A hybrid nanomemristor/transistor logic circuit capable of self-programming
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Memristor crossbars were fabricated at 40 nm half-pitch, using nanoimprint lithography on the same substrate with Si metal-oxide-semiconductor field effect transistor (MOS FET) arrays to form fully integrated hybrid memory resistor (memristor)/transistor circuits. The digitally configured memristor crossbars were used to perform logic functions, to serve as a routing fabric for interconnecting the FETs and as the target for storing information. As an illustrative demonstration, the compound Boolean logic operation (A AND B) OR (C AND D) was performed with kilohertz frequency inputs, using resistor-based logic in a memristor crossbar with FET inverter/amplifier outputs. By routing the output signal of a logic operation back onto a target memristor inside the array, the crossbar was conditionally configured by setting the state of a nonvolatile switch. Such conditional programming illuminates the way for a variety of self-programmed logic arrays, and for electronic synaptic computing.
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Memristors can be used to implement digital logic, synapses in neural applications, and hybrid circuits.
“They can also be used to implement digital logic [9], synapses in neural applications [10,11], and hybrid circuits [6,12].”
From Sub-nanosecond switching of a tantalum oxide memristor (2011) · cites this paper as [12]
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Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008) · Nature · doi:10.1038/nature06932 · Cited by 11,744 · see citing works
Self-citationMemristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268 · cited 4× · see citing works
“Memristance is very interesting for a variety of digital and analog switching applications (1, 2), especially because a memristor does not lose its state when the electrical power is turned off (the memory is nonvolatile).”
BackgroundInfluentialConductance of a Molecular Junction
Reed, M. A., Zhou, C., Muller, C. J., Burgin, T. P., & Tour, J. M. (1997) · Science · doi:10.1126/science.278.5336.252 · Cited by 3,463 · see citing works
Memristive switching mechanism for metal/oxide/metal nanodevices
Yang, J. J., Pickett, M. D., Li, X., Ohlberg, D. A. A., Stewart, D. R., & Williams, R. S. (2008) · Nature Nanotechnology · doi:10.1038/nnano.2008.160 · Cited by 2,987 · see citing works
Self-citationMemristive devices and systems
Chua, L. O., & Kang, S. M. (1976) · Proceedings of the IEEE · doi:10.1109/proc.1976.10092 · Cited by 2,604 · see citing works
Imprint Lithography with 25-Nanometer Resolution
Chou, S. Y., Krauss, P. R., & Renstrom, P. J. (1996) · Science · doi:10.1126/science.272.5258.85 · Cited by 2,285 · see citing works
Logic Gates and Computation from Assembled Nanowire Building Blocks
Huang, Y., Duan, X., Cui, Y., Lauhon, L. J., Kim, K.-H., & Lieber, C. M. (2001) · Science · doi:10.1126/science.1066192 · Cited by 2,125 · see citing works
Carbon Nanotube-Based Nonvolatile Random Access Memory for Molecular Computing
Rueckes, T., Kim, K., Joselevich, E., Tseng, G. Y., Cheung, C. L., & Lieber, C. M. (2000) · Science · doi:10.1126/science.289.5476.94 · Cited by 1,716 · see citing works
Electronically Configurable Molecular-Based Logic Gates
Collier, C. P., Wong, E. W., Bělohradský, M., Raymo, F. M., Stoddart, J. F., Kuekes, P. J., Williams, R. S., & Heath, J. R. (1999) · Science · doi:10.1126/science.285.5426.391 · Cited by 1,519 · see citing works
Self-citationConductance Switching in Single Molecules Through Conformational Changes
Donhauser, Z. J., Mantooth, B. A., Kelly, K. F., Bumm, L. A., Monnell, J. D., Stapleton, J. J., Price, D. W. J., Rawlett, A. M., Allara, D. L., Tour, J. M., et al. (2001) · Science · doi:10.1126/science.1060294 · Cited by 1,246 · see citing works
