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A Decade of Knowm SDC Memristor Literature, Part 1

What the research community did with Knowm's Self-Directed Channel memristor across a decade of papers.

By Tim Molter ·

More than a decade ago, before we had sold a single device, Alex Nugent and I tried to lay the whole idea out in one paper: AHaH Computing — From Metastable Switches to Attractors to Machine Learning (PLoS ONE, 2014). It runs the full stack end to end — the metastable-switch (MSS) device model, the Anti-Hebbian and Hebbian (AHaH) plasticity rules and the nodes you build from differential memristor pairs, and a set of machine-learning benchmarks (Breast Cancer, MNIST, Reuters, Census Income) run in both functional and full-circuit simulation.

We planted that seed in 2016 by selling the physical device. This series is about what grew from it: which of those ideas other groups verified independently, which they extended in directions we never took, and where the device went off and surprised us.

We have sold a physical memristor — the Self-Directed Channel (SDC) device — since 2016. I wanted to know what people have done with it, so over the last few weeks I built a corpus of every paper I could find that uses or cites the SDC device or the MSS model, and ran it through a reproducible mining pipeline. This post is the first cut of what came out.

It is meant as a resource. If you are about to work with these devices, this is the map: who went before you, what they tried, and what they measured. Everything below is generated from a single papers.json corpus filedownload it and run your own queries — so the counts and the index are reproducible and will update as the literature grows.

The seeds we planted#

Before any of the papers below existed, we put the pieces into the open so people could build on them. If you are modeling the device or doing machine learning with it, start here:

  • The visionAHaH Computing, PLoS ONE 2014: MSS model → AHaH nodes → machine-learning benchmarks, all in one paper.
  • The model, implemented — the Generalized Metastable Switch model, with worked implementations in LTspice and Xyce / Verilog-A (full write-ups on the modeling hub). The code is open source in memristor-models-4-all, and jSpice is our memristor-aware SPICE engine. We did this Xyce and LTspice work years before the wave of SPICE-modeling papers — it is the standard they are (re)building.
  • The ML and the data — the PLoS simulation source is in knowm/AHaH, and the exact benchmarks from the paper are packaged in knowm/Datasets: Breast Cancer Wisconsin, MNIST, Reuters-21578, Census Income, and more. Anyone can pull those and reproduce the numbers.
  • The hardware — the physical SDC memristor, on sale since 2016, with operating guidance (thresholds, max ratings, current-limit rule) in the SDC datasheet.
  • The platformMemristor Discovery, our open-source application for running experiments on the device with a Digilent Analog Discovery 2 — everything from raw I–V curves to a full classification demo.

Here is Alex using exactly that platform to run a simple classification experiment on real Knowm memristors:

Alex running a classification experiment on real Knowm memristors with the open-source Memristor Discovery platform. (Vimeo)

Everything after this section is what the rest of the world did once those seeds were out.

A few papers worth pulling out#

The index at the bottom is the whole haystack. Before we get there, here are a few needles — papers I keep coming back to. Each one either verifies something from that original PLoS paper or extends it somewhere we never went. I will add to this list over time; if you have a favorite I missed, tell me.

Xu et al. 2025 — Evaluation of memristor performance in neural networks using an AHaH framework. AHaH is our machine-learning architecture — a classifier built from differential memristor pairs — and this is one of the few independent groups to implement it. They build the AHaH classifier from our compositional machine-learning work and drive it with the MSS device model and parameters taken straight from our 2014 PLoS paper, then run it on the Wisconsin Breast Cancer dataset — one of the exact classification benchmarks we published in that paper, where our AHaH classifier reached an F1 score of 0.997. In other words, an outside group independently reproduced one of our headline AHaH benchmarks. This is all in simulation — the AHaH classifier runs in software against the MSS model, not against physical parts on a bench. Working in that simulated setting lets them push past what we did: they swap in several modeled device chemistries (including a silver-chalcogenide device much like the SDC) and stress the classifier with read noise, cyclic degradation, and abrupt “cliff-like” resistance jumps. Their takeaway is that the device’s dynamics, not its raw resistance, drive accuracy — gradual degradation is easy to compensate for, but sudden cliff-like drops are what wreck the network.

Gogoi & Mallajosyula 2020 — A comparative study on the forming methods of chalcogenide memristors. This one tests our tungsten SDC device by name — W bottom electrode, Ge₂Se₃ active layer, Ag top — and answers a question we get a lot: how should you form it? They try five methods (sinusoidal, linear voltage sweep, linear current sweep, constant bias, and fast pulse), and the headline lines up with what our datasheet already says — “forming voltages do not need to exceed normal operating voltages”: you do not need a separate high-voltage electroforming step. A normal low-voltage operating sweep forms the channel on its own — they call a dedicated current-sweep forming step “redundant since the subsequent voltage sweep for device operation itself acts as a forming step.” Their measured set/reset of roughly +0.25 V / −0.1 V sit right on top of our datasheet’s +0.26 V / −0.11 V, and they confirm the self-directed-channel mechanism is its own thing, not a conductive-bridge (CBRAM) cell. Two practical warnings fall out: current-sweep forming gives a gradual, poor ON/OFF result, and driving the device hard negative (around −4.3 V) can phase-change the active layer — so don’t.

Mazur et al. 2025 — Strategies to finding optimal parameters for plasticity changes in memristor-based systems. Where Xu’s study is simulation, this one is hands-on hardware. The Szaciłowski group at AGH in Kraków bought our “W” devices and went hunting for the pulse parameters that give clean synaptic behavior. They map potentiation/depression, spike-rate-dependent plasticity (SRDP), and spike-timing-dependent plasticity (STDP) directly on the device — at under a picojoule per pulse — and use it to argue, rightly, that the field needs shared testing and benchmarking protocols so results from different memristive systems can be compared. If you are planning to use a Knowm device as a synapse, this is a practical starting point for where to set your pulses — alongside the operating window, current-limit, and series-resistor guidance in our datasheet.

