1
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Bae J, Kwon C, Park SO, Jeong H, Park T, Jang T, Cho Y, Kim S, Choi S. Tunable ion energy barrier modulation through aliovalent halide doping for reliable and dynamic memristive neuromorphic systems. SCIENCE ADVANCES 2024; 10:eadm7221. [PMID: 38848362 PMCID: PMC11160469 DOI: 10.1126/sciadv.adm7221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 05/03/2024] [Indexed: 06/09/2024]
Abstract
Memristive neuromorphic computing has emerged as a promising computing paradigm for the upcoming artificial intelligence era, offering low power consumption and high speed. However, its commercialization remains challenging due to reliability issues from stochastic ion movements. Here, we propose an innovative method to enhance the memristive uniformity and performance through aliovalent halide doping. By introducing fluorine concentration into dynamic TiO2-x memristors, we experimentally demonstrate reduced device variations, improved switching speeds, and enhanced switching windows. Atomistic simulations of amorphous TiO2-x reveal that fluoride ions attract oxygen vacancies, improving the reversible redistribution and uniformity. A number of migration barrier calculations statistically show that fluoride ions also reduce the migration energies of nearby oxygen vacancies, facilitating ionic diffusion and high-speed switching. The detailed Voronoi volume analysis further suggests design principles in terms of the migrating species' electrostatic repulsion and migration barriers. This work presents an innovative methodology for the fabrication of reliable memristor devices, contributing to the realization of hardware-based neuromorphic systems.
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Affiliation(s)
- Jongmin Bae
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Choah Kwon
- Department of Nuclear Engineering, Hanyang University, Seoul 04763, Republic of Korea
| | - See-On Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Hakcheon Jeong
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Taehoon Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Taehwan Jang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Yoonho Cho
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Sangtae Kim
- Department of Nuclear Engineering, Hanyang University, Seoul 04763, Republic of Korea
- Department of Material Science and Engineering, Hanyang University, Seoul 04763, Republic of Korea
| | - Shinhyun Choi
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
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2
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Woo KS, Han J, Yi SI, Thomas L, Park H, Kumar S, Hwang CS. Tunable stochastic memristors for energy-efficient encryption and computing. Nat Commun 2024; 15:3245. [PMID: 38622148 PMCID: PMC11018740 DOI: 10.1038/s41467-024-47488-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 04/03/2024] [Indexed: 04/17/2024] Open
Abstract
Information security and computing, two critical technological challenges for post-digital computation, pose opposing requirements - security (encryption) requires a source of unpredictability, while computing generally requires predictability. Each of these contrasting requirements presently necessitates distinct conventional Si-based hardware units with power-hungry overheads. This work demonstrates Cu0.3Te0.7/HfO2 ('CuTeHO') ion-migration-driven memristors that satisfy the contrasting requirements. Under specific operating biases, CuTeHO memristors generate truly random and physically unclonable functions, while under other biases, they perform universal Boolean logic. Using these computing primitives, this work experimentally demonstrates a single system that performs cryptographic key generation, universal Boolean logic operations, and encryption/decryption. Circuit-based calculations reveal the energy and latency advantages of the CuTeHO memristors in these operations. This work illustrates the functional flexibility of memristors in implementing operations with varying component-level requirements.
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Affiliation(s)
- Kyung Seok Woo
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea
- Sandia National Laboratories, Livermore, CA, USA
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Janguk Han
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea
| | - Su-In Yi
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Luke Thomas
- Applied Materials Inc., Santa Clara, CA, USA
| | - Hyungjun Park
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea
| | - Suhas Kumar
- Sandia National Laboratories, Livermore, CA, USA.
| | - Cheol Seong Hwang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea.
