The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
On the physical properties of memristive, memcapacitive and meminductive systems
Open accessAbstract
We discuss the physical properties of realistic memristive, memcapacitive and meminductive systems. In particular, by employing the well-known theory of response functions and microscopic derivations, we show that resistors, capacitors and inductors with memory emerge naturally in the response of systems-especially those of nanoscale dimensions-subjected to external perturbations. As a consequence, since memristances, memcapacitances and meminductances are simply response functions, they are not necessarily finite. This means that, unlike what has always been argued in some literature, diverging and non-crossing input-output curves of all these memory elements are physically possible in both quantum and classical regimes. For similar reasons, it is not surprising to find memcapacitances and meminductances that acquire negative values at certain times during dynamics, while the passivity criterion of memristive systems imposes always a non-negative value on the resistance at any given time. We finally show that ideal memristors, namely those whose state depends only on the charge that flows through them (or on the history of the voltage), are subject to very strict physical conditions and are unable to protect their memory state against the unavoidable fluctuations, and therefore are susceptible to a stochastic catastrophe. Similar considerations apply to ideal memcapacitors and meminductors.
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““memristors” understood merely as nonlinear resistors with memory have been described by Kubo theory in the 1950s14.”
From The Missing Memristor has Not been Found (2015) · cites this paper as [14]
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“Our perspective rests on the fact that memristive, memcapacitive, and meminductive devices and systems are simply generalizations of the traditional resistors, capacitors, and inductors to the case of memory response [6].”
From Comment on 'If it's pinched it's a memristor' (2019) · cites this paper as [6]
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Citations
Cites
Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008) · Nature · doi:10.1038/nature06932 · Cited by 11,828
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268 · cited 5×
“By ideal memristors we mean those whose resistance depends only on the charge that flows in the system (or on the history of the voltage) [1, 3].”
BackgroundMethodInfluentialKubo, R. (1957) · Journal of the Physical Society of Japan · doi:10.1143/jpsj.12.570 · Cited by 9,441 · cited 10×
“function [19] (whether treating the electron problem quantum-”
BackgroundMethodInfluentialIrreversibility and heat generation in the computing process
Landauer, R. (1961) · IBM Journal of Research and Development · doi:10.1147/rd.53.0183 · Cited by 4,980
Nanoionics-based resistive switching memories
Waser, R., & Aono, M. (2007) · Nature Materials · doi:10.1038/nmat2023 · Cited by 4,923 · cited 1×
“From experiments, however, we know that the switching actually occurs as soon as the applied voltage or current exceeds its threshold value [31, 32, 23].”
BackgroundHandbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences
Gardiner, C. W. (1985) · Springer series in synergetics · doi:10.1007/978-3-662-02452-2 · Cited by 3,748
Thermal Agitation of Electric Charge in Conductors
Nyquist, H. (1928) · Physical Review · doi:10.1103/physrev.32.110 · Cited by 3,264 · cited 1×
“In particular, the (intrinsic) thermal agitation of electrons inside any voltage-controlled memristor is responsible for the well-known Johnson–Nyquist noise [28, 29] (voltage fluctuations).”
BackgroundCan programming be liberated from the von Neumann style?
Backus, J. (1978) · Communications of the ACM · doi:10.1145/359576.359579 · Cited by 2,607 · cited 1×
“Non-traditional computing represents an important research direction with the aim of solving the ‘von Neumann bottleneck’ that plagues our computer architectures [11].”
BackgroundMemristive devices and systems
Chua, L. O., & Kang, S. M. (1976) · Proceedings of the IEEE · doi:10.1109/proc.1976.10092 · Cited by 2,604
‘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
Flagged first, then by citations
Research works printed but not linked: 3
- Ashcroft N W, 1976, Solid State Physics
- Gilbert T L, 1955, Phys. Rev., 100, 1243
- Bigi I I, 1999, CP Violation
Cited by
Sorted by citations
Nanoionic memristive phenomena in metal oxides: the valence change mechanism
Dittmann, R., Menzel, S., & Waser, R. M. (2021) · Advances In Physics · doi:10.1080/00018732.2022.2084006 · Cited by 208
Universal Memcomputing Machines
Traversa, F. L., & Ventra, M. D. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2391182 · Cited by 150
“The whole concept of memcomputing can be realized in practice by utilizing physical properties of many materials and systems which show a certain degree of time non-locality (memory) in their response functions at particular frequencies and strengths of the inputs [14]–[16].”
BackgroundExperimental photonic quantum memristor
Spagnolo, M., Morris, J., Piacentini, S., Antesberger, M., Massa, F., Crespi, A., Ceccarelli, F., Osellame, R., & Walther, P. J. (2022) · Nature Photonics · doi:10.1038/s41566-022-00973-5 · Cited by 141
The Missing Memristor has Not been Found
Vongehr, S., & Meng, X. (2015) · Scientific Reports · doi:10.1038/srep11657 · Cited by 131
A Novel Window Function for Memristor Model With Application in Programming Analog Circuits
Zha, J., Huang, H., & Liu, Y. (2015) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2015.2505959 · Cited by 124
“On the other hand, in [17]–[19], some significant limitations of ideal memristor models were discussed.”
Background
Metadata
- Authors
- Di Ventra, M., & Pershin, Y. V.
- Affiliations
- University of South Carolina (US)
- Venue
- Nanotechnology
- Publisher
- IOP Publishing
- Published
- 2013-05-24
- Volume
- 24
- Issue
- 25
- Pages
- 255201
- ISSN
- 0957-4484 (ISSN-L)
- 1361-6528
- OpenAlex
- W2135517727
- Semantic Scholar
- c36f81401d2c03a40a32c218b3d5f1e048af075d
- Cited by
- 130
- References
- 29
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 7 · 2023: 8 · 2022: 26 · 2021: 8 · 2020: 7 · 2019: 7 · 2018: 13 · 2017: 13 · 2016: 9 · 2015: 9 · 2014: 5 · 2013: 2
- FWCI
- 5.00
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nanotechnology (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (0802830, 1202383)
- University of California, San Diego
- Division of Materials Research
- Division of Electrical, Communications and Cyber Systems (ECCS-1202383)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Advanced Thermodynamics and Statistical Mechanics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Ferroelectric and Negative Capacitance Devices
- Keywords
- memristors, memcapacitor, meminductor, memory elements, response functions, nanosystems, input-output curves
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