More to come — I am still hand-picking a few additions here.

How much is there, really?#

After deduping and screening, the corpus holds 337 papers that engage with Knowm — not a passing keyword hit. The chart below is the full decade, each paper colored by how it engages the device.

What I read off this:

  1. The volume is climbing — roughly tripled from the late 2010s to the mid 2020s, with 2024 the busiest year. 2026 is partial, so do not read the short bar as a downturn.
  2. The blue band — papers that put a real device on a bench and measured it — is the largest and steadiest. This is not a simulation-only literature.
  3. The green band is MSS-model work in SPICE and similar, often without touching hardware.

Stacked up year over year, the body of work a new researcher inherits has climbed past 300 — 327 of the 337 papers carry a publication year:

Each paper lands in one of four engagement tiers — this is the classification the pipeline assigns:

  • Measured a real device — put physical Knowm hardware on a bench and characterized it.
  • Used the MSS / Knowm model — simulated with our metastable-switch model (or the generalized version).
  • Names / uses (unclear) — clearly works with Knowm but the available text does not let us pin down device-vs-model.
  • Cites Knowm — references the device or model in passing.

I count a citation as engagement on purpose. A paper that cites Knowm is almost always using either the device or the model, and I would rather keep a borderline paper than drop a real user. The evidence ladder, high to low: a human decision, then full PDF text, then an abstract read, then a keyword match.

Where the work comes from#

The device is global. Of the 232 papers with a resolvable lead-author affiliation, here is the split by country (the other 105 — datasheets, theses, and records without a clean institution — are left out).

China leads by a wide margin, then the USA, then Chile — with a broad European cluster behind them (Spain, Poland, Bulgaria, Austria, the UK, France) and a strong showing from India. The country where the device is made is not where it is most used — most of this work happens somewhere else. The actual lab map — who measured what, and where — is the subject of Part 3.

What spread: the device and the model, not (yet) the architecture#

We have put three different things into the world, and the field picked them up at very different rates.

  1. The physical memristors — the big one. More than 120 papers (the blue band above) put a real Knowm device on the bench and measured it, and more are hiding in the “uses Knowm, details unclear” pile. If you want prior art on how the device behaves, this is where most of it is — Part 3 will be a who’s-who of the groups doing it.
  2. The MSS model. Around three dozen papers (the green band) use our Metastable Switch model, or its generalized version, as their simulation basis. The strongest signal here is not the count but that other groups extend the model rather than replace it: Laguna-Sanchez adds α-stable switching thresholds, El-Geresy builds an event-based version. That is what adoption looks like.
  3. The architecture — kT-RAM, kT-bits, AHaH nodes. This one has barely traveled. Exactly five papers in the whole corpus engage the architecture itself, and two of those are ours (Molter 2016, Nugent 2017). That leaves three independent ones: Abbood 2021, and the recent Xu 2025 and Xie 2026. The device and the model are everywhere; the computing architecture we have been building around them is still almost entirely ours to carry.

Practically, that tells you where the well-worn paths are. If you want to measure or simulate an SDC device, you are joining a crowd with shared tools and a decade of prior art. If you want to build AHaH machines out of kT-bits, there is very little to lean on yet — a warning or an opportunity, depending on your temperament.

The heavy hitters#

If you only read a dozen papers, the citation counts pick a reasonable dozen. Here are the most-cited works in the corpus.

Three papers sit at the top, nearly tied: Campbell’s high-temperature device paper — the device itself, described by the person who fabricates it — just ahead of Minati’s physical-memristor chaos circuit and Berdan’s synaptic-dynamics paper, an early, influential use of it as a synapse. Our generalized MSS model paper is fourth. After that the list spreads across chaos circuits, in-memory logic, neuromorphic and machine-learning work, and device physics — a good sign the device found a lot of different niches.

Essential reading#

Citation count is a popularity contest, not a syllabus. Here is a curated short list instead — the papers I would hand a new researcher, grouped by what each one is good for. I treat Knowm’s own sources as the baseline the rest is measured against: the device from Campbell, the model from Molter, the architecture from Nugent.

ThemePaperCitesWhy read it
Primary / deviceSelf-directed channel memristor for high temperature operation (Campbell 2016)143The device, by its fabricator — the founding characterization.
Primary / modelThe generalized metastable switch memristor model (Molter 2016)74Knowm’s GMS device model — the simulation baseline others adopt.
Primary / paradigmThermodynamic-RAM technology stack (Nugent 2017)24kT-RAM / AHaH computing, Knowm’s architecture vision.
Most-cited / synapseEmulating short-term synaptic dynamics with memristive devices (Berdan 2016)139Early high-impact neuromorphic use (139 cites).
Most-cited / MLMemristive GAN in analog (Krestinskaya 2020)57Generative model on memristor hardware (57).
LogicSIXOR: Single-cycle in-memristor XOR (TaheriNejad 2021)42Single-cycle in-memristor XOR — stateful logic anchor.
ChaosA dream that has come true: Chaos from a nonlinear circuit with a real memristor (Volos 2020)44First experimental chaos from a real-memristor circuit.
Device physicsComparison of the electrical response of Cu and Ag ion-conducting SDC memristors over the temperature range 6 K to 300 K (Drake 2019)15Cu vs Ag, 6 K–300 K — chemistry & cryogenic behavior.
Device physicsStructural and parametric identification of knowm memristors (Ostrovskii 2021)55Parameter identification of the real device (55).
Device physicsComprehensive Study of SDC Memristors for Resistive RAM Applications (Garda 2024)8Broad measurement study across variants.
Device physicsState characterisation of self-directed channel memristive devices (Hajtó 2025)0Recent state-characterization of the device.
ModelingMeasurement and Modeling of SDC Memristors: Extensive Study (Bednarz 2024)0Head-to-head model fits across four chemistries.
VariabilityCharacterization and modeling of variability in commercial self-directed channel memristors (Jiménez-Gallo 2023)2Variability characterization & memdiode model.
MultilevelExploring memristor multi-level tuning dependencies on the applied pulse properties via a low cost instrumentation setup (Gomez 2019)34Analog/multilevel pulse programming (34).
AHaH uptakeEvaluation of memristor performance in neural networks using an AHaH framework (Xu 2025)0Independent AHaH-framework adoption.