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3
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Wang K, Shi J, Lai W, He Q, Xu J, Ni Z, Liu X, Pi X, Yang D. All-silicon multidimensionally-encoded optical physical unclonable functions for integrated circuit anti-counterfeiting. Nat Commun 2024; 15:3203. [PMID: 38615044 PMCID: PMC11016093 DOI: 10.1038/s41467-024-47479-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 04/02/2024] [Indexed: 04/15/2024] Open
Abstract
Integrated circuit anti-counterfeiting based on optical physical unclonable functions (PUFs) plays a crucial role in guaranteeing secure identification and authentication for Internet of Things (IoT) devices. While considerable efforts have been devoted to exploring optical PUFs, two critical challenges remain: incompatibility with the complementary metal-oxide-semiconductor (CMOS) technology and limited information entropy. Here, we demonstrate all-silicon multidimensionally-encoded optical PUFs fabricated by integrating silicon (Si) metasurface and erbium-doped Si quantum dots (Er-Si QDs) with a CMOS-compatible procedure. Five in-situ optical responses have been manifested within a single pixel, rendering an ultrahigh information entropy of 2.32 bits/pixel. The position-dependent optical responses originate from the position-dependent radiation field and Purcell effect. Our evaluation highlights their potential in IoT security through advanced metrics like bit uniformity, similarity, intra- and inter-Hamming distance, false-acceptance and rejection rates, and encoding capacity. We finally demonstrate the implementation of efficient lightweight mutual authentication protocols for IoT applications by using the all-Si multidimensionally-encoded optical PUFs.
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Affiliation(s)
- Kun Wang
- State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Jianwei Shi
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing, 100190, China
- State Key Laboratory for Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, 100083, China
| | - Wenxuan Lai
- State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Qiang He
- State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Jun Xu
- School of Electronic Science and Engineering & National Laboratory of Solid State Microstructures, Nanjing University, Nanjing, Jiangsu, 210093, China
- School of Microelectronics, Nantong University, Nantong, Jiangsu, 226019, China
| | - Zhenyi Ni
- State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China.
| | - Xinfeng Liu
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing, 100190, China.
| | - Xiaodong Pi
- State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China.
- Institute of Advanced Semiconductors, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, Zhejiang, 311215, China.
| | - Deren Yang
- State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China.
- Institute of Advanced Semiconductors, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Zhejiang University, Hangzhou, Zhejiang, 311215, China.
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4
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Wang R, Zhang W, Wang S, Zeng T, Ma X, Wang H, Hao Y. Memristor-Based Signal Processing for Compressed Sensing. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:1354. [PMID: 37110939 PMCID: PMC10141131 DOI: 10.3390/nano13081354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/04/2023] [Accepted: 04/05/2023] [Indexed: 06/19/2023]
Abstract
With the rapid progress of artificial intelligence, various perception networks were constructed to enable Internet of Things (IoT) applications, thereby imposing formidable challenges to communication bandwidth and information security. Memristors, which exhibit powerful analog computing capabilities, emerged as a promising solution expected to address these challenges by enabling the development of the next-generation high-speed digital compressed sensing (CS) technologies for edge computing. However, the mechanisms and fundamental properties of memristors for achieving CS remain unclear, and the underlying principles for selecting different implementation methods based on various application scenarios have yet to be elucidated. A comprehensive overview of memristor-based CS techniques is currently lacking. In this article, we systematically presented CS requirements on device performance and hardware implementation. The relevant models were analyzed and discussed from the mechanism level to elaborate the memristor CS system scientifically. In addition, the method of deploying CS hardware using the powerful signal processing capabilities and unique performance of memristors was further reviewed. Subsequently, the potential of memristors in all-in-one compression and encryption was anticipated. Finally, existing challenges and future outlooks for memristor-based CS systems were discussed.
