Organic memristive devices
Organic memristive devices
Research foundation
Research foundation
NeuroCompute.cloud is grounded in long-term research on organic memristors, synapse-like devices, STDP learning, reservoir computing and neurorehabilitation-related neural modeling.
Research categories
Synaptic plasticity and STDP
Synaptic plasticity and STDP
Reservoir computing
Reservoir computing
Associative learning
Associative learning
Spinal cord / CPG modeling
Spinal cord / CPG modeling
Bio-signal and rehabilitation dynamics
Bio-signal and rehabilitation dynamics
Energy efficiency in neuromorphic systems
Energy efficiency in neuromorphic systems
Printed and flexible organic devices
Printed and flexible organic devices
Selected research articles
Printed and flexible organic devicesBiomimetics, 2026
Printed Organic Memristive Device on Rigid and Flexible Supports for Neuromorphic Applications
Victor Erokhin and co-authors
A recent article on printed organic memristive devices on rigid and flexible supports for neuromorphic applications.
Why this matters for NeuroCompute.cloud: It supports NeuroCompute.cloud’s direction toward remotely accessible organic memristive hardware, including flexible and wearable-relevant device platforms.
Read the articleEnergy efficiency in neuromorphic systemsIEEE Access, 2026
Critical Analysis of Energy Consumption in Neuro-Computational Systems
Ivan Kipelkin, Ilija Kamenko, Jovan Ivošević, Alina Fedorova, Grigory Zharkov, Jovana Maricic, Stojanka Bratic, Nebojša Pilipović, Natasa Samardzic, Staniša Dautović, Milovan Medojević, Branimir Bajac, Jordi Vallverdú, Dragiša Žunić, Francesco Restuccia, Vincenzo Alessio, Francesco Longo, Giovanni Merlino, Dario Bruneo, Salvatore Distefano, Alexander Toschev, Alexey Mikhaylov, Victor Erokhin, Max Talanov
A unified benchmark of energy consumption per synaptic event across GPUs, NPUs, FPGAs, digital spiking processors, memristive devices, and biological reference ranges.
Why this matters for NeuroCompute.cloud: It frames why specialized low-energy computing substrates matter for selected workloads rather than as universal GPU replacements.
Read the articleOrganic memristive devicesMaterials Today Chemistry, 2026
Printing Polyaniline Based Organic Memristive Devices for Neuromorphic Computing Applications
Silvia Battistoni, Anna N. Matsukatova, Rocco Carcione, Luciano Ferrucci, Matteo Parmeggiani, Matteo Cocuzza, Simone Luigi Marasso, Andrey V. Emelyanov, Vyacheslav A. Demin, Victor Erokhin
A study of printable polyaniline-based organic memristive devices and their potential as scalable, adaptable hardware elements for neuromorphic computing applications.
Why this matters for NeuroCompute.cloud: It supports the transition from device research to scalable experimental hardware modules.
Read the articleReservoir computingAdvanced Intelligent Systems, 2023
Combination of Organic-Based Reservoir Computing and Spiking Neuromorphic Systems for a Robust and Efficient Pattern Classification
Anna N. Matsukatova, Nikita V. Prudnikov, Vsevolod A. Kulagin, Silvia Battistoni, Anton A. Minnekhanov, Andrey D. Trofimov, Aleksandr A. Nesmelov, Sergey A. Zavyalov, Yulia N. Malakhova, Matteo Parmeggiani, Alberto Ballesio, Simone Luigi Marasso, Sergey N. Chvalun, Vyacheslav A. Demin, Andrey V. Emelyanov, Victor Erokhin
A fully organic system combining volatile polyaniline reservoir computing with a nonvolatile parylene-memristor spiking readout layer for robust spatiotemporal pattern classification.
Why this matters for NeuroCompute.cloud: It points toward cloud modules for temporal biosignals, sensor data and low-complexity classification.
Read the articleSpinal cord / CPG modelingFrontiers in Neuroscience, 2023
Memristive Circuit-Based Model of Central Pattern Generator to Reproduce Spinal Neuronal Activity in Walking Pattern
Dinar N. Masaev, Alina A. Suleimanova, Nikita V. Prudnikov, Mariia V. Serenko, Andrey V. Emelyanov, Vyacheslav A. Demin, Igor A. Lavrov, Max O. Talanov, Victor V. Erokhin
A self-learning memristive circuit model that uses biologically plausible spike-timing-dependent plasticity to reproduce spinal neuronal activity associated with walking patterns.
Why this matters for NeuroCompute.cloud: It is directly connected to the initial Spinal Cord Twin / CPG cloud module.
Read the articleOrganic memristive devicesBioNanoScience, 2020
Memristive Devices for Neuromorphic Applications: Comparative Analysis
Victor Erokhin
A comparative review of organic and inorganic memristive devices for neuromorphic applications, including memory-processing integration, sensors, oscillators, bio-mimicking circuits, and living-system coupling.
Why this matters for NeuroCompute.cloud: It explains the device-level foundation behind specialized memristive compute layers.