The full index#

Below is the complete corpus — every relevant paper, newest first, with how it engages Knowm and its citation count. This is the thing I most wanted when I started: one list, in one place. It is generated from papers.json, so it grows as the literature does.

Full index — all 337 relevant papers (click to expand)
YearFirst authorTitleEngagesCites
2026BhardwajExperimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learningdevice0
2026ChenResearch on memristor-based logic circuitsmodel0
2026El-GeresyDelay conditioned generative modelling of resistive drift in memristorscites0
2026FengA coupled backward stochastic differential equation (BSDE) framework for metastable transition precursors in a stochastically forced Duffing oscillatorcites0
2026FiaccoImplementation of neural networks on FPGAs with memristors for optimizing data processing in ATLAS()device0
2026FrankIntegrating physical unclonable functions from novel nanomaterials, circuit elements, and memory technologies into future hardware architecturesdevice0
2026GoAn energy-and endurance-aware hybrid CMOS–SDC memristor convolutional spiking neural network for edge intelligenceuses1
2026GuoA bio-inspired neuromorphic system for fusing visual features and autonomous learningcites0
2026JeniferEmerging SDC Memristor Architectures for AI Hardware: Multibit Storage Capabilities, Thermal Effects, and Dynamic Simulation Analysisuses0
2026JurjA Physics-Regularized Neural Surrogate Framework for Printed Memristorscites0
2026KhanEnergy-Efficient Epileptic Seizure Prediction Using RRAM-Based In-Memory Computingcites0
2026LiVaristructure resistive switching memory devices through dynamical redox of oxidescites0
2026MladenovMemristor Models with Parasitic Parameters for Analysis of Passive Memory Arraysdevice0
2026PhamNon-pinched hysteresis in CrOx/TiOy-based memristive devices: Modeling and analysiscites0
2026PoreddyAnalyzing analog, digital, asymmetric, and butterfly-like hysteresis characteristics using generalized memristor modelcites0
2026StoyanAnalysis of Memristor-Based Neural Networks and Logic Circuits for Artificial Intelligence Using Standard and Improved Memristor Modelsuses0
2026TaherInfluence of the Ge–Chalcogenide Active Layer on Electrical Conduction in Self-Directed Channel Memristorsuses0
2026TariqMemristive Conductance Programming and Dot Products for Inference in Machine Learninguses0
2026VourkasHow to ‘Tame’ a memristor: advanced control unit for reliable ReRAM operation leveraging prognostics and health management approachesdevice0
2026WangRobust Sb2Se3 memristors via pressure-modulated growth for noise-resilient neuromorphic computingdevice0
2026WangDesign of Memristor‐Based Balanced Ternary Full Adderdevice0
2026XieA Memristor-Based SNN Hardware Architecture with AHaH Plasticityuses0
2026ZhaoHigh-temperature memristors enabled by interfacial engineeringcites1
2025AthinaAdvancing AI Hardware with SDC Memristors: A Review of Multibit Storage, Thermal Resilience, and Dynamic Simulation Strategiesuses0
2025BaranMemristive Wilson–Cowan Neuron Models: Innovative Conceptual Framework and Programmable Analog and Digital Implementationscites1
2025BarrowsUncontrolled learning: Codesign of neuromorphic hardware topology for neuromorphic algorithmsdevice5
2025BEDNARZTESTING THE SDC MEMRISTORS IN THREE PHASE SYSTEMSdevice0
2025BednarzMemristor-based adaptive leaky integrate-and-fire neuron model: a simulation studymodel0
2025ChenMagnetic-field controlled organic spintronic memristor for neural network computationcites2
2025DisfaniHigh-Speed and Low-Cost In-Array Memristive Multipliers using SIXOR and TMSL Logicscites1
2025El-GeresyEvent-based simulation of stochastic memristive devices for neuromorphic computingmodel2
2025El–GeresyEnergy-Information Trade-Off in Self-Directed Channel Memristorsdevice0
2025GardaTesting the SDC memristors in three phase systemsuses0
2025GulafshanRealistic behavioral model for ReRAMs capturing non-idealitiesdevice4
2025GuoMultisensory Memristive Circuits With Parallel Processing and Dual Adaptive Featurescites4
2025HajtóState characterisation of self-directed channel memristive devicesdevice0
2025HuangDesign and Application of Memristor-CMOS Ternary Comparatordevice0
2025IsahWhat are Memelements: Memristor, Memcapacitor and Meminductor?device1
2025KalanakiMajority voting for low power and low complexity preamble detection by hybrid memristor-CMOS architecturecites0
2025KirilovMemristor-Based Logical Gates and Schemes for Artificial Intelligencedevice1
2025KirilovLTSPICE Memristor Neuron with a Modified Transfer Function Based on Memristor Model with Parasitic Parametersdevice1
2025KirilovOctave Memristor Models’ Library and Application for Analysis of Memristors and Memristor-Based Circuitscites0
2025KrestinskayaMemristors: Properties, Modelsmodel0
2025KumarNew ternary decoders using hybrid memristor-MOS logicmodel1
2025KumarMBTC: Memristor-MOS-Based Binary to Ternary Converter for Image Processing Applicationcites0
2025Lopez-JimenezExperimental Evaluation of Memristor-Enhanced Analog Oscillators: Relaxation and Wien-Bridge Casesdevice6
2025MazurStrategies to Finding Optimal Parameters for Plasticity Changes in Memristor-Based Systems for Neuromorphic Data Computingdevice2
2025MirandaFrom simulation to reality: experimental analysis of a quantum entanglement simulation with slime molds (Physarum polycephalum) as bioelectronic componentsdevice0
2025MladenovImproved memristor model with parasitic parametersuses1
2025PanTransmission Delay Analysis Based on Memristor Gate Circuitsuses0
