Article
Nanoscience & Nanotechnology
Xuelian Zhang, Haohan Chen, Siqi Cheng, Feng Guo, Wenjing Jie, Jianhua Hao
Summary: This study investigates the resistive switching characteristics, synaptic functions, and neuromorphic computing of memristors based on two-dimensional MXene Ti3C2 nanosheets. The results show that both digital and analog resistive switching behaviors can coexist in these memristors depending on the magnitude of operation voltage. Additionally, the artificial synapses based on these memristors exhibit basic synaptic functions and successfully emulate the learning-forgetting experience. Moreover, the artificial synapses can be used to construct an artificial neural network for image recognition.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Automation & Control Systems
Wei Wang, Erika Covi, Alessandro Milozzi, Matteo Farronato, Saverio Ricci, Caterina Sbandati, Giacomo Pedretti, Daniele Ielmini
Summary: Motion detection is a primary visual function for the survival of animals, with direction-selective (DS) neurons playing a crucial role in the visual neural system. These neurons detect motion through spatiotemporal correlation within different receptive fields. Innovative memory devices with short-term memory effects can be used to achieve real-time neuromorphic processing of sensor data.
ADVANCED INTELLIGENT SYSTEMS
(2021)
Article
Nanoscience & Nanotechnology
Chi-Hsin Huang, Hsuan Chang, Tzu-Yi Yang, Yi-Chung Wang, Yu-Lun Chueh, Kenji Nomura
Summary: The study demonstrates a new type of gate-tunable memristor based on 2D-SnO2 material, which can achieve complex neuromorphic learning. By regulating the gate bias, the gate-tunable synaptic device dynamically modulates the analog switching behavior, while exhibiting excellent linearity and an improved conductance change ratio. This new device opens up new opportunities for advancing neuromorphic device technology.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Mathematics, Interdisciplinary Applications
Yuriy Gerasimov, Evgenii Zykov, Nikita Prudnikov, Max Talanov, Alexander Toschev, Victor Erokhin
Summary: This paper is dedicated to the experimental study of learning properties of systems, based on polyaniline (PANI) memristive devices. The study demonstrates the impact of signals with different forms, amplitudes, and frequencies on memristive device conductance, with pulse width modulation appearing as the most adequate method for implementing neuromorphic circuits.
CHAOS SOLITONS & FRACTALS
(2021)
Review
Chemistry, Multidisciplinary
Gregory Soon How Thien, Mohd Arif Mohd Sarjidan, Noor Azrina Talik, Boon Tong Goh, Boon Kar Yap, Zhicai He, Kah-Yoong Chan
Summary: This review discusses the impact of top electrode (TE) dependence on resistive switching (RS) characteristics in different materials used as potential candidates for memory devices. The relevance and importance of electrode dependence in the design of halide perovskite (HP) memories are highlighted through the exploration of electrode modification advances and techniques.
MATERIALS CHEMISTRY FRONTIERS
(2022)
Article
Chemistry, Physical
Anna N. Matsukatova, Artem Yu. Vdovichenko, Timofey D. Patsaev, Pavel A. Forsh, Pavel K. Kashkarov, Vyacheslav A. Demin, Andrey V. Emelyanov
Summary: This paper addresses the issue of high variability of memristive characteristics in brain-inspired neuromorphic computing systems and proposes methods to decrease the stochasticity of memristors and simplify the neural network architecture. Experiments show that optimizing the nanocomposite structure and performing post-fabrication annealing can improve the performance of memristors. Simulations demonstrate that neural networks based on these memristors have high classification accuracy and low variation in heart disease prediction. The controlled incorporation of nanocomposite memristors in neural networks shows promising prospects.
Article
Nanoscience & Nanotechnology
Kota Sugawara, Hisashi Shima, Makoto Takahashi, Yasuhisa Naitoh, Hiroshi Suga, Hiroyuki Akinaga
Summary: Research and development of resistive switching memories, such as ReRAM and memristors, are actively promoted for new computing techniques. The study used low-frequency-noise spectroscopy to investigate traps in conduction paths of a TaOx-based ReRAM device, revealing multiple trap levels at different temperatures, showcasing the device's advantage in analog resistive switching applications.
ADVANCED ELECTRONIC MATERIALS
(2022)
Article
Chemistry, Physical
Anna N. Matsukatova, Artem Yu. Vdovichenko, Timofey D. Patsaev, Pavel A. Forsh, Pavel K. Kashkarov, Vyacheslav A. Demin, Andrey V. Emelyanov
Summary: This paper addresses the issue of high variability in memristive characteristics and its negative effect on neural network training in parylene-based memristors. The study proposes methods to decrease internal stochasticity and simplify the neural network architecture of memristors, resulting in improved performance. The introduction of optimal Ag nanoparticle concentration and post-fabrication annealing show promising results in reducing voltage variation and increasing resistive switching window. The study also establishes a resistive switching mechanism for nanocomposite parylene-based memristors and demonstrates high classification accuracy with low variation in a formal neural network for heart disease prediction.
Article
Engineering, Electrical & Electronic
Chengcheng Wang, Bo Chen, Junyao Mei, Lu Tai, Yueran Qi, Yuan Gao, Jixuan Wu, Xuepeng Zhan, Jiezhi Chen
Summary: A complementary memristor cell based on monolayer AlOx film is proposed, with analog and digital resistive switching behaviors. Typical synapse behaviors are emulated in different working modes, and the cell shows low/high accuracies with different power consumption in the MNIST recognition task. These findings provide potential for energy-efficient and feasible neuro-morphic computing based on AlOx monolayer memristors.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2023)
Article
Chemistry, Physical
Min-Kyu Song, Seok Daniel Namgung, Hojung Lee, Jeong Hyun Yoon, Young-Woong Song, Kang Hee Cho, Yoon-Sik Lee, Jong-Seok Lee, Ki Tae Nam, Jang-Yeon Kwon
Summary: This study investigates the gradual switching phenomenon in peptide-based memristors under high proton conductivity. The unexpected high slope value in the log/-V curve at low voltage leads to significantly increased accuracy of image recognition.
Article
Polymer Science
Han-Hyeong Choi, Hyun Jin Kim, Jinwoo Oh, Minsung Kim, Youngjin Kim, Jae Young Jho, Keun Hyung Lee, Jeong Gon Son, Jong Hyuk Park
Summary: An effective and simple approach for fabricating complementary resistive switching (CRS) memory devices using self-assembled block copolymer micelles is reported. This approach can reduce sneak currents and achieve position selectivity during resistive switching.
MACROMOLECULAR RAPID COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Shaobo Cheng, Min-Han Lee, Xing Li, Lorenzo Fratino, Federico Tesler, Myung-Geun Han, Javier Del Valle, R. C. Dynes, Marcelo J. Rozenberg, Ivan K. Schuller, Yimei Zhu
Summary: Vanadium dioxide (VO2) is capable of metal-insulator transition and resistive switching, making it suitable for neuromorphic computing hardware. This study reveals the mechanisms of both volatile and nonvolatile switching in VO2, which can emulate neuronal and synaptic behaviors, respectively, providing a comprehensive understanding of resistive switching crucial for neuromorphic computing development.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Chemistry, Multidisciplinary
Shaochuan Chen, Ilia Valov
Summary: Redox-based resistive random access memories (ReRAMs) rely on electrochemical processes involving oxidation and reduction within devices. Material selection plays a crucial role in resistive switching properties. The study explores the impact of materials configuration on redox reactions in HfO2-based ECM and VCM systems, highlighting the influence of capping layer materials and electrode configuration on resistive switching characteristics.
ADVANCED MATERIALS
(2022)
Article
Chemistry, Physical
Li Zhang, Zhenhua Tang, Junlin Fang, Xiujuan Jiang, Yan-Ping Jiang, Qi-Jun Sun, Jing-Min Fan, Xin-Gui Tang, Gaokuo Zhong
Summary: Artificial neural network-based computing has the potential to overcome the limitations of conventional computers and has a wide range of applications. By using NiO/Cu2O memristors to emulate biological synapses, the recognition accuracy of an artificial neural network based on synaptic weight modulation reached up to 96.84% on average, demonstrating the potential of artificial synapses in artificial intelligence systems.
APPLIED SURFACE SCIENCE
(2022)
Article
Materials Science, Multidisciplinary
B. Sun, S. Ranjan, G. Zhou, T. Guo, Y. Xia, L. Wei, Y. N. Zhou, Y. A. Wu
Summary: Resistive random-access memory provides dual functionalities of data storage and computing at the same position, making it a promising candidate for energy efficient neuromorphic computing. The key points to realize neuromorphic computing include selection of functional materials, design of multistate devices, and complete logic function implementation in-memory computing. A memristor device with stable intermediate multistate resistive switching behaviors has been demonstrated, which enables simulated pixel data storage and 2-bit parallel logic computations for neuromorphic computing.
MATERIALS TODAY ADVANCES
(2021)
Article
Chemistry, Multidisciplinary
Zining Sun, Huanyu Liang, Huanlei Wang, Jing Shi, Minghua Huang, Jingwei Chen, Shuai Liu, Weiqian Tian, Haijie Cao, Zhi Li
Summary: In this study, a compact nanostructure with embedded Ni-Ni3S2 nanoparticles in S-doped carbon matrix was constructed for fast electron/ion transport and high volumetric capacity. The Ni-Ni3S2@SC anode exhibited superior rate capability, stable cycling performance, and exceptional volumetric capacity in sodium/potassium ion batteries. The spatially confined edge-to-edge strategy could be applied to construct various metal sulfide dense electrodes for advanced energy storage devices.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Jowan Rostami, Tobias Benselfelt, Lorenza Maddalena, Civan Avci, Farhiya Alex Sellman, Goksu Cinar Ciftci, Per A. Larsson, Federico Carosio, Farid Akhtar, Weiqian Tian, Lars Wagberg
Summary: Metal-organic frameworks (MOFs) are hybrid porous crystalline networks with tunable properties. However, their powder form limits their practical applications. To overcome this challenge, nanoMOFs are combined with cellulose nanofibrils to create robust MOF-based aerogels with high MOF content, which show excellent potential for various applications.
ADVANCED MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Scott T. Keene, Wesley Michaels, Armantas Melianas, Tyler J. Quill, Elliot J. Fuller, Alexander Giovannitti, Iain McCulloch, A. Alec Talin, Christopher J. Tassone, Jian Qin, Alessandro Troisi, Alberto Salleo
Summary: Traditional electronic transport models for conducting polymers focus on conjugated chains and ignore the contributions of nominally insulating components. This study demonstrates that the chemical structure of the non-conductive component has a significant effect on charge carrier mobility. By diluting the conducting polymer with excess insulator, blends with high insulator content can exhibit carrier mobilities comparable to pure conducting polymers. A single, multiscale transport model based on the microstructure of the polymer blends is developed to describe the transport properties for different dilutions. The results reveal that the high carrier mobility in primarily insulator blends is achieved through long-range tunneling mechanism facilitated by aromatic rings.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Chemistry, Physical
Yucheng Li, Liyu Zhu, Jingyang Zhao, Mengjie Qiu, Jing Liu, Jing He, Luying Wang, Jiandu Lei, Weiqian Tian, Long Rong
Summary: A high-efficiency nickel-iron bimetallic catalyst with excellent hydrogenation performance and stability was synthesized. The introduction of Fe element formed a protective NiFe2O4 layer on the catalyst surface, enhancing hydrogen adsorption capacity and resistance to oxidation. The introduction of Na element further improved the purity of the catalyst and the interaction between Ni and Fe, leading to enhanced hydrogenation performance. The reaction mechanism was systematically investigated using density functional theory (DFT) calculations.
CATALYSIS SCIENCE & TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Georgios Chondrogiannis, Pedro Reu, Mahiar M. Hamedi
Summary: Nucleic acid amplification testing (NAAT) is the gold standard for infectious disease diagnostics, but it is mainly limited to centralized laboratories. Researchers have addressed the bottleneck issue of DNA extraction by immobilizing the enzyme ACP on nitrocellulose, enabling home-based kits and expanding the capabilities of home-testing beyond antigen tests.