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Affiliation(s)
- Rui Wang
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi’an 710071, China
| | - Wanlin Zhang
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi’an 710071, China
| | - Saisai Wang
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Advanced Materials and Nanotechnology, Xidian University, Xi’an 710071, China
| | - Tonglong Zeng
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi’an 710071, China
| | - Xiaohua Ma
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi’an 710071, China
| | - Hong Wang
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi’an 710071, China
| | - Yue Hao
- Key Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi’an 710071, China
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5
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Wang R, Wang S, Xin Y, Cao Y, Liang Y, Peng Y, Feng J, Li Y, Lv L, Ma X, Wang H, Hao Y. All‐in‐One Compression and Encryption Engine Based on Flexible Polyimide Memristor. SMALL SCIENCE 2023. [DOI: 10.1002/smsc.202200082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Affiliation(s)
- Rui Wang
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 China
| | - Saisai Wang
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Yuhan Xin
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Yaxiong Cao
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Yu Liang
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Yaqian Peng
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Jie Feng
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Yang Li
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Advanced Materials and Nanotechnology Xidian University Xi'an 710071 China
| | - Ling Lv
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 China
| | - Xiaohua Ma
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 China
| | - Hong Wang
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 China
| | - Yue Hao
- Key Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 China
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6
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Go S, Wang Q, Lim KG, Lee TH, Bajalovic N, Loke DK. Ultrafast Near-Ideal Phase-Change Memristive Physical Unclonable Functions Driven by Amorphous State Variations. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2204453. [PMID: 36372549 PMCID: PMC9798968 DOI: 10.1002/advs.202204453] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/11/2022] [Indexed: 06/16/2023]
Abstract
There is an ever-increasing demand for next-generation devices that do not require passwords and are impervious to cloning. For traditional hardware security solutions in edge computing devices, inherent limitations are addressed by physical unclonable functions (PUF). However, realizing efficient roots of trust for resource constrained hardware remains extremely challenging, despite excellent demonstrations with conventional silicon circuits and archetypal oxide memristor-based crossbars. An attractive, down-scalable approach to design efficient cryptographic hardware is to harness memristive materials with a large-degree-of-randomness in materials state variations, but this strategy is still not well understood. Here, the utilization of high-degree-of-randomness amorphous (A) state variations associated with different operating conditions via thermal fluctuation effects is demonstrated, as well as an integrated framework for in memory computing and next generation security primitives, viz., APUF, for achieving secure key generation and device authentication. Near ideal uniformity and uniqueness without additional initial writing overheads in weak memristive A-PUF is achieved. In-memory computing empowers a strong exclusive OR (XOR-) and-repeat A PUF construction to avoid machine learning attacks, while rapid crystallization processes enable large-sized-key reconfigurability. These findings pave the way for achieving a broadly applicable security primitive for enhancing antipiracy of integrated systems and product authentication in supply chains.
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Affiliation(s)
- Shao‐Xiang Go
- Department of ScienceMathematics and TechnologySingapore University of Technology and DesignSingapore487372Singapore
| | - Qiang Wang
- Department of ScienceMathematics and TechnologySingapore University of Technology and DesignSingapore487372Singapore
| | - Kian Guan Lim
- Department of ScienceMathematics and TechnologySingapore University of Technology and DesignSingapore487372Singapore
| | - Tae Hoon Lee
- Department of EngineeringUniversity of CambridgeTrumpington StreetCambridgeCB2 1PZUK
- School of Materials Science and EngineeringKyungpook National UniversityDaegu41566Republic of Korea
| | - Natasa Bajalovic
- Department of ScienceMathematics and TechnologySingapore University of Technology and DesignSingapore487372Singapore
| | - Desmond K. Loke
- Department of ScienceMathematics and TechnologySingapore University of Technology and DesignSingapore487372Singapore
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7
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Woo KS, Kim J, Han J, Kim W, Jang YH, Hwang CS. Probabilistic computing using Cu 0.1Te 0.9/HfO 2/Pt diffusive memristors. Nat Commun 2022; 13:5762. [PMID: 36180426 PMCID: PMC9525628 DOI: 10.1038/s41467-022-33455-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 09/19/2022] [Indexed: 11/17/2022] Open
Abstract
A computing scheme that can solve complex tasks is necessary as the big data field proliferates. Probabilistic computing (p-computing) paves the way to efficiently handle problems based on stochastic units called probabilistic bits (p-bits). This study proposes p-computing based on the threshold switching (TS) behavior of a Cu0.1Te0.9/HfO2/Pt (CTHP) diffusive memristor. The theoretical background of the p-computing resembling the Hopfield network structure is introduced to explain the p-computing system. P-bits are realized by the stochastic TS behavior of CTHP diffusive memristors, and they are connected to form the p-computing network. The memristor-based p-bit is likely to be ‘0’ and ‘1’, of which probability is controlled by an input voltage. The memristor-based p-computing enables all 16 Boolean logic operations in both forward and inverted operations, showing the possibility of expanding its uses for complex operations, such as full adder and factorization. Designing a computing scheme to solve complex tasks as the big data field proliferates remains a challenge. Here, the authors present a probabilistic bit generation hardware built using the random nature of CuxTe1−x/HfO2/Pt memristors capable of performing logic gates with invertible mode, showing the expandability to complex logic circuits.