2025RabieeReliable leakage-enabled memristor model for large-scale circuitscites0
2025SafaOpenMENA: An Open-Source Memristor Interfacing and Compute Board for Neuromorphic Edge-AI Applicationsdevice1
2025SalmanAnalysis of a novel fractional-order chaotic circuit with a feedback memristor: design, dynamics, and applicationcites0
2025SchmidtFrom simulation to reality: experimental analysis of a quantum entanglement simulation with slime molds (Physarum polycephalum) as bioelectronic componentsdevice0
2025SeilerAn efficient robust serial imply-based in-memristor adderdevice0
2025SeilerAn improved serial imply adder algorithm for efficient neural network applicationsdevice3
2025TaherInvestigation in the influence of the device material layers on the electrical performance of the self-directed channel (SDC) memristoruses1
2025VourkasA beginner’s guide to developing behavioral models of memristive devices capturing nonideal and dynamic switching response in SPICEdevice1
2025VourkasSystem interfaces for accurate READing from memristive devices in multi-level ReRAM and neuromorphic computing applicationsdevice2
2025WangHigh-Order Associative Learning Based on Memristive Circuits for Efficient Learningdevice0
2025WuA 20-kHz Memristor-based Pulse Width Modulation for Power Convertersdevice0
2025XuEvaluation of memristor performance in neural networks using an AHaH frameworkmodel0
2025ZhouDesign Of Three-Valued Logic Gates Based on Knowm Memristorsuses0
2024AfrinAnalysis of Learning Mechanisms in Spiking Neural Networks with R (t) Elements and Memristive Synapsesmodel0
2024AleshinMechanisms of the Formation of Conductive Channels in Bipolar Memristors of Various Designscites1
2024BednarzMeasurement and modeling of self-directed channel (SDC) memristors: An extensive studyuses4
2024BednarzMeasurement and Modeling of SDC Memristors: Extensive Studyuses0
2024BednarzMeasurement and Modeling of SDC Memristors: Extensive Studyuses0
2024BiolekIncremental mutators for transforming between extended higher-order elementsuses3
2024BiswasExploring neuromorphic potentials of silver-based self-directed-channel memristors for artificial synapses in neural network circuitsuses1
2024Biswas… Biologically-inspired AI Hardware Accelerators: Unveiling the Potential of Metal Self-Directed Channel (M-SDC) Memristors in Neuromorphic Computinguses0
2024DuttCharacterization and Modeling of Long-Term Device Performance in Resistive Random Access Memoriesdevice0
2024GandolfiInformation transfer in neuronal circuits: From biological neurons to neuromorphic electronicsdevice6
2024GardaComprehensive Study of SDC Memristors for Resistive RAM Applicationsdevice8
2024GuoNeuromorphic circuit of classical and operant conditioning based on tunable neural circuitry motifscites20
2024GuptaMemristors based Computation and Synthesisdevice0
2024HeSpatiotemporal chaos in a sine map lattice with discrete memristor couplinguses31
2024HuoCoexistence of cyclic sequential pattern recognition and associative memory in neural networks by attractor mechanismscites6
2024IsahThe significance of a window function in the modeling of HP TiO2 memristor: Pros and Consdevice1
2024JurjPySpice-Simulated In Situ Learning with Memristor Emulation for Single-Layer Spiking Neural Networkscites2
2024KabirEffects of Group IVA Elements on the Electrical Response of a Ge2Se3-Based Optically Gated Transistoruses2
2024KarakulakSawtooth Signal Generator Using a Carbon-Based Memristordevice2
2024KirilovA simple memristor model for memory devicescites5
2024LiuBrain‐Like Biomimetic Circuit Design Based on Memristorcites1
2024MeliviluConditional and Multi-Level WRITE Operations on Current-Controlled Memristive Devices for Neuromorphic Applicationsuses1
2024MladenovA memristor neural network based on simple logarithmic-sigmoidal transfer function with MOS transistorsmodel4
2024NachawatyVoltage‐Driven Fluorine Motion for Novel Organic Spintronic Memristorcites13
2024PandaHybrid CMOS Memristor Based Frequency Divider Using D Flip Flopuses1
2024PandaHybrid CMOS Memristor-Based Data Compressor Using Shannon Fano Encoderuses2
2024ParlarA new operational amplifier model using a memristor emulator circuit and application to a phase-shifted oscillator circuit Memristör taklit devresi kullanılarak yeni bir …cites4
2024PizarroDesign and Simulation of a Hyperdimensional Computing System with Memristive Associative Memory for Image Classification.cites1
2024QiuIMPLY-based approximate full adders for efficient arithmetic operations in image processing and machine learningdevice1
2024RamirezAn Advanced Memory WRITE Algorithm to Mitigate the Effects of ReRAM Cell Variabilityuses2
2024RashidiDesign and physical implementation of memristive logic and computation unitsdevice0
2024SoutoNeuromorphic circuit simulation with memristors: Design and evaluation using memtorch for mnist and cifardevice8
2024SunGuest Editorial: Memristive electronic circuits, neural networks and neuromorphic computingcites0
2024WangUltrafast vision perception by neuromorphic optical flowcites0
2024WangDesign of chaotic circuit based on Knowm memristorcites6
2024WangPreassigned-Time Stabilization of Memristive Chaotic Circuit via Switching Controlcites0
2024WangCrossbar array based on tri-valued memristors: its design and application.cites8
2024WangDesign method for unbalanced ternary logic family based on binary memristorscites7
2024WangMemristor-based adaptive neuromorphic perception in unstructured environmentscites59