Read the articleAssociative learningJournal of Physics D: Applied Physics, 2020
Associative STDP-Like Learning of Neuromorphic Circuits Based on Polyaniline Memristive Microdevices
Nikita V. Prudnikov, Dmitry A. Lapkin, Andrey V. Emelyanov, Anton A. Minnekhanov, Yulia N. Malakhova, Sergey N. Chvalun, Vyacheslav A. Demin, Victor V. Erokhin
An experimental demonstration of improved STDP timescales and unsupervised associative learning in a simple spiking neural network built with polyaniline memristive microdevices.
Why this matters for NeuroCompute.cloud: It supports future associative learning and STDP demonstration modules.
Read the articleSynaptic plasticity and STDPBioNanoScience, 2011
Material Memristive Device Circuits with Synaptic Plasticity: Learning and Memory
Victor Erokhin, Tatiana Berzina, Paolo Camorani, Anteo Smerieri, Dimitris Vavoulis, Jianfeng Feng, Marco P. Fontana
An experimental demonstration of organic memristive device circuits showing adaptive behavior inspired by synaptic plasticity and learning in a biological neural reference system.
Why this matters for NeuroCompute.cloud: It is part of the scientific basis for hardware learning modules.
Read the articleSelected patents
Organic electronicsPublished November 24, 2003
Entirely Organic Diode
Inventors: Victor Erokhin, Gianluca Raviele, Joachim Glatz-Reichenbach, Claudio Nicolini
Assignee: Polo Naz Di Bioelettronica
A patent family entry for an all-organic diode, extending the early device toolbox around organic electronic components.
Why this matters for NeuroCompute.cloud: Organic-device primitives are part of the materials and circuit lineage behind organic memristive systems and low-energy adaptive hardware.
Read the patentNanoscale thin filmsPublished August 23, 1995
Thin Films and Structures Containing the Same
Inventors: Victor Erokhin, Paolo Facci, Claudio Nicolini
Assignee: Technobiochip
A Langmuir-Blodgett thin-film invention involving nanoscale particles for films capable of mono-electronic effects.
Why this matters for NeuroCompute.cloud: It shows an early research path into nanoscale functional films, a foundation area for later organic, bioelectronic and memristive device work.
Read the patentNanoscale thin filmsPublished July 18, 1996
Thin Film Devices
Inventors: Victor Erokhin, Paulo Facci, Claudio Nicolini
Assignee: Technobiochip
A thin-film device patent using nanometer-scale cadmium sulfide particles in Langmuir-Blodgett bilayers to enable room-temperature measurement of mono-electronic phenomena.
Why this matters for NeuroCompute.cloud: This connects device fabrication, nanoscale materials and measurement methods, which are all relevant to turning experimental physical substrates into accessible compute infrastructure.
Read the patentSensor systemsPublished June 19, 2004
Device for Monitoring of Physical and / or Chemical Parameters Through a Plurality of Sensor Groups
Inventors: Roman Berzine, Giovanni Catellani, Victor Erokhin, Lucio Mercadanti
Assignee: Politec Engineering S R L
A monitoring-device patent organized around multiple sensor groups for physical and chemical parameter tracking.
Why this matters for NeuroCompute.cloud: Sensor-facing hardware matters for NeuroCompute.cloud because many target workloads involve temporal signals, biosignals and adaptive sensor-processing experiments.
Read the patentBioelectronic filmsPublished April 18, 1995
Protein Thin Films and Compositions for Use in Their Preparation
Inventors: Francesco Antolini, Victor Erokhin, Paolo Facci, Claudio Nicolini, Sergei Vakula
Assignee: Technobiochip
A protein thin-film patent covering preparation methods for homogeneous, ordered, thermally stabilized and substrate-compatible protein films.
Why this matters for NeuroCompute.cloud: The work highlights the bioelectronic materials background behind coupling soft, organic and biological systems with engineered device platforms.
Read the patentPrinted functional materialsPublished April 15, 2002
Series of Pens for Drawing Lines with Electrical and Electro-Optical Properties
Inventors: Sandro Carrara, Victor Erokhin
Assignee: Sandro Carrara, Victor Erokhin
A patent entry for drawing lines with desired electrical and electro-optical properties, pointing toward direct-write functional materials.
Why this matters for NeuroCompute.cloud: Direct-write and printed functional structures are relevant to scalable organic electronics and future flexible or educational neuromorphic hardware formats.
Read the patentOrganic electronicsPublished May 23, 2002
Fully Organic Electrolytic Capacitor
Inventors: Victor Erokhin, Gianluca Raviele, Joachim Glatz-Reichenbach, Claudio Nicolini
Assignee: Polo Naz Di Bioelettronica
A patent family entry for a fully organic electrolytic capacitor, expanding the set of organic circuit elements.
Why this matters for NeuroCompute.cloud: Organic capacitive and ionic/electrolytic behavior is adjacent to the device physics used in adaptive organic electronics and memristive circuits.
Read the patentNanostructure assemblyPublished July 25, 2004
Procedure for the Standard Arrangement of Nanocaps
Inventors: Tatiana Berzina, Victor Erokhin, Svetlana Erokhina, Lorenzo Musa
Assignee: Lorenzo Musa
A patent entry for arranging nanoscale caps in a standardized way, addressing controlled organization at small scales.
Why this matters for NeuroCompute.cloud: Reliable nanoscale arrangement is one of the practical bridges between laboratory materials research and repeatable device fabrication.
Read the patentReady to test memristive hardware without building a lab?
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