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Affiliation(s)
- Kyung Seok Woo
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Jaehyun Kim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Janguk Han
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Woohyun Kim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Yoon Ho Jang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Cheol Seong Hwang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea.
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8
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All-in-one, bio-inspired, and low-power crypto engines for near-sensor security based on two-dimensional memtransistors. Nat Commun 2022; 13:3587. [PMID: 35739100 PMCID: PMC9226122 DOI: 10.1038/s41467-022-31148-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/31/2022] [Indexed: 11/15/2022] Open
Abstract
In the emerging era of the internet of things (IoT), ubiquitous sensors continuously collect, consume, store, and communicate a huge volume of information which is becoming increasingly vulnerable to theft and misuse. Modern software cryptosystems require extensive computational infrastructure for implementing ciphering algorithms, making them difficult to be adopted by IoT edge sensors that operate with limited hardware resources and at low energy budgets. Here we propose and experimentally demonstrate an “all-in-one” 8 × 8 array of robust, low-power, and bio-inspired crypto engines monolithically integrated with IoT edge sensors based on two-dimensional (2D) memtransistors. Each engine comprises five 2D memtransistors to accomplish sensing and encoding functionalities. The ciphered information is shown to be secure from an eavesdropper with finite resources and access to deep neural networks. Our hardware platform consists of a total of 320 fully integrated monolayer MoS2-based memtransistors and consumes energy in the range of hundreds of picojoules and offers near-sensor security. Internet of things (IoT) sensors can collect, store and communicate large volumes of information, which require effective security measures. Here, the authors report the realization of low-power edge sensors based on photosensitive and programmable 2D memtransistors, integrating sensing, storage and encryption functionalities.
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Abbas H, Li J, Ang DS. Conductive Bridge Random Access Memory (CBRAM): Challenges and Opportunities for Memory and Neuromorphic Computing Applications. MICROMACHINES 2022; 13:mi13050725. [PMID: 35630191 PMCID: PMC9143014 DOI: 10.3390/mi13050725] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/29/2022] [Accepted: 04/29/2022] [Indexed: 11/16/2022]
Abstract
Due to a rapid increase in the amount of data, there is a huge demand for the development of new memory technologies as well as emerging computing systems for high-density memory storage and efficient computing. As the conventional transistor-based storage devices and computing systems are approaching their scaling and technical limits, extensive research on emerging technologies is becoming more and more important. Among other emerging technologies, CBRAM offers excellent opportunities for future memory and neuromorphic computing applications. The principles of the CBRAM are explored in depth in this review, including the materials and issues associated with various materials, as well as the basic switching mechanisms. Furthermore, the opportunities that CBRAMs provide for memory and brain-inspired neuromorphic computing applications, as well as the challenges that CBRAMs confront in those applications, are thoroughly discussed. The emulation of biological synapses and neurons using CBRAM devices fabricated with various switching materials and device engineering and material innovation approaches are examined in depth.
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10
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Reconfigurable Stochastic neurons based on tin oxide/MoS 2 hetero-memristors for simulated annealing and the Boltzmann machine. Nat Commun 2021; 12:5710. [PMID: 34588444 PMCID: PMC8481256 DOI: 10.1038/s41467-021-26012-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 09/09/2021] [Indexed: 11/08/2022] Open
Abstract
Neuromorphic hardware implementation of Boltzmann Machine using a network of stochastic neurons can allow non-deterministic polynomial-time (NP) hard combinatorial optimization problems to be efficiently solved. Efficient implementation of such Boltzmann Machine with simulated annealing desires the statistical parameters of the stochastic neurons to be dynamically tunable, however, there has been limited research on stochastic semiconductor devices with controllable statistical distributions. Here, we demonstrate a reconfigurable tin oxide (SnOx)/molybdenum disulfide (MoS2) heterogeneous memristive device that can realize tunable stochastic dynamics in its output sampling characteristics. The device can sample exponential-class sigmoidal distributions analogous to the Fermi-Dirac distribution of physical systems with quantitatively defined tunable "temperature" effect. A BM composed of these tunable stochastic neuron devices, which can enable simulated annealing with designed "cooling" strategies, is conducted to solve the MAX-SAT, a representative in NP-hard combinatorial optimization problems. Quantitative insights into the effect of different "cooling" strategies on improving the BM optimization process efficiency are also provided.