2024WangA balanced CMOS compatible ternary memristor-NMOS logic family and its applicationcites17
2024WangElementary cellular automata realized by stateful three-memristor logic operationscites2
2024WangSelf-reconfigurable multifunctional memristive nociceptor for intelligent roboticscites2
2024WUSeveral trigger circuit designs based on memristorsdevice0
2024ZhangTwin-T Network Oscillator Based on Knowm Memristorsuses1
2024ÇakırA memristor-based Liénard Oscillator designdevice3
2024ÇakırMemristör tabanlı bir Liénard Osilatörü tasarımıdevice4
2023AldanaUnravelling the data retention mechanisms under thermal stress on 2D memristorscites17
2023AleshinEstimation of the activation energy in the Ag/SnSe/Ge2Se3/W self-directed channel memristordevice1
2023AleshinActivation processes during operation of an Ag/SnSe/Ge2Se3/W ion memristor with a self− directed current− conducting channeldevice0
2023AlshayaExperimental results of 1C1R structure based on Knowm memristoruses2
2023BenattiBiologically plausible information propagation in a CMOS integrate-and-fire artificial neuron circuit with memristive synapsesdevice8
2023BenattiUltra-low power logic in memory with commercial grade memristors and FPGA-based smart-IMPLY architecturedevice1
2023BenattiBiologically plausible information propagation in a complementary metal-oxide semiconductor integrate-and-fire artificial neuron circuit with memristive synapsesdevice8
2023BenattiCMOS leaky integrate-and-fire neuron circuit with memristorbased synapses reveals biologically plausible information transmissionmodel0
2023CayoA comprehensive simulation framework to validate progressive read-monitored write schemes for ReRAMcites8
2023CayoOn the Development of Prognostics and System Health Management (PHM) Techniques for ReRAM Applicationsdevice3
2023CireraEffective current-driven memory operations for low-power reram applicationsdevice10
2023CireraUsing Current to Drive Two SDC Memristors Connected in Series and in Anti-Seriesdevice0
2023CireraCurrent Driven Random Exploration of Resistive Switching Devices, an Opportunity to Improve Bit Error Ratiodevice2
2023CorrerExploring amorphous Ge-As-Se-Te as an active layer candidate in memristive devicescites0
2023CuiAn RRAM-based PUF with adjustable programmable voltage and multi-mode operationdevice1
2023DalmışExistence of Capacitive Effects in a Tungsten-based SDC Memristive Systemdevice2
2023ErcanExamination of the Reliability of a Robustness Test for the Self-Directed Channel Carbon-Based Memristors by Reading Their DC Resistancedevice0
2023FaqiangA chaotic circuit based on Knowm memristor: modeling, analysis, and experimental verification.uses1
2023FernandezDesign Exploration of Threshold Logic in Memory and Experimental Implementation Using Knowm Memristors.uses10
2023GuoImplementing bionic associate memory based on spiking signalcites19
2023HongA Field-Programmable Metamaterial Using Memristor as a Stable Switcherdevice0
2023Jiménez-GalloCharacterization and modeling of variability in commercial self-directed channel memristorsuses2
2023KhanHigh Speed Readout Techniques for High Density Non-Volatile Memristor Crossbar Memory with Suppressed Sneak-Path Currentcites0
2023Laguna-SanchezThe probabilistic behavior of the set and reset thresholds in Knowm’s SDC memristors: Characterization and Simulationdevice2
2023LiTernary combinational logic gate design based on tri-valued memristorscites1
2023LinTestability design of memristive digital circuits based on Knowm memristoruses3
2023LiuCompact Model Library in Simscape for Various Memristorsuses0
2023LiuRecent advances in halide perovskite memristors: From materials to applicationscites13
2023LázaroDesign and simulation of memristor-based neural networksdevice4
2023LázaroDesign and simulation of memristor-based neural networksdevice0
2023MaA fast homeostatic inhibitory plasticity rule circuit with a memristive synapseuses3
2023MladenovMemristor-based neural network implementation with adjustable synaptic weights in LTSPICEcites7
2023MladenovApplication of metal oxide memristor models in logic gatescites9
2023MoroMemristive analog computing and innovative sensors for neuromorphic systemscites0
2023NairMemristive pixel-CNN loop generate for CNN generalisationsuses15
2023NavazMemristive Crossbar for Hyper Dimensional Consumer Text Analytics Acceleratorcites0
2023OmarA brief introduction to memristor deviceuses5
2023OstrovskiiDesign of a memristor-based neuron for spiking neural networksdevice1
2023RadhakrishnanConsumer document analytical accelerator hardwarecites3
2023RiquelmeRevI-Ve: A comprehensive software interface for easy ReRAM device characterizationuses3
2023VentraRestoring Sanity: The Memristor Testdevice0
2023WangTernary Combinational Logic Gates Design Based on Tri-Valued Memristorsmodel1
2023WangA balanced Memristor-CMOS ternary logic family and its applicationmodel1
2023АлёшинАктивационные процессы при работе ионного мемристора Ag/SnSe/Ge2Se3/W с самоформирующимся токопроводящим каналомdevice0
2022AleshinTemperature-frequency study of germanium selenide memristors with a self-directed current-conducting channeluses3
2022AleshinFeatures of the Formation of Conductive Channels in Memristors Based on Solid Electrolytesuses1
2022CireraStochastic resonance exploration in current-driven reram devicesdevice7
2022CireraExploring different circuit-level approaches to the forming of resistive random access memoriesdevice7
2022DiasMemristor-based neuromodulation device for real-time monitoring and adaptive control of neuronal populationsdevice38