A Defect-Tolerant Computer Architecture: Opportunities for Nanotechnology
Heath, J. R., Kuekes, P. J., Snider, G. S., & Williams, R. S. (1998) · Science · doi:10.1126/science.280.5370.1716 · Cited by 889 · see citing works
Self-citationHeath, J. R., & Ratner, M. A. (2003) · Physics Today · doi:10.1063/1.1583533 · Cited by 742 · see citing works
Nanoscale molecular-switch crossbar circuits
Chen, Y., Jung, G. Y., Ohlberg, D. A. A., Li, X., Stewart, D. R., Jeppesen, J. O., Nielsen, K. A., Stoddart, J. F., & Williams, R. S. (2003) · Nanotechnology · doi:10.1088/0957-4484/14/4/311 · Cited by 637 · see citing works
Self-citationCMOL FPGA: a reconfigurable architecture for hybrid digital circuits with two-terminal nanodevices
Strukov, D. B., & Likharev, K. K. (2005) · Nanotechnology · doi:10.1088/0957-4484/16/6/045 · Cited by 506 · see citing works
Walmsley, I. A., & RABITZ, H. A. (2003) · Physics Today · doi:10.1063/1.1611352 · Cited by 418 · see citing works
Array-based architecture for FET-based, nanoscale electronics
DeHon, A. M. (2003) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2003.808508 · Cited by 377 · see citing works
Nano/CMOS architectures using a field-programmable nanowire interconnect
Snider, G. S., & Williams, R. S. (2007) · Nanotechnology · doi:10.1088/0957-4484/18/3/035204 · Cited by 364 · see citing works
Self-citationSpike-timing-dependent learning in memristive nanodevices
Snider, G. S. (2008) · 2008 IEEE International Symposium on Nanoscale Architectures · doi:10.1109/nanoarch.2008.4585796 · Cited by 341 · see citing works
Switching phenomena in titanium oxide thin films
Argall, F. (1968) · Solid-State Electronics · doi:10.1016/0038-1101(68)90092-0 · Cited by 308 · see citing works
Molecular electronics: from devices and interconnect to circuits and architecture
Stan, M. R., Franzon, P. D., Goldstein, S. C., Lach, J., & Ziegler, M. M. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.818327 · Cited by 278 · see citing works
Self-organized computation with unreliable, memristive nanodevices
Snider, G. S. (2007) · Nanotechnology · doi:10.1088/0957-4484/18/36/365202 · Cited by 264 · see citing works
A nonvolatile programmable solid-electrolyte nanometer switch
Kaeriyama, S., Sakamoto, T., Sunamura, H., Mizuno, M., Kawaura, H., Hasegawa, T., Terabe, K., Nakayama, T., & Aono, M. (2005) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2004.837244 · Cited by 217 · see citing works
Direct Observation of Nanoscale Switching Centers in Metal/Molecule/Metal Structures
Lau, C. N., Stewart, D. R., Williams, R. S., & Bockrath, M. (2004) · Nano Letters · doi:10.1021/nl035117a · Cited by 217 · see citing works
Self-citationThe crossbar latch: Logic value storage, restoration, and inversion in crossbar circuits
Kuekes, P. J., Stewart, D. R., & Williams, R. S. (2004) · Journal of Applied Physics · doi:10.1063/1.1823026 · Cited by 186 · see citing works
Self-citationCircuit Fabrication at 17 nm Half-Pitch by Nanoimprint Lithography
Jung, G. Y., Johnston‐Halperin, E., Wu, W., Yu, Z., Wang, S.-Y., Tong, W. M., Li, Z., Green, J. E., Sheriff, B. A., Boukai, A. I., et al. (2006) · Nano Letters · doi:10.1021/nl052110f · Cited by 172 · see citing works
Self-citationComputing with hysteretic resistor crossbars
Snider, G. (2005) · Applied Physics A · doi:10.1007/s00339-004-3149-1 · Cited by 141 · see citing works
CrossNets: High‐Performance Neuromorphic Architectures for CMOL Circuits
LIKHAREV, K., MAYR, A., MUCKRA, I., & TÜREL, Ö. (2003) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1292.010 · Cited by 121 · see citing works
Reconfigurable Hybrid CMOS/Nanodevice Circuits for Image Processing
Strukov, D. B., & Likharev, K. K. (2007) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2007.907841 · Cited by 51 · see citing works
Fabrication and test of nano crossbar switches/MOSFET hybrid circuits by imprinting lithography