ADVANCED MATERIALS TECHNOLOGIES
(2023)
Article
Chemistry, Physical
Tyler J. Quill, Garrett LeCroy, David M. Halat, Rajendar Sheelamanthula, Adam Marks, Lorena S. Grundy, Iain McCulloch, Jeffrey A. Reimer, Nitash P. Balsara, Alexander Giovannitti, Alberto Salleo, Christopher J. Takacs
Summary: A polymer semiconductor/ionic-liquid nanocomposite with mixed conduction was studied. Dynamic structural changes during electrochemical charging were observed using operando X-ray scattering, enabling efficient electronic transport. This unique dual-network microstructure resulted in a dynamic ionic/electronic nanocomposite with liquid-like ionic transport and highly mobile electronic charges. The ordered structure of the nanocomposite and mechanisms leading to efficient electron transport were confirmed using operando X-ray scattering and in situ spectroscopy.
Article
Chemistry, Multidisciplinary
Tobias Benselfelt, Jyoti Shakya, Philipp Rothemund, Stefan B. Lindstrom, Andrew Piper, Thomas E. Winkler, Alireza Hajian, Lars Wagberg, Christoph Keplinger, Mahiar Max Hamedi
Summary: By electronically controlling conductive hydrogels, the limitations of stimuli-responsive hydrogels can be overcome and enable direct integration with modern electronic systems. This materials system allows precise shape-morphing, with high tunability and adaptability, paving the way for the design of advanced soft intelligent systems.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Garrett LeCroy, Camila Cendra, Tyler J. Quill, Maximilian Moser, Rawad Hallani, James F. Ponder Jr, Kevin Stone, Stephen D. Kang, Allen Yu-Lun Liang, Quentin Thiburce, Iain McCulloch, Frank C. Spano, Alexander Giovannitti, Alberto Salleo
Summary: This study explores the fundamental electrochemical charging mechanisms of organic mixed ionic-electronic conductors (OMIECs). By combining in situ electronic charge transport measurements, spectroelectrochemistry, and ex situ X-ray scattering electrochemical charging experiments, the researchers find that polymer chains planarize during electrochemical charging. The most effective conductivity modulation is achieved through the formation of well-ordered, interconnected aggregates that host high mobility electronic charge carriers.
MATERIALS HORIZONS
(2023)
Article
Materials Science, Multidisciplinary
Sam Gielen, Virginia Cuesta Gomez, Sonny Brebels, Tyler James Quill, Jochen Vanderspikken, Laurence Lutsen, Pilar de la Cruz, Koen Vandewal, Fernando Langa, Wouter Maes
Summary: This study presents the design and synthesis of novel push-pull type meso-ethynyl-extended porphyrin compounds and their evaluation in near-infrared organic photodetectors. The compounds show excellent light absorption performance and photoconversion efficiency, making them promising candidates for small molecule-based near-infrared photodetectors.
JOURNAL OF MATERIALS CHEMISTRY C
(2022)
Article
Chemistry, Physical
Jiawei Wei, Ping Li, Jing Shi, Minghua Huang, Weiqian Tian, Huanlei Wang
Summary: This study presents a facile and effective strategy for designing high-performance carbon-based oxygen reduction catalysts. The N/S co-doped carbon catalysts achieved a large specific surface area, hierarchical porous structure, and rich defective sites, exhibiting excellent oxygen reduction reaction activity and stability. Furthermore, the assembled zinc-air battery with this catalyst as the air cathode showed superior electrochemical performance compared to the traditional Pt/C catalyst.
SUSTAINABLE ENERGY & FUELS
(2022)
Article
Chemistry, Physical
Yuxiao Cui, Chandrasekar M. Subramaniyam, Lengwan Li, Tong Han, Min-A Kang, Jian Li, Luyao Zhao, Xinfeng Wei, Anna J. Svagan, Mahiar M. Hamedi
Summary: This study proposes a simple and rapid method to address the low conductivity and structural instability issues of amorphous hard carbon. By using an emulsion solvent-evaporation method, hierarchically structured microparticles of hard carbon with increased surface area and improved electronic conductivity were created. The experimental results demonstrate that hierarchical self-assembly is an attractive approach for enhancing the performance of microparticles used in battery production.
JOURNAL OF MATERIALS CHEMISTRY A
(2022)