2022FernandezReliability-aware ratioed logic operations for energy-efficient computational ReRAMcites5
2022FernandezDesign and simulation of peripheral driving circuitry for computational ReRAMcites5
2022FloriniA hybrid CMOS-memristor spiking neural network supporting multiple learning rulesdevice23
2022FrankUsing memristor arrays as physical unclonable functionsdevice6
2022Gallo-BourdeauTraining of artificial neural networkscites12
2022GaoBPSK circuit based on SDC memristordevice5
2022GetachewThe Memristor and its Implementation in Deep Neural Network Designing: A Reviewcites0
2022HasanMathematical simulation of memristive for classification in machine learninguses0
2022HosseiniCombined CMOS-Memristor-Based Phase Frequency Detectoruses0
2022IsahReview on the basic circuit elements and memristor interpretation: Analysis, technology and applicationsdevice48
2022IsahMemristor− the fourth fundamental passive electronic component and its memory interpretationdevice0
2022KhanAll-Printed Flexible Memristor with Metal–Non-Metal-Doped TiO2 Nanoparticle Thin Filmscites36
2022KimApplication of the Test for Memristor to Experimental Memory Devicesdevice0
2022LaskaridisStudy of a chaotic circuit with a physical memristor as a nonlinear resistordevice6
2022LaskaridisAntimonotonicity, hysteresis and coexisting attractors in a shinriki circuit with a physical memristor as a nonlinear resistordevice8
2022LiA fully configurable PUF using dynamic variations of resistive crossbar arraysdevice14
2022LyapunovStudy of resistive switching in GeSx/Ag system for neuromorphic computing applicationscites0
2022MarcoOscillatory circuits with a real non-volatile Stanford memristor modelmodel16
2022MemristorsAvailable online: https://knowm. org/downloadsuses8
2022NtinasHarnessing memristor circuits and device variability in emergent computing applicationsdevice0
2022OnyejegbuA variable bandwidth memristor‐based Legendre Optimum low pass filter for radio frequency applicationsuses4
2022PrzyczynaKNOWM memristors in a bridge synapse delay-based reservoir computing system for detection of epileptic seizuresdevice9
2022SantosOptimization of memristor based ultrasonic transducers for mesoscopic characterization of biomaterialsuses4
2022SantosMemristor based ultrasonic optimized excitations for mesoscopic nonlinear characterization of biomedical tissuesuses1
2022WangFPGA synthesis of ternary memristor-CMOS decodersmodel14
2022WangFloating memcapacitor based on knowm memristor and its dynamic behaviorsmodel10
2022WangLow-variance memristor-based multi-level ternary combinational logicmodel32
2022WangFPGA synthesis of ternary memristor-CMOS decoders for active matrix microdisplaysmodel14
2022ZhouGradient-based neuromorphic learning on dynamical RRAM arraysmodel32
2022ZhouA fully memristive spiking neural network with unsupervised learningmodel9
2022ZhouMemristive Spiking Neural Network for Neuromorphic Computingcites0
2021AbboodThe Effects of Conductance on Metastable Switches in Memristive Devices Based on Anti-Hebbian and Hebbian (AHaH) Learning Rulesmodel1
2021BaiSpatial-temporal hybrid neural network with computing-in-memory architecturecites21
2021BaumgartenUniversal computation using localized limit-cycle attractors in neural networkscites0
2021BunnamMemristor-based design solutions for mitigating parametric variations in IoT applicationsdevice2
2021CantleyImpact of radiation on pattern recognition in memristor-based neuromorphic circuitscites2
2021CayoDesign Steps towards a MCU-based Instrumentation System for Memristor-based Crossbar Arraysuses7
2021ChenA mixed-kernel, variable-dimension memristive CNN for electronic nose recognitioncites36
2021GardaModeling of Memristors under Periodic Signals of Different Parameters. Energies 2021, 14, 7264device9
2021GardaModeling of memristors under periodic signals of different parametersdevice9
2021GogoiEnhancing the Switching Performance of CH3NH3PbI3 Memristors by the Control of Size and Characterization Parameterscites23
2021IsahPolarity reversal effect of a memristor from the circuit point of view and insights into the memristor fusecites6
2021IsahMemristors in Nonlinear Network: Application to Information (Signal and Image) Processingcites0
2021LaubeDevice variability analysis for memristive material implicationdevice5
2021LiDynamically configurable physical unclonable function based on RRAM crossbardevice5
2021MalikA stochastic compact model describing memristor plasticity and volatilitycites8
2021ManuComparative analysis of memristor devices as neuron.device1
2021MarkovicMemristors as Candidates for Replacing Digital Potentiometers in Electric Circuits. Electronics 2021, 10, 181uses8
2021MarkovićMemristors as candidates for replacing digital potentiometers in electric circuitsuses8
2021MiguelMemristor: funcionamiento y aplicacionescites0
2021MinatiChaotic circuit based on physical memristoruses0
2021OstrovskiiStructural and parametric identification of knowm memristorsdevice55
2021RadakovitsBehavioral leakage and inter-cycle variability emulator model for rerams (BELIEVER)device10
2021SharifHybrid memristor-CMOS implementation of logic gates design using LTSpicemodel3
2021SharifHybrid memristor-CMOS implementation of logic gates design using LTSpice.model3
2021ShenHistory erase effect of real memristorsuses4
2021ShenHistory Erase Effect of Real Memristors. Electronics 2021, 10, 303uses4
2021SinghMEMRISTOR BASED ROIC FOR INFRARED SPECTRUM FOREST FIRE DETECTIONmodel0
2021StollerDemonstration of three true random number generator circuits using memristor created entropy and commercial off-the-shelf componentsdevice15
2021TaheriNejadSIXOR: Single-cycle in-memristor XORdevice42
2021WeyOn Memristor Modeling for a VGA Applicationuses0
2021ZhaoGradient decomposition methods for training neural networks with non-ideal synaptic devicescites9
2021ZhaoGradient Decomposition Methods for Training Neural Networks with Non-Ideal Weightscites9
2020AhmedDesign of Memristor Device Based Voltagedevice0
2020BaiDetection through deep neural networks: a reservoir computing approach for mimo-ofdm symbol detectioncites4
2020BosuMemristorToolbox: Open source framework to control memristors in Unity for ternary applicationsuses2
2020BunnamEmpirical temperature model of self-directed channel memristoruses9
2020DowlingProbabilistic memristive networks: Application of a master equation to networks of binary ReRAM cellscites20
2020FernandezComprehensive predictive modeling of resistive switching devices using a bias-dependent window function approachmodel16
2020FernandezShortest path computing in directed graphs with weighted edges mapped on random networks of memristorsmodel3
2020FernandezPerformance Assessment of Memristor Networks as Shortest Path Problem Solverscites1
2020FernandezReRAM-based ratioed combinational circuit design: a solution for in-memory computingcites7
2020FernandezA voltage-driven window function concept for behavioral memristor device modelingcites4
2020FosterAn FPGA based system for interfacing with crossbar arraysdevice8
2020GogoiA comparative study on the forming methods of chalcogenide memristors to optimize the resistive switching performancedevice12
2020IsahMemristor dynamics involved in cells communication for a 2D non‐linear networkcites11
2020KetronMonte Carlo Simulations on Resistive Switching Memristor Modelingcites0
2020KimAn experimental proof that resistance‐switching memory cells are not memristorsdevice38
2020KrestinskayaMemristive GAN in analogmodel57
2020LiuConjugated polymers for information storage and neuromorphic computingcites25
2020LópezReliability-aware circuit design to mitigate impact of device defects and variability in emerging memristor-based applicationscites0
2020MinatiA chaotic circuit based on a physical memristordevice140
2020NilsenMemristor Implementation of a Ternary Storage Circuitcites1
2020NugentKnowm Memristor Discovery Manualuses3
2020ReutherSurvey of machine learning acceleratorscites153
2020SilvaHybrid CMOS/Memristor Circuits Emulatordevice0
2020StollerNovel Memristor Based True Random Number Generatoruses0
2020VolosA dream that has come true: Chaos from a nonlinear circuit with a real memristordevice44
2020VolosThe first experimental evidence of chaos from a nonlinear circuit with a real memristordevice10
2020WangHigh-density memristor-CMOS ternary logic familymodel2
2019CampbellThe self-directed channel memristor: operational dependence on the metal-chalcogenide layeruses11
2019CorreiaDesenho lógico com Memristorsmodel0
2019DrakeComparison of the electrical response of Cu and Ag ion-conducting SDC memristors over the temperature range 6 K to 300 Kdevice15
2019EscuderoMemristive logic in crossbar memory arrays: Variability-aware design for higher reliabilitycites29
2019EshraghianAnalog weights in ReRAM DNN acceleratorsmodel36
2019EshraghianRetinal and Neural Dynamics using Memristor-CMOS Architecturesdevice0
2019GhediraCoexistence of bipolar and unipolar memristor switching behaviorcites6
2019GhediraCoexistence of Bipolar and Unipolar Memristor Switchingcites6
2019GomezVoltage divider for self-limited analog state programing of memristorsdevice30
2019GomezExploring memristor multi-level tuning dependencies on the applied pulse properties via a low cost instrumentation setupdevice34
2019GomezExploring the “resistance change per energy unit” as universal performance parameter for resistive switching devicesuses10
2019GrotheMemristors for programmable circuits controlled by embedded systemscites3
2019Ibrahim2019 36th National Radio Science Conference (NRSC)device4
2019IncKnowm Self Directed Channel Memristors Data Sheetuses4
2019JafriCurrent assisted memory effect in superconductor–ferromagnet bilayers: A potential candidate for memristorscites5
2019KrestinskayaMemristors: properties, models, materialscites13
2019Lei-JieDesign and analysis of new meminductor model based on Knowm memristoruses6
2019LuInvestigation of the Conduction Mechanisms in the Ag-and Cu-Based Self-Directed Channel (SDC) Memristoruses0
2019MajzoubOn the mechanism of creating pinched hysteresis loops using a commercial memristor devicedevice26
2019MarkovićJedno rješenje automatizacije programiranja KnowM memristoracites1
2019NigusBinary-Weighted Synaptic Circuit for Neuromorphic Learning System Using Stochastic Memristor SPICE Modeldevice0
2019NigusStochastic and novel generic scalable window function-based deterministic memristor SPICE model comparison and implementation for synaptic circuit designdevice6
2019NtinasExperimental investigation of memristance enhancementuses6
2019RadakovitsImplementation and characterization of a memristive memory systemdevice13
2019SelmyHardware implementation of a low power memristor-based voltage controlled oscillatordevice3
2019TaheriNejadFrom behavioral design of memristive circuits and systems to physical implementationscites27
2019TaheriNejadA semi-serial topology for compact and fast IMPLY-based memristive full adderscites27
2019VourkasModeling Memristor–Based Circuit Networks on Crossbar Architecturescites3
2019YamamotoMemristor Engineering: Modeling, Fabrication, and Characterizationdevice0
