model Predictive Control and Robustness Validation

Tao Sun, Zhijing Liao, Mustafa Al-Ani, Laura-Beth Jordan, Guang Li, Siyuan Zhan, Michael Belmont, Christopher Edwards

Summary: This paper presents further tank testing results based on the linear passive damping control and linear non-causal optimal control presented in the previous papers. The results show that the model predictive controller (MPC) can significantly improve energy output and outperform the LNOC in a range of irregular unidirectional waves. In addition, both the MPC and LNOC controller demonstrate robustness in more realistic sea conditions.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2023)

Article Green & Sustainable Science & Technology

Modelling and Control Tank Testing Validation for Attenuator Type Wave Energy Converter-Part I: Experiment Setup and Control-Oriented Modelling

Zhijing Liao, Tao Sun, Mustafa Al-Ani, Laura-Beth Jordan, Guang Li, Zhenchun Wang, Michael Belmont, Christopher Edwards

Summary: Advanced non-causal optimal control strategies have been shown to greatly enhance the energy output of a scale physical model of an attenuator type wave energy converter through tank testing experiments. These strategies, including linear non-causal optimal control (LNOC) and model predictive control (MPC), outperform optimally tuned passive damping control, achieving energy output improvements ranging from 10% to 460% in irregular waves. The controllers also demonstrate robust performance in various real sea conditions and can be applied to other wave energy converters.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2023)

Article Engineering, Manufacturing

Tailoring material microstructure and property in wire-laser directed energy deposition through a wiggle deposition strategy

Lin Gao, Jishnu Bhattacharyya, Wenhao Lin, Zhongshu Ren, Andrew C. Chuang, Pavel D. Shevchenko, Viktor Nikitin, Ji Ma, Sean R. Agnew, Tao Sun

Summary: This study develops a unique approach to control the solidification texture and crystallographic texture of 316L stainless steel samples through changing the deposition pattern in wire-laser directed energy deposition. This approach reduces anisotropy and increases ductility, leading to tailored local properties. By manipulating the melt pool instability, the control of material microstructure and anisotropy in metal additive manufacturing is achieved.

ADDITIVE MANUFACTURING (2023)

Article Optics

Depth Estimation Using Polarizer-Free Liquid Crystal Lens

Lai Wenjie, Liu Zhiqiang, Sun Tao, Hu Xiao

Summary: A depth estimation scheme for polarizer-free liquid crystal lenses was proposed, which utilizes the blur caused by o-light to enhance the accuracy of depth estimation. Removing the polarizer reduces the complexity of the optical system and is significant for practical applications.

ACTA OPTICA SINICA (2023)

Article Computer Science, Artificial Intelligence

Sentiment Analysis: Comprehensive Reviews, Recent Advances, and Open Challenges

Qiang Lu, Xia Sun, Yunfei Long, Zhizezhang Gao, Jun Feng, Tao Sun

Summary: Sentiment analysis (SA) has achieved significant breakthroughs in the past decade and there is a growing interest in multimodal SA (MSA). This article provides a comprehensive overview of SA advances, introduces a novel framework for SA tasks, and discusses the workflows and recent advances of single-modal SA. It also explores the research gaps and challenges in MSA, and proposes potential directions for future improvement.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023)

Article Chemistry, Physical

Size-dependent bending of a rectangular polymer film

Yin Liu, Xuemei Fu, Ruochen Yang, Jun Liu, Benjamin Chee Keong Tee, Zhuangjian Liu

Summary: Inhomogeneous swelling of fluoroelastomer films in liquid environments can be used in soft actuators and sensors. We report an abnormal size-dependent bending phenomenon of rectangular fluoroelastomer films, where the bending direction changes from long-side bending to short-side bending with increasing length or width or decreasing thickness. By using finite element analysis and a bilayer model, we reveal the key role of gravity in determining the size-dependent bending behavior. These findings can be useful for designing swelling-based polymer actuators and sensors in the future.

SOFT MATTER (2023)

Article Multidisciplinary Sciences

Advances in biophysical feedbacks and the resulting stable states in tidal flat systems

Heyue Zhang, Yi Zhou, Tao Sun, Haobing Cao, Zeng Zhou

Summary: Tidal flats are vital for maintaining coastal ecosystem health, resisting natural coastal disasters, and sequestering blue carbon. However, they have been increasingly degraded due to human activities, storm surges, and reduced sediment availability. Understanding and supporting the self-organization process driven by biophysical interactions in tidal flats is essential for their ecological protection and restoration.

CHINESE SCIENCE BULLETIN-CHINESE (2023)

No Data Available