Li, Z., Li, X., Ohlberg, D. A. A., Straznicky, J., Wu, W., Yu, Z., Borghetti, J. L., Tong, W. M., Stewart, D. R., & Williams, R. S. (2008) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.774144 · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Nanoscale Memristor Device as Synapse in Neuromorphic Systems
Jo, S. H., Chang, T., Ebong, I., Bhadviya, B. B., Mazumder, P., & Lu, W. (2010) · Nano Letters · doi:10.1021/nl904092h · Cited by 4,174 · see citing works
The future of electronics based on memristive systems
Zidan, M. A., Strachan, J. P., & Lu, W. D. (2018) · Nature Electronics · doi:10.1038/s41928-017-0006-8 · Cited by 2,138 · see citing works
‘Memristive’ switches enable ‘stateful’ logic operations via material implication
Borghetti, J., Snider, G. S., Kuekes, P. J., Yang, J. J., Stewart, D. R., & Williams, R. S. (2010) · Nature · doi:10.1038/nature08940 · Cited by 1,929 · see citing works
Self-citationExperimental demonstration of associative memory with memristive neural networks
Pershin, Y. V., & Di Ventra, M. (2010) · Neural Networks · doi:10.1016/j.neunet.2010.05.001 · Cited by 1,041 · see citing works
Kim, K.-H., Gaba, S., Wheeler, D., Cruz-Albrecht, J. M., Hussain, T., Srinivasa, N., & Lu, W. (2012) · Nano Letters · doi:10.1021/nl203687n · Cited by 924 · see citing works
Memory effects in complex materials and nanoscale systems
Pershin, Y. V., & Di Ventra, M. (2011) · Advances In Physics · doi:10.1080/00018732.2010.544961 · Cited by 823 · see citing works
Yu, S., Wu, Y., Jeyasingh, R., Kuzum, D., & Wong, H.-S. P. (2011) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2011.2147791 · Cited by 805 · see citing works
Sub-nanosecond switching of a tantalum oxide memristor
Torrezan, A. C., Strachan, J. P., Medeiros-Ribeiro, G., & Williams, R. S. (2011) · Nanotechnology · doi:10.1088/0957-4484/22/48/485203 · Cited by 701 · see citing works
Self-citationIf it's pinched it's a memristor
Chua, L. (2014) · Semiconductor Science and Technology · doi:10.1088/0268-1242/29/10/104001 · Cited by 685 · see citing works
Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies
Kvatinsky, S., Satat, G., Wald, N., Friedman, E. G., Avinoam Kolodny, A., & Weiser, U. C. (2013) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · doi:10.1109/tvlsi.2013.2282132 · Cited by 680 · see citing works
Practical Approach to Programmable Analog Circuits With Memristors
Pershin, Y. V., & Di Ventra, M. (2010) · IEEE Transactions on Circuits and Systems I: Regular Papers · doi:10.1109/tcsi.2009.2038539 · Cited by 639 · see citing works
High switching endurance in TaOx memristive devices
Yang, J. J., Zhang, M.-X., Strachan, J. P., Miao, F., Pickett, M. D., Kelley, R. D., Medeiros-Ribeiro, G., & Williams, R. S. (2010) · Applied Physics Letters · doi:10.1063/1.3524521 · Cited by 637 · see citing works
Self-citationOn Spike-Timing-Dependent-Plasticity, Memristive Devices, and Building a Self-Learning Visual Cortex
Zamarreño-Ramos, C., Camuñas-Mesa, L. A., Pérez‐Carrasco, J. A., Masquelier, T., Serrano‐Gotarredona, T., & Linares-Barranco, B. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00026 · Cited by 558 · see citing works
STDP and STDP variations with memristors for spiking neuromorphic learning systems
Serrano‐Gotarredona, T., Masquelier, T., Prodromakis, T., Indiveri, G., & Linares-Barranco, B. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00002 · Cited by 531 · see citing works
Memristor-based neural networks
Thomas, A. (2013) · Journal of Physics D: Applied Physics · doi:10.1088/0022-3727/46/9/093001 · Cited by 471 · see citing works
Synaptic behaviors and modeling of a metal oxide memristive device
Chang, T., Jo, S.-H., Kim, K.-H., Sheridan, P., Gaba, S., & Lu, W. (2011) · Applied Physics A · doi:10.1007/s00339-011-6296-1 · Cited by 432 · see citing works
Pickett, M. D., & Stanley Williams, R. (2012) · Nanotechnology · doi:10.1088/0957-4484/23/21/215202 · Cited by 385 · see citing works
Self-citationPhase-transition driven memristive system
Driscoll, T., Kim, H.-T., Chae, B.-G., Ventra, M. D., & Basov, D. N. (2009) · Applied Physics Letters · doi:10.1063/1.3187531 · Cited by 380 · see citing works
An Organic Nanoparticle Transistor Behaving as a Biological Spiking Synapse
Alibart, F., Pleutin, S., Guérin, D., Novembre, C., Lenfant, S., Lmimouni, K., Gamrat, C., & Vuillaume, D. (2009) · Advanced Functional Materials · doi:10.1002/adfm.200901335 · Cited by 377 · see citing works
Logic Design Within Memristive Memories Using Memristor-Aided loGIC (MAGIC)
Talati, N., Gupta, S., Mane, P. S., & Kvatinsky, S. (2016) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2016.2570248 · Cited by 341 · see citing works
Dynamical Properties and Design Analysis for Nonvolatile Memristor Memories
Ho, Y., Huang, G. M., & Li, P. (2010) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2010.2078710 · Cited by 331 · see citing works
Adaptive oxide electronics: A review
Ha, S. D., & Ramanathan, S. (2011) · Journal of Applied Physics · doi:10.1063/1.3640806 · Cited by 305 · see citing works
Seo, K., Kim, I., Jung, S., Jo, M., Park, S., Park, J., Shin, J., Biju, K. P., Kong, J., Lee, K., et al. (2011) · Nanotechnology · doi:10.1088/0957-4484/22/25/254023 · Cited by 286 · see citing works
Chua, L. O. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2190814 · Cited by 284 · see citing works
Ho, Y., Huang, G. M., & Li, P. (2009) · doi:10.1145/1687399.1687491 · Cited by 272 · see citing works
Neuromorphic, Digital, and Quantum Computation With Memory Circuit Elements
Pershin, Y. V., & Ventra, M. D. (2011) · Proceedings of the IEEE · doi:10.1109/jproc.2011.2166369 · Cited by 261 · see citing works
Kvatinsky, S., Wald, N., Satat, G., Avinoam Kolodny, A., Weiser, U. C., & Friedman, E. G. (2012) · International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) · doi:10.1109/cnna.2012.6331426 · Cited by 256 · see citing works
A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing
Sillin, H. O., Aguilera, R., Shieh, H.-H., Avizienis, A. V., Aono, M., Stieg, A. Z., & Gimzewski, J. K. (2013) · Nanotechnology · doi:10.1088/0957-4484/24/38/384004 · Cited by 255 · see citing works
A Family of Electronically Reconfigurable Nanodevices
Yang, J. J., Borghetti, J. L., Murphy, D. L. K., Stewart, D. R., & Williams, R. S. (2009) · Advanced Materials · doi:10.1002/adma.200900822 · Cited by 231 · see citing works
Self-citationEmerging Memristor-Based Logic Circuit Design Approaches: A Review
Vourkas, I., & Sirakoulis, G. C. (2016) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2016.2583673 · Cited by 225 · see citing works
Memristors: Devices, Models, and Applications [Scanning the Issue]
Mazumder, P., Kang, S. M., & Waser, R. M. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2190812 · Cited by 201 · see citing works
Driscoll, T., Quinn, J., Klein, S., Kim, H. T., Kim, B.-S., Pershin, Y. V., Ventra, M. D., & Basov, D. N. (2010) · Applied Physics Letters · doi:10.1063/1.3485060 · Cited by 198 · see citing works
Nanoscale resistive memory with intrinsic diode characteristics and long endurance
Kim, K.-H., Hyun Jo, S., Gaba, S., & Lu, W. (2010) · Applied Physics Letters · doi:10.1063/1.3294625 · Cited by 187 · see citing works
Tunable synaptic behavior realized in C3N composite based memristor
Zhou, L., Yang, S., Ding, G., Yang, J., Ren, Y., Zhang, S., Mao, J., Yang, Y., Zhou, Y., & Han, S. (2019) · Nano Energy · doi:10.1016/j.nanoen.2019.01.045 · Cited by 172 · see citing works
Memristor: A New Concept in Synchronization of Coupled Neuromorphic C ircuits
VOLOS, C. K., Kyprianidis, I. M., Stouboulos, I. N., Cuautle, E. T. , & Vaidyanathan, S. V. (2015) · Journal of Engineering Science and Technology Review · doi:10.25103/jestr.082.21 · Cited by 171 · see citing works
Metal/TiO2 interfaces for memristive switches
Yang, J. J., Strachan, J. P., Miao, F., Zhang, M.-X., Pickett, M. D., Yi, W., Ohlberg, D. A. A., Medeiros‐Ribeiro, G., & Williams, R. S. (2011) · Applied Physics A · doi:10.1007/s00339-011-6265-8 · Cited by 160 · see citing works
Self-citationIn-memory computing with emerging memory devices: Status and outlook
Mannocci, P., Farronato, M., Lepri, N., Cattaneo, L., Glukhov, A., Sun, Z., & Ielmini, D. (2023) · APL Machine Learning · doi:10.1063/5.0136403 · Cited by 152 · see citing works
Memristive-biosensors: A new detection method by using nanofabricated memristors
Carrara, S., Sacchetto, D., Doucey, M., Baj-Rossi, C., Micheli, G. D., & Leblebici, Y. (2012) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2012.04.089 · Cited by 135 · see citing works
A Novel Design and Modeling Paradigm for Memristor-Based Crossbar Circuits
Vourkas, I., & Sirakoulis, G. C. (2012) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2012.2217153 · Cited by 132 · see citing works
Hyperchaos and horseshoe in a 4D memristive system with a line of equilibria and its implementation
Li, Q., Hu, S., Tang, S., & Zeng, G. Z. (2013) · International Journal of Circuit Theory and Applications · doi:10.1002/cta.1912 · Cited by 120 · see citing works
Lee, T. S., Lee, N. J., Abbas, H., Lee, H. H., Yoon, T., & Kang, C. J. (2020) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.0c00128 · Cited by 118 · see citing works
Charge transport through molecular ensembles: Recent progress in molecular electronics
Liu, Y., Qiu, X., Soni, S., & Chiechi, R. C. (2021) · Chemical Physics Reviews · doi:10.1063/5.0050667 · Cited by 112 · see citing works
An organic–inorganic hybrid perovskite logic gate for better computing
Lin, G., Lin, Y., Cui, R., Huang, H., Guo, X., Li, C., Dong, J., Guo, X., & Sun, B. (2015) · Journal of Materials Chemistry C · doi:10.1039/c5tc02270c · Cited by 101 · see citing works
Leaky Integrate-and-Fire Biristor Neuron
Han, J.-W., & Meyyappan, M. (2018) · IEEE Electron Device Letters · doi:10.1109/led.2018.2856092 · Cited by 99 · see citing works
Electrical transport and thermometry of electroformed titanium dioxide memristive switches
Borghetti, J. L., Strukov, D. B., Pickett, M. D., Yang, J. J., Stewart, D. R., & Williams, R. S. (2009) · Journal of Applied Physics · doi:10.1063/1.3264621 · Cited by 100 · see citing works
Self-citationDevice and SPICE modeling of RRAM devices
Sheridan, P., Kim, K.-H., Gaba, S., Chang, T., Chen, L., & Lu, W. (2011) · Nanoscale · doi:10.1039/c1nr10557d · Cited by 98 · see citing works
A Memristor with Low Switching Current and Voltage for 1S1R Integration and Array Operation
Upadhyay, N. K., Sun, W. B., Lin, P., Joshi, S., Midya, R., Zhang, X., Wang, Z., Jiang, H., Yoon, J. H., Rao, M., et al. (2020) · Advanced Electronic Materials · doi:10.1002/aelm.201901411 · Cited by 95 · see citing works
Matveyev, Y., Egorov, K. V., Markeev, A. M., & Zenkevich, A. V. (2015) · Journal of Applied Physics · doi:10.1063/1.4905792 · Cited by 93 · see citing works
Polyfluorene-Based Push−Pull Type Functional Materials for Write-Once-Read-Many-Times Memory Devices
Zhuang, X., Chen, Y., Li, B., Ma, D., Zhang, B., & Li, Y. (2010) · Chemistry of Materials · doi:10.1021/cm1012872 · Cited by 92 · see citing works
Ultra-Efficient Processing In-Memory for Data Intensive Applications
Imani, M., Gupta, S., & Rosing, T. (2017) · ACM/IEEE Design Automation Conference (DAC) · doi:10.1145/3061639.3062337 · Cited by 91 · see citing works
Design Exploration of Hybrid CMOS and Memristor Circuit by New Modified Nodal Analysis
Fei, W., Yu, H., Zhang, W., & Yeo, K. S. (2011) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · doi:10.1109/tvlsi.2011.2136443 · Cited by 91 · see citing works
From Memristive Materials to Neural Networks
Guo, T., Sun, B. T., Ranjan, S., Jiao, Y., Wei, L., Zhou, Y., & Wu, Y. A. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c10796 · Cited by 87 · see citing works
Spin-wave interference patterns created by spin-torque nano-oscillators for memory and computation
Macià, F., Kent, A. D., & Hoppensteadt, F. C. (2011) · Nanotechnology · doi:10.1088/0957-4484/22/9/095301 · Cited by 82 · see citing works
Memristor PUF—A Security Primitive: Theory and Experiment
Mazady, A., Rahman, M. T., Forte, D. J., & Anwar, M. F. (2015) · IEEE Journal on Emerging and Selected Topics in Circuits and Systems · doi:10.1109/jetcas.2015.2435532 · Cited by 82 · see citing works
Implementation and study of the nonlinear dynamics of a memristor-based Duffing oscillator
Sabarathinam, S., VOLOS, C. K., & Thamilmaran, K. (2016) · Nonlinear Dynamics · doi:10.1007/s11071-016-3022-8 · Cited by 81 · see citing works
Lee, J., Ryu, J., Kim, B., Hussain, F. A., Mahata, C., Sim, E., Ismail, M., Abbas, Y., Abbas, H., Lee, D. K., et al. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c07867 · Cited by 78 · see citing works
Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications
Bose, S. K., Mallinson, J. B., Gazoni, R. M., & Brown, S. A. (2017) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2017.2766063 · Cited by 77 · see citing works
Memristor-CMOS logic and digital computational components
Cho, K.-R., Lee, S.-J., & Eshraghian, K. (2015) · Microelectronics Journal · doi:10.1016/j.mejo.2014.12.006 · Cited by 75 · see citing works
Optimization of non-linear conductance modulation based on metal oxide memristors
Liu, H., Wei, M., & Chen, Y. (2018) · Nanotechnology Reviews · doi:10.1515/ntrev-2018-0045 · Cited by 73 · see citing works
If It’s Pinched It’s a Memristor
Chua, L. O. (2013) · Springer eBooks · doi:10.1007/978-1-4614-9068-5_2 · Cited by 70 · see citing works
A Proposal for Hybrid Memristor-CMOS Spiking Neuromorphic Learning Systems
Serrano‐Gotarredona, T., Prodromakis, T., & Linares-Barranco, B. (2013) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2013.2256271 · Cited by 69 · see citing works
Applications of nanoimprint lithography/hot embossing: a review
Chen, Y. (2015) · Applied Physics A · doi:10.1007/s00339-015-9071-x · Cited by 69 · see citing works
Efficient Image Encryption Using a Chaos-based PWL Memristor
Lin, Z., & Wang, H. (2010) · IETE Technical Review · doi:10.4103/0256-4602.64605 · Cited by 68 · see citing works
A Novel Nondestructive Read/Write Circuit for Memristor-Based Memory Arrays
Elshamy, M. R., Mostafa, H., Ghallab, Y. H., & Said, M. S. (2014) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · doi:10.1109/tvlsi.2014.2377192 · Cited by 66 · see citing works
Memristors for the Curious Outsiders
Carbajal, J. P., & Caravelli, F. (2018) · Technologies · doi:10.3390/technologies6040118 · Cited by 64 · see citing works
A New Memristive Neuron Map Model and Its Network’s Dynamics under Electrochemical Coupling
Ramakrishnan, B., Mehrabbeik, M., Parastesh, F., Rajagopal, K., & Jafari, S. (2022) · Electronics · doi:10.3390/electronics11010153 · Cited by 62 · see citing works
Exploiting memristance in adaptive asynchronous spiking neuromorphic nanotechnology systems
Linares-Barranco, B., & Serrano‐Gotarredona, T. (2009) · DIGITAL.CSIC (Spanish National Research Council (CSIC)) · Cited by 60 · see citing works
Stochastic hybrid 3D matrix: learning and adaptation of electrical properties
Erokhin, V. V., Berzina, T., Gorshkov, K., Camorani, P., Pucci, A., Ricci, L. B., Ruggeri, G., Sigala, R., & Schüz, A. (2012) · Journal of Materials Chemistry · doi:10.1039/c2jm35064e · Cited by 60 · see citing works
Du, N., Kiani, M., Mayr, C., You, T., Bürger, D., Skorupa, I., Schmidt, O. G., & Schmidt, H. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00227 · Cited by 58 · see citing works
Learning with memristive devices: How should we model their behavior?
Querlioz, D., Dollfus, P., Bichler, O., & Gamrat, C. (2011) · IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH) · doi:10.1109/nanoarch.2011.5941497 · Cited by 57 · see citing works
Nauman, M. M., Duraisamy, N., Rahman, K., Dang, H. W., Jo, J., & Choi, K. H. (2012) · Current Applied Physics · doi:10.1016/j.cap.2012.06.017 · Cited by 57 · see citing works
Memristor based unbalanced ternary logic gates
Khalid, M., & Singh, J. (2016) · Analog Integrated Circuits and Signal Processing · doi:10.1007/s10470-016-0733-1 · Cited by 56 · see citing works
Memristive devices for computing: Beyond CMOS and beyond von Neumann
Nguyen, H. A. D., Yu, J., Xie, L., Taouil, M., Hamdioui, S., & Fey, D. (2017) · IFIP/IEEE International Conference on Very Large Scale Integration · doi:10.1109/vlsi-soc.2017.8203479 · Cited by 53 · see citing works
Field Programmable Stateful Logic Array
Kim, K., Shin, S., & Kang, S.-M. S. (2011) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2011.2165067 · Cited by 52 · see citing works
ORGANIC MEMRISTOR DEVICES FOR LOGIC ELEMENTS WITH MEMORY
Erokhin, V. V., HOWARD, G. D., & Adamatzky, A. (2012) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127412502835 · Cited by 51 · see citing works
A memristor oscillator based on a twin-T network
Li, Z., & Zeng, Y. (2013) · Chinese Physics B · doi:10.1088/1674-1056/22/4/040502 · Cited by 51 · see citing works
Self-citationCrossbar Nanoscale HfO2-Based Electronic Synapses
Matveyev, Y., Kirtaev, R. V., Fetisova, A., Zakharchenko, S., Negrov, D. V., & Zenkevich, A. V. (2016) · Nanoscale Research Letters · doi:10.1186/s11671-016-1360-6 · Cited by 51 · see citing works
Memristive self-learning logic circuit with application to encoder and decoder
Hong, Q., Shi, Z., Sun, J., & Du, S. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-05281-z · Cited by 48 · see citing works
Resistive Computing: Memristors-Enabled Signal Multiplication
Shin, S., Kim, K., & Kang, S.-M. S. (2013) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2013.2244434 · Cited by 48 · see citing works
Applications of Multi-Terminal Memristive Devices: A Review
Sacchetto, D., Gaillardon, P., Zervas, M., Carrara, S., Micheli, G. D., & Leblebici, Y. (2013) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2013.2256258 · Cited by 47 · see citing works
Hybrid Flexible Resistive Random Access Memory‐Gated Transistor for Novel Nonvolatile Data Storage
Han, S., Zhou, Y., Chen, B., Wang, C., Zhou, L., Yan, Y., Zhuang, J., Sun, Q., Zhang, H., & Roy, V. A. L. (2015) · Small · doi:10.1002/smll.201502243 · Cited by 47 · see citing works
In-Memory Computing for Machine Learning and Deep Learning
Lepri, N., Glukhov, A., Cattaneo, L., Farronato, M., Mannocci, P., & Ielmini, D. (2023) · IEEE Journal of the Electron Devices Society · doi:10.1109/jeds.2023.3265875 · Cited by 48 · see citing works
Multiterminal Memristive Nanowire Devices for Logic and Memory Applications: A Review
Sacchetto, D., Micheli, G. D., & Leblebici, Y. (2011) · Proceedings of the IEEE · doi:10.1109/jproc.2011.2172569 · Cited by 45 · see citing works
Kim, H. J., Zheng, H., Park, J., Kim, D. H., Kang, C. J., Jang, J. T., Kim, D. H., & Yoon, T. (2017) · Nanotechnology · doi:10.1088/1361-6528/aa712c · Cited by 45 · see citing works
SIXOR: Single-Cycle In-Memristor XOR
TaheriNejad, N. (2021) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · doi:10.1109/tvlsi.2021.3062293 · Cited by 45 · see citing works
Neuromorphic behavior in percolating nanoparticle films
Fostner, S., & Brown, S. A. (2015) · Physical Review E · doi:10.1103/physreve.92.052134 · Cited by 44 · see citing works
Memristors With Flexible Electronic Applications
