Publications by Carlo Ricciardi

2022 roadmap on neuromorphic computing and engineering

Emre Neftci, Srikanth Ramaswamy, Roberto Galeazzi, Yihwa Kim, Silvia Tolu, Abu Sebastian, Carlo Ricciardi, Xuan Li, Elisa Donati

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer i ...

IOP Publishing Ltd2022

Na3V2(PO4)(3)-Supported Electrospun Carbon Nanofiber Nonwoven Fabric as Self-Standing Na-Ion Cell Cathode

Jürgen Brugger, Carlo Ricciardi, Lorenzo Lucherini

Sodium-ion technology is a reliable alternative to lithium-ion for large-scale energy storage because of the abundance of sodium sources and related low cost. In this work, we report about a simple fabrication of self-standing electrodes based on electrosp ...

2020

Fabrication of clamped-clamped beam resonators with embedded fluidic nanochannel

Philippe Renaud, Stefano Silvