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Wang Z, Wan T, Ma S, Chai Y. Multidimensional vision sensors for information processing. NATURE NANOTECHNOLOGY 2024; 19:919-930. [PMID: 38877323 DOI: 10.1038/s41565-024-01665-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/07/2024] [Indexed: 06/16/2024]
Abstract
The visual scene in the physical world integrates multidimensional information (spatial, temporal, polarization, spectrum and so on) and typically shows unstructured characteristics. Conventional image sensors cannot process this multidimensional vision data, creating a need for vision sensors that can efficiently extract features from substantial multidimensional vision data. Vision sensors are able to transform the unstructured visual scene into featured information without relying on sophisticated algorithms and complex hardware. The response characteristics of sensors can be abstracted into operators with specific functionalities, allowing for the efficient processing of perceptual information. In this Review, we delve into the hardware implementation of multidimensional vision sensors, exploring their working mechanisms and design principles. We exemplify multidimensional vision sensors built on emerging devices and silicon-based system integration. We further provide benchmarking metrics for multidimensional vision sensors and conclude with the principle of device-system co-design and co-optimization.
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Affiliation(s)
- Zhaoqing Wang
- Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
- Joint Research Centre of Microelectronics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
| | - Tianqing Wan
- Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
- Joint Research Centre of Microelectronics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
| | - Sijie Ma
- Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
- Joint Research Centre of Microelectronics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
| | - Yang Chai
- Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
- Joint Research Centre of Microelectronics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
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2
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Tan T, Guo H, Li Y, Wang Y, Cai W, Bao W, Zhou P, Feng X. Integration of MoS 2 Memtransistor Devices and Analogue Circuits for Sensor Fusion in Autonomous Vehicle Target Localization. ACS NANO 2024; 18:13652-13661. [PMID: 38751043 DOI: 10.1021/acsnano.4c00456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
In contemporary autonomous driving systems relying on sensor fusion, traditional digital processors encounter challenges associated with analogue-to-digital conversion and iterative vector-matrix operations, which are encumbered by limitations in terms of response time and energy consumption. In this study, we present an analogue Kalman filter circuit based on molybdenum disulfide (MoS2) memtransistor, designed to accelerate sensor fusion for precise localization in autonomous vehicle applications. The nonvolatile memory characteristics of the memtransistor allow for the storage of a fixed Kalman gain, which eliminates the data convergence and thus accelerates the processing speeds. Additionally, the modulation of multiple conductance states by the gate terminal enables fast adaptability to diverse autonomous driving scenarios by tuning multiple Kalman filter gains. Our proposed analogue Kalman filter circuit accurately estimates the position coordinates of target vehicles by fusing sensor data from light detection and ranging (LiDAR), millimeter-wave radar (Radar), and camera, and it successfully solves real-word problems in a signal-free crossroad intersection. Notably, our system achieves a 1000-fold improvement in energy efficiency compared to that of digital circuits. This work underscores the viability of a memtransistor for achieving fast, energy-efficient real-time sensing, and continuous signal processing in advanced sensor fusion technology.
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Affiliation(s)
- Tian Tan
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Haoyue Guo
- School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yida Li
- School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yafei Wang
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Weiwei Cai
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Wenzhong Bao
- School of Microelectronics, Fudan University, Shanghai 200433, China
- Shaoxing Laboratory, Shaoxing 312300, China
| | - Peng Zhou
- School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Xuewei Feng
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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3
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Wu Y, Deng W, Li K, Wang X, Liu B, Li J, Chen Z, Zhang Y. A Spiking Artificial Vision Architecture Based on Fully Emulating the Human Vision. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2312094. [PMID: 38320173 DOI: 10.1002/adma.202312094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/29/2024] [Indexed: 02/08/2024]
Abstract
Intelligent vision necessitates the deployment of detectors that are always-on and low-power, mirroring the continuous and uninterrupted responsiveness characteristic of human vision. Nonetheless, contemporary artificial vision systems attain this goal by the continuous processing of massive image frames and executing intricate algorithms, thereby expending substantial computational power and energy. In contrast, biological data processing, based on event-triggered spiking, has higher efficiency and lower energy consumption. Here, this work proposes an artificial vision architecture consisting of spiking photodetectors and artificial synapses, closely mirroring the intricacies of the human visual system. Distinct from previously reported techniques, the photodetector is self-powered and event-triggered, outputting light-modulated spiking signals directly, thereby fulfilling the imperative for always-on with low-power consumption. With the spiking signals processing through the integrated synapse units, recognition of graphics, gestures, and human action has been implemented, illustrating the potent image processing capabilities inherent within this architecture. The results prove the 90% accuracy rate in human action recognition within a mere five epochs utilizing a rudimentary artificial neural network. This novel architecture, grounded in spiking photodetectors, offers a viable alternative to the extant models of always-on low-power artificial vision system.
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Affiliation(s)
- Yi Wu
- Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Wenjie Deng
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Kexin Li
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Xiaoting Wang
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Bo Liu
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Jingzhen Li
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Zhijie Chen
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Yongzhe Zhang
- Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China
- Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
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Wali A, Ravichandran H, Das S. A 2D Cryptographic Hash Function Incorporating Homomorphic Encryption for Secure Digital Signatures. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2400661. [PMID: 38373292 DOI: 10.1002/adma.202400661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Indexed: 02/21/2024]
Abstract
User authentication is a critical aspect of any information exchange system which verifies the identities of individuals seeking access to sensitive information. Conventionally, this approachrelies on establishing robust digital signature protocols which employ asymmetric encryption techniques involving a key pair consisting of a public key and its matching private key. In this article, a user verification platform constructed using integrated circuits (ICs) with atomically thin two-dimensional (2D) monolayer molybdenum disulfide (MoS2 ) memtransistors is presented. First, generation of secure cryptographic keys is demonstrated by exploiting the inherent stochasticity of carrier trapping and detrapping at the 2D/oxide interface trap sites. Subsequently, the ability to manipulate the functionality of logical NOR is leveraged to create a secure one-way hash function which when homomorphically operated upon with NAND, XOR, OR, NOT, and AND logic circuits generate distinct digital signatures. These signatures when subsequently decrypted, verify the authenticity of the receiver while ensuring complete preservation of data integrity and confidentiality as the underlying information is never revealed. Finally, the advantages of implementing a NOR-based hashing techniques in comparison to the conventional XOR-based encryption method are established. This demonstration highlights the potential of 2D-based ICs in developing critical hardware information security primitives.
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Affiliation(s)
- Akshay Wali
- Electrical Engineering and Computer Science, Penn State University, University Park, PA, 16802, USA
| | | | - Saptarshi Das
- Electrical Engineering and Computer Science, Penn State University, University Park, PA, 16802, USA
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
- Materials Science and Engineering, Penn State University, University Park, PA, 16802, USA
- Materials Research Institute, Penn State University, University Park, PA, 16802, USA
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Ansari S, Bianconi S, Kang CM, Mohseni H. From Material to Cameras: Low-Dimensional Photodetector Arrays on CMOS. SMALL METHODS 2024; 8:e2300595. [PMID: 37501320 DOI: 10.1002/smtd.202300595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/25/2023] [Indexed: 07/29/2023]
Abstract
The last two decades have witnessed a dramatic increase in research on low-dimensional material with exceptional optoelectronic properties. While low-dimensional materials offer exciting new opportunities for imaging, their integration in practical applications has been slow. In fact, most existing reports are based on single-pixel devices that cannot rival the quantity and quality of information provided by massively parallelized mega-pixel imagers based on complementary metal-oxide semiconductor (CMOS) readout electronics. The first goal of this review is to present new opportunities in producing high-resolution cameras using these new materials. New photodetection methods and materials in the field are presented, and the challenges involved in their integration on CMOS chips for making high-resolution cameras are discussed. Practical approaches are then presented to address these challenges and methods to integrate low-dimensional material on CMOS. It is also shown that such integrations could be used for ultra-low noise and massively parallel testing of new material and devices. The second goal of this review is to present the colossal untapped potential of low-dimensional material in enabling the next-generation of low-cost and high-performance cameras. It is proposed that low-dimensional materials have the natural ability to create excellent bio-inspired artificial imaging systems with unique features such as in-pixel computing, multi-band imaging, and curved retinas.
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Affiliation(s)
- Samaneh Ansari
- Electrical and Computer Engneering Department, Northwestern University, Evanston, IL, 60208, USA
| | - Simone Bianconi
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA
| | - Chang-Mo Kang
- Photonic Semiconductor Research Center, Korea Photonics Technology Institute, Gwangju, 61007, Republic of Korea
| | - Hooman Mohseni
- Electrical and Computer Engneering Department, Northwestern University, Evanston, IL, 60208, USA
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Zhu S, Xie T, Lv Z, Leng YB, Zhang YQ, Xu R, Qin J, Zhou Y, Roy VAL, Han ST. Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2301986. [PMID: 37435995 DOI: 10.1002/adma.202301986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/28/2023] [Accepted: 07/10/2023] [Indexed: 07/13/2023]
Abstract
The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.
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Affiliation(s)
- Shirui Zhu
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Tao Xie
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ziyu Lv
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Yan-Bing Leng
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Yu-Qi Zhang
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Runze Xu
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Jingrun Qin
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Vellaisamy A L Roy
- School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, 999077, P. R. China
| | - Su-Ting Han
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
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Choi C, Lee GJ, Chang S, Song YM, Kim DH. Nanomaterial-Based Artificial Vision Systems: From Bioinspired Electronic Eyes to In-Sensor Processing Devices. ACS NANO 2024; 18:1241-1256. [PMID: 38166167 DOI: 10.1021/acsnano.3c10181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
High-performance robotic vision empowers mobile and humanoid robots to detect and identify their surrounding objects efficiently, which enables them to cooperate with humans and assist human activities. For error-free execution of these robots' tasks, efficient imaging and data processing capabilities are essential, even under diverse and complex environments. However, conventional technologies fall short of meeting the high-standard requirements of robotic vision under such circumstances. Here, we discuss recent progress in artificial vision systems with high-performance imaging and data processing capabilities enabled by distinctive electrical, optical, and mechanical characteristics of nanomaterials surpassing the limitations of traditional silicon technologies. In particular, we focus on nanomaterial-based electronic eyes and in-sensor processing devices inspired by biological eyes and animal visual recognition systems, respectively. We provide perspectives on key nanomaterials, device components, and their functionalities, as well as explain the remaining challenges and future prospects of the artificial vision systems.
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Affiliation(s)
- Changsoon Choi
- Center for Optoelectronic Materials and Devices, Post-silicon Semiconductor Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Gil Ju Lee
- Department of Electronics Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Sehui Chang
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea
| | - Young Min Song
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea
- AI Graduate School, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea
- Department of Semiconductor Engineering, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea
| | - Dae-Hyeong Kim
- Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul 08826, Republic of Korea
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
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Ravichandran H, Sen D, Wali A, Schranghamer TF, Trainor N, Redwing JM, Ray B, Das S. A Peripheral-Free True Random Number Generator Based on Integrated Circuits Enabled by Atomically Thin Two-Dimensional Materials. ACS NANO 2023; 17:16817-16826. [PMID: 37616285 DOI: 10.1021/acsnano.3c03581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
A true random number generator (TRNG) is essential to ensure information security for Internet of Things (IoT) edge devices. While pseudorandom number generators (PRNGs) have been instrumental, their deterministic nature limits their application in security-sensitive scenarios. In contrast, hardware-based TRNGs derived from physically unpredictable processes offer greater reliability. This study demonstrates a peripheral-free TRNG utilizing two cascaded three-stage inverters (TSIs) in conjunction with an XOR gate composed of monolayer molybdenum disulfide (MoS2) field-effect transistors (FETs) by exploiting the stochastic charge trapping and detrapping phenomena at and/or near the MoS2/dielectric interface. The entropy source passes the NIST SP800-90B tests with a minimum normalized entropy of 0.8780, while the generated bits pass the NIST SP800-22 randomness tests without any postprocessing. Moreover, the keys generated using these random bits are uncorrelated with near-ideal entropy, bit uniformity, and Hamming distances, exhibiting resilience against machine learning (ML) attacks, temperature variations, and supply bias fluctuations with a frugal energy expenditure of 30 pJ/bit. This approach offers an advantageous alternative to conventional silicon, memristive, and nanomaterial-based TRNGs as it obviates the need for extensive peripherals while harnessing the potential of atomically thin 2D materials in developing low-power TRNGs.
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Affiliation(s)
- Harikrishnan Ravichandran
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Dipanjan Sen
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Akshay Wali
- Electrical Engineering and Computer Science, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Thomas F Schranghamer
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Nicholas Trainor
- Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- 2D Crystal Consortium, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Joan M Redwing
- Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- 2D Crystal Consortium, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Biswajit Ray
- Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado 80523, United States
| | - Saptarshi Das
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- 2D Crystal Consortium, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Electrical Engineering and Computer Science, Pennsylvania State University, University Park, Pennsylvania 16802, United States
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Lau CS, Das S, Verzhbitskiy IA, Huang D, Zhang Y, Talha-Dean T, Fu W, Venkatakrishnarao D, Johnson Goh KE. Dielectrics for Two-Dimensional Transition-Metal Dichalcogenide Applications. ACS NANO 2023. [PMID: 37257134 DOI: 10.1021/acsnano.3c03455] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Despite over a decade of intense research efforts, the full potential of two-dimensional transition-metal dichalcogenides continues to be limited by major challenges. The lack of compatible and scalable dielectric materials and integration techniques restrict device performances and their commercial applications. Conventional dielectric integration techniques for bulk semiconductors are difficult to adapt for atomically thin two-dimensional materials. This review provides a brief introduction into various common and emerging dielectric synthesis and integration techniques and discusses their applicability for 2D transition metal dichalcogenides. Dielectric integration for various applications is reviewed in subsequent sections including nanoelectronics, optoelectronics, flexible electronics, valleytronics, biosensing, quantum information processing, and quantum sensing. For each application, we introduce basic device working principles, discuss the specific dielectric requirements, review current progress, present key challenges, and offer insights into future prospects and opportunities.
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Affiliation(s)
- Chit Siong Lau
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Sarthak Das
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Ivan A Verzhbitskiy
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Ding Huang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Yiyu Zhang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Teymour Talha-Dean
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
- Department of Physics and Astronomy, Queen Mary University of London, London E1 4NS, United Kingdom
| | - Wei Fu
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Dasari Venkatakrishnarao
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
| | - Kuan Eng Johnson Goh
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore 138634, Republic of Singapore
- Department of Physics, National University of Singapore, 2 Science Drive 3, 117551, Singapore
- Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 50 Nanyang Avenue 639798, Singapore
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