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11
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Chen X, Wang K, Shi B, Liu T, Chen R, Zhang M, Wen W, Xing G, Wu J. All-Inorganic Perovskite Nanorod Arrays with Spatially Randomly Distributed Lasing Modes for All-Photonic Cryptographic Primitives. ACS APPLIED MATERIALS & INTERFACES 2021; 13:30891-30901. [PMID: 34156815 DOI: 10.1021/acsami.1c08864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The level of hardware or information security can be increased by applying physical unclonable functions (PUFs), which have a high complexity and unique nonreplicability and are based on random physical patterns generated by nature, to anticounterfeiting and encryption technologies. The preparation of PUFs should be as simple and convenient as possible, while maintaining the high complexity and stability of PUFs to ensure high reliability in use. In this study, an all-inorganic perovskite single-crystal array with a controllable morphology and a random size was prepared by a one-step recrystallization method in a solvent atmosphere to generate all-photonic cryptographic primitives. The nondeterministic size of the perovskite nanorods mainly arises from crystal growth in an indeterminate direction, producing a high entropy for the system. The cavity-size-dependent lasing emission behavior of perovskite single crystals was investigated as a preliminary exploration of the generation of all-photonic cryptographic primitives. The lasing-mode number was positively correlated with the length of the perovskite nanorods. Therefore, the prepared perovskite nanorod array with random sizes can be transformed into a quaternary cryptographic key array following encoding rules based on the lasing-mode number. Superior lasing stability was observed for the all-inorganic perovskite under continuous excitation, demonstrating the high reliability of this system.
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Affiliation(s)
- Xinlian Chen
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
| | - Kaiyang Wang
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Bori Shi
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
| | - Tanghao Liu
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Riming Chen
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Mengying Zhang
- Department of Physics, Shanghai University, Shanghai 200444, China
| | - Weijia Wen
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
- Department of Physics, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Guichuan Xing
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Jinbo Wu
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
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12
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Wen C, Li X, Zanotti T, Puglisi FM, Shi Y, Saiz F, Antidormi A, Roche S, Zheng W, Liang X, Hu J, Duhm S, Roldan JB, Wu T, Chen V, Pop E, Garrido B, Zhu K, Hui F, Lanza M. Advanced Data Encryption using 2D Materials. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2100185. [PMID: 34046938 DOI: 10.1002/adma.202100185] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 03/23/2021] [Indexed: 05/25/2023]
Abstract
Advanced data encryption requires the use of true random number generators (TRNGs) to produce unpredictable sequences of bits. TRNG circuits with high degree of randomness and low power consumption may be fabricated by using the random telegraph noise (RTN) current signals produced by polarized metal/insulator/metal (MIM) devices as entropy source. However, the RTN signals produced by MIM devices made of traditional insulators, i.e., transition metal oxides like HfO2 and Al2 O3 , are not stable enough due to the formation and lateral expansion of defect clusters, resulting in undesired current fluctuations and the disappearance of the RTN effect. Here, the fabrication of highly stable TRNG circuits with low power consumption, high degree of randomness (even for a long string of 224 - 1 bits), and high throughput of 1 Mbit s-1 by using MIM devices made of multilayer hexagonal boron nitride (h-BN) is shown. Their application is also demonstrated to produce one-time passwords, which is ideal for the internet-of-everything. The superior stability of the h-BN-based TRNG is related to the presence of few-atoms-wide defects embedded within the layered and crystalline structure of the h-BN stack, which produces a confinement effect that avoids their lateral expansion and results in stable operation.
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Affiliation(s)
- Chao Wen
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
| | - Xuehua Li
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
| | - Tommaso Zanotti
- Dipartimento di Ingegneria "Enzo Ferrari", Università di Modena e Reggio Emilia, Modena, 41125, Italy
| | - Francesco Maria Puglisi
- Dipartimento di Ingegneria "Enzo Ferrari", Università di Modena e Reggio Emilia, Modena, 41125, Italy
| | - Yuanyuan Shi
- IMEC, Kapeldreef 75, Heverlee, Leuven, B-3001, Belgium
| | - Fernan Saiz
- Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - Aleandro Antidormi
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, Barcelona, E-08193, Spain
| | - Stephan Roche
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, Barcelona, E-08193, Spain
- ICREA, Institucio Catalana de Recerca i Estudis Avançats, Barcelona, E-08010, Spain
| | - Wenwen Zheng
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
| | - Xianhu Liang
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
| | - Jiaxin Hu
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
| | - Steffen Duhm
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
| | - Juan B Roldan
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias, Avd. Fuentenueva s/n, Granada, 18071, Spain
| | - Tianru Wu
- School of Physical Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai, 201210, China
| | - Victoria Chen
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Eric Pop
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Blas Garrido
- Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Martí i Franquès 1, Barcelona, E-08028, Spain
| | - Kaichen Zhu
- Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, 199 Ren Ai Road, Suzhou, 215123, China
- Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Martí i Franquès 1, Barcelona, E-08028, Spain
| | - Fei Hui
- Department of Materials Science and Engineering, Technion - Israel Institute of Technology, Haifa, 320003, Israel
| | - Mario Lanza
- Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
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13
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Torun N, Torun I, Sakir M, Kalay M, Onses MS. Physically Unclonable Surfaces via Dewetting of Polymer Thin Films. ACS APPLIED MATERIALS & INTERFACES 2021; 13:11247-11259. [PMID: 33587594 DOI: 10.1021/acsami.0c16846] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
From anti-counterfeiting to biotechnology applications, there is a strong demand for encoded surfaces with multiple security layers that are prepared by stochastic processes and are adaptable to deterministic fabrication approaches. Here, we present dewetting instabilities in nanoscopic (thickness <100 nm) polymer films as a form of physically unclonable function (PUF). The inherent randomness involved in the dewetting process presents a highly suitable platform for fabricating unclonable surfaces. The thermal annealing-induced dewetting of poly(2-vinyl pyridine) (P2VP) on polystyrene-grafted substrates enables fabrication of randomly positioned functional features that are separated at a microscopic length scale, a requirement set by optical authentication systems. At a first level, PUFs can be simply and readily verified via reflection of visible light. Area-specific electrostatic interactions between P2VP and citrate-stabilized gold nanoparticles allow for fabrication of plasmonic PUFs. The strong surface-enhanced Raman scattering by plasmonic nanoparticles together with incorporation of taggants facilitates a molecular vibration-based security layer. The patterning of P2VP films presents opportunities for fabricating hybrid security labels, which can be resolved through both stochastic and deterministic pathways. The adaptability to a broad range of nanoscale materials, simplicity, versatility, compatibility with conventional fabrication approaches, and high levels of stability offer key opportunities in encoding applications.
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Affiliation(s)
- Neslihan Torun
- ERNAM-Nanotechnology Research and Application Center, Erciyes University, Kayseri 38039, Turkey
| | - Ilker Torun
- ERNAM-Nanotechnology Research and Application Center, Erciyes University, Kayseri 38039, Turkey
- Department of Materials Science and Engineering, Erciyes University, Kayseri 38039, Turkey
| | - Menekse Sakir
- ERNAM-Nanotechnology Research and Application Center, Erciyes University, Kayseri 38039, Turkey
| | - Mustafa Kalay
- ERNAM-Nanotechnology Research and Application Center, Erciyes University, Kayseri 38039, Turkey
- Department of Electricity and Energy, Kayseri University, Kayseri 38039, Turkey
| | - M Serdar Onses
- ERNAM-Nanotechnology Research and Application Center, Erciyes University, Kayseri 38039, Turkey
- Department of Materials Science and Engineering, Erciyes University, Kayseri 38039, Turkey
- UNAM-Institute of Materials Science and Nanotechnology, Bilkent University, Ankara 06800, Turkey
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14
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Yang H, Wang Z, Guo X, Su H, Sun K, Yang D, Xiao W, Wang Q, He D. Controlled Growth of Fine Multifilaments in Polymer-Based Memristive Devices Via the Conduction Control. ACS APPLIED MATERIALS & INTERFACES 2020; 12:34370-34377. [PMID: 32627526 DOI: 10.1021/acsami.0c07533] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Solid polymer electrolyte (SPE) is one of the choices for many ionic devices, including organic transistors, ion batteries, memristors, and more. However, uncontrollable conductive filament formation seriously affects the performance of the device. In this paper, the PEDOT:PSS was doped to improve the electronic and ionic conductivity of amorphous polymer electrolyte poly(vinylpyrrolidone) (PVP), realizing the transition of the filaments growth from cathode to anode in atomic switch memristors. Based on the difference in ion and electron mobility and scanning electron microscope observation, the in situ reductions of metal ions inside the dielectric layer can effectively prevent the formation of uncontrollable filaments. The formation of uniformly distributed metal particles in the dielectric layer is similar to co-sputter doping technology, which enables the device to exhibit excellent performance, such as smaller set/reset bias distribution, endurance, and retention. Obviously, this innovative way improves the conductive mechanism of ionic devices.
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Affiliation(s)
- Huiyong Yang
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Zheng Wang
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Xiangyu Guo
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Hao Su
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Kai Sun
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Dongliang Yang
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Wei Xiao
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Qi Wang
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
| | - Deyan He
- School of Physical Science and Technology, Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, Lanzhou 730000, P. R. China
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15
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Zhou G, Wu J, Wang L, Sun B, Ren Z, Xu C, Yao Y, Liao L, Wang G, Zheng S, Mazumder P, Duan S, Song Q. Evolution map of the memristor: from pure capacitive state to resistive switching state. NANOSCALE 2019; 11:17222-17229. [PMID: 31531487 DOI: 10.1039/c9nr05550a] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Memristors possess great application prospects in terabit nonvolatile storage devices, memory-in-logic algorithmic chips and bio-inspired artificial neural network systems. However, "what is the origin state of the memristor?" has remained an unanswered question for half a century. While many applications rely on the memristor, its origin state is becoming a fundamental issue. Herein, we reveal a new state, the pure capacitance state (PCS), which occurs before the memristor is triggered, and the origin state of the memristor can be verified in the memory cells through controlling the ambience parameters. Discovery of the PCS, a missing earlier stage of the memristor, completes the whole evolution map of the memristor from the very beginning to the final developed state.
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Affiliation(s)
- Guangdong Zhou
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Jinggao Wu
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Lidan Wang
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Bai Sun
- School of Physical Science and Technology, Southwest Jiaotong University, Chengdu 610031, China
| | - Zhijun Ren
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Cunyun Xu
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Yanqing Yao
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Liping Liao
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Gang Wang
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Shaohui Zheng
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Pinaki Mazumder
- Department of Electrical Engineering and Computer Science, University of Michigan, 48109, USA.
| | - Shukai Duan
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
| | - Qunliang Song
- School of Mathematic and Statistic, School of Materials and Energy, College of Electronic and Information Engineering, School of Artificial Intelligence, Southwest University, Chongqing, 400715, China.
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16
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Wlaźlak E, Marzec M, Zawal P, Szaciłowski K. Memristor in a Reservoir System-Experimental Evidence for High-Level Computing and Neuromorphic Behavior of PbI 2. ACS APPLIED MATERIALS & INTERFACES 2019; 11:17009-17018. [PMID: 30986023 DOI: 10.1021/acsami.9b01841] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Lead halides in an asymmetric layered structure form memristive devices which are controlled by the electronic structure of the PbX2|metal interface. In this paper, we explain the mechanism that stands behind the I- V pinched hysteresis loop of the device and shortly present its synaptic-like plasticity (spike-timing-dependent plasticity and spike-rate-dependent plasticity) and nonvolatile memory effects. This memristive element was incorporated into a reservoir system, in particular, the echo-state network with delayed feedback, which exhibits brain-like recurrent behavior and demonstrates metaplasticity as one of the available learning mechanisms. It can serve as a classification system that classifies input signals according to their amplitude.
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Affiliation(s)
- E Wlaźlak
- Faculty of Chemistry , Jagiellonian University , ul. Gronostajowa 2 , 30-060 Kraków , Poland
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