Gergel-Hackett, N., Tedesco, J. L., & Richter, C. A. (2011) · Proceedings of the IEEE · doi:10.1109/jproc.2011.2158284 · Cited by 43 · see citing works
Organic electronic synapses with pinched hystereses based on graphene quantum-dot nanocomposites
Choi, H. Y., Wu, C., Bok, C. H., & Kim, T. W. (2017) · NPG Asia Materials · doi:10.1038/am.2017.133 · Cited by 43 · see citing works
Memristive devices based on solution‐processed ZnO nanocrystals
Wang, J., Sun, B., Gao, F., & Greenham, N. C. (2009) · physica status solidi (a) · doi:10.1002/pssa.200925467 · Cited by 42 · see citing works
Meng, J., Wang, T., He, Z., Li, Q., Zhu, H., Li, J., Chen, L., Sun, Q., & Zhang, D. W. (2021) · Nano Research · doi:10.1007/s12274-021-3729-9 · Cited by 41 · see citing works
3D CMOS-memristor hybrid circuits
Cheng, K.-T. T., & Strukov, D. B. (2012) · International Symposium on Physical Design · doi:10.1145/2160916.2160925 · Cited by 40 · see citing works
Switching mechanisms in microscale memristors
Prodromakis, T., Michelakis, K., & Toumazou, C. (2010) · Electronics Letters · doi:10.1049/el.2010.2716 · Cited by 39 · see citing works
Compact Circuit Model and Hardware Emulation for Floating Memristor Devices
Shin, S., Zheng, L., Weickhardt, G., Cho, S.-I., & Kang, S.-M. S. (2013) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2013.2256259 · Cited by 38 · see citing works
Electric currents in networks of interconnected memristors
Oskoee, E. N., & Sahimi, M. (2011) · Physical Review E · doi:10.1103/physreve.83.031105 · Cited by 38 · see citing works
Flexible Three‐Dimensional Organic Field‐Effect Transistors Fabricated by an Imprinting Technique
Nakahara, R., Uno, M. O., Uemura, T., Takimiya, K., & Takeya, J. (2012) · Advanced Materials · doi:10.1002/adma.201201234 · Cited by 38 · see citing works
Khan, M. U., Hassan, G., Raza, M. A., Bae, J., & Kobayashi, N. P. (2019) · Journal of Materials Science Materials in Electronics · doi:10.1007/s10854-019-00753-y · Cited by 38 · see citing works
Wang, C., Ling, Z., & Wu, R. (2017) · Journal of Circuits Systems and Computers · doi:10.1142/s021812661850038x · Cited by 36 · see citing works
Instar and outstar learning with memristive nanodevices
Snider, G. S. (2010) · Nanotechnology · doi:10.1088/0957-4484/22/1/015201 · Cited by 35 · see citing works
Programmable Resistive-Switch Nanowire Transistor Logic Circuits
Shim, W., Yao, J., & Lieber, C. M. (2014) · Nano Letters · doi:10.1021/nl502654f · Cited by 35 · see citing works
Mem-fractive properties of mushrooms
Beasley, A. E., Abdelouahab, M.-S., Lozi, R., Tsompanas, M., Powell, A. L., & Adamatzky, A. (2021) · Bioinspiration & Biomimetics · doi:10.1088/1748-3190/ac2e0c · Cited by 36 · see citing works
- Authors
- Borghetti, J., Li, Z., Straznicky, J., Li, X., Ohlberg, D. A. A., Wu, W., Stewart, D. R., & Williams, R. S.
- Affiliations
- Hewlett-Packard (United States) (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2009-02-10
- Volume
- 106
- Issue
- 6
- Pages
- 1699-1703
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2631082
- OpenAlex
- W2064632620
- Cited by
- 270
- References
- 29
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 8 · 2023: 6 · 2022: 5 · 2021: 11 · 2020: 13 · 2019: 16 · 2018: 18 · 2017: 21 · 2016: 11 · 2015: 23 · 2014: 18 · 2013: 26 · 2012: 21
- FWCI
- 22.98
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency
- Advanced Research Projects Agency
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Ferroelectric and Negative Capacitance Devices
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Semiconductor Devices and Circuit Design
- Keywords
- memristor crossbar, Boolean circuits, nanoimprint lithography, nonvolatile switching
- MeSH terms
- Computers, Transistors, Electronic, Nanotechnology
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