2019王发强基于 Knowm 忆阻器的新型忆感器模型的设计与分析model2
2018AzambujaAction Learning Experiments Using Spiking Neural Networks and Humanoid Robotscites0
2018CampbellAn Optically Gated Transistor Composed of Amorphous M + Ge2Se3 (M = Cu or Sn) for Accessing and Continuously Programming a Memristordevice12
2018CaravelliMemristors for the curious outsiderscites64
2018ChenOXYGEN AND SILVER-OXYGEN DEFECTS IN Ge2Se3 ELECTROCHEMICAL METALLIZATION BRIDGE MEMRISTORSuses0
2018DahlModeling memristor radiation interaction events and the effect on neuromorphic learning circuitscites10
2018EscuderoVariability-tolerant memristor-based ratioed logic in crossbar arraycites8
2018FeySimulating memristive networks in systemc-amsmodel2
2018GardaThe memristor switching behavior from the energy point of viewdevice2
2018GardaModeling sinusoidally driven self-directed channel memristorsdevice6
2018GardaModeling of Memristors Under Sinusoidal Excitations with Various Frequenciesdevice6
2018IrmanovaImpact of integrated circuit packaging on synaptic dynamics of memristive devicescites1
2018KhrapkoInvestigation of the memristor nonlinear propertiesdevice3
2018KhrapkoBADANIE NIELINIOWYCH WŁAŚCIWOŚCI MEMRYSTORAdevice0
2018MolterThermodynamisches Rechnen: Neuromorphe Computerarchitekturen Teil 2model1
2018NugentMemristors: Where fantasy meets fact (Conference Presentation)uses0
2018NugentSelf Directed Channel Memristorsuses6
2018SuarezEvaluation of the computational capabilities of a memristive random network (MN3) under the context of reservoir computingcites14
2018SungPerspective: A review on memristive hardware for neuromorphic computationcites216
2018VourkasSpecial issue on ‘Advances in Memristive Networks’model0
2017Ballbe… approach to Memristive Devices and its applications on Stateful Logic: Design and experimental evaluation of the IMPLY logic gate with Knowm memristorsdevice0
2017Ballbe… to Memristive Devices and its applications on Stateful Logic: Design and experimental evaluation of the IMPLY logic gate with Knowm memristorsdevice0
2017BaumannMemristor‐enhanced humanoid robot control system–Part II: Circuit theoretic model and performance analysismodel23
2017EdblomExploration of big data and machine learning in retailcites0
2017LebdehAn efficient heterogeneous memristive xnor for in-memory computingcites41
2017LebdehMemristive Stateful Logic Gates for In-Memory Computing Applicationscites0
2017LloydUsing LT-Spice Circuit Modeling to Investigate the Effects of Changing the Metal-Selenide Layer in the Self-Directed Channel Memristoruses0
2017LluciàDesign of a multi-level memory cell with new emerging non-volatile memristive technologydevice0
2017MarkovićMain-line memristor mounted type loaded-line phase shifter realizationcites14
2017MbarekCharacterization, and modeling of memristor devicescites5
2017NugentFrom memristors to compositional machine learning: Exploring neuromemristive algorithmic abstractions with the knowm apidevice0
2017NugentThermodynamic-RAM technology stackdevice24
2017RzigaThe basic I–V characteristics of memristor model: simulation and analysiscites27
2016AzambujaDiverse, noisy and parallel: a new spiking neural network approach for humanoid robot controlcites11
2016BerdanEmulating short-term synaptic dynamics with memristive devicesmodel139
2016BoynFerroelectric tunnel junctions: memristors for neuromorphic computingcites0
2016CampbellSelf-directed channel memristor for high temperature operationdevice143
2016CampbellPulse shape and timing dependence on the spike-timing dependent plasticity response of ion-conducting memristors as synapsesuses35
2016CastilloMore than Moore. Experience on material implication computing with an electromechanical memristor emulatorcites1
2016Escudero-LópezAn experience with chalcogenide memristors, and implications on memory and computer applicationsdevice2
2016FeyEvaluating ternary adders using a hybrid memristor/CMOS approachmodel4
2016KorczynskiMemristor variants and models from Knowmuses0
2016LeckliderDid the memristor breakthroug (finally) occur?device0
2016MolterThe generalized metastable switch memristor modelmodel74
2016MolterMachine Learning with Memristors via Thermodynamic RAMmodel2
2016NugentMemristive neural processor utilizing anti-hebbian and hebbian technologyuses70
2016SantosA memristor based ultrasonic transducer: The memosduceruses16
2016WangA New Simple Chaotic Circuit Based on Memristorcites80
2016WuA new simple chaotic circuit based on memristorcites80
2016ZuinExperience on material implication computing with an electromechanical memristor emulatorcites1
2015CampbellReconfigurable Electronics and Non-Volatile Memory Researchdevice0
2014NugentCortical Processing with Thermodynamic-RAMuses3
2014NugentAHaH computing with thermodynamic RAM: bridging the technology stackuses0
AnagnostopoulosUsing Memristor Arrays as Physical Unclonable Functionsdevice0
ChuaDefinición y crítica del memristorcites0
FernándezMemristor-based Neuromorphic Computingdevice0
GardaAbstract submission template for MEMRISYS 2017 The memristor switching behavior from the energetic point of viewdevice0
IIIMemristors in Neural Networksdevice0
LázaroDiseño y simulación de redes neuronales basadas en memristores Design and simulation of memristor-based neural networks.device0
ΝτίναςΑξιοποίηση μεταβλητότητας διατάξεων memristor και κυκλωμάτων memristor για εφαρμογές αναδυόμενου υπολογισμούdevice0

Next in the series: what people built with these devices — neuromorphic synapses, in-memory logic, chaos circuits, hardware security, and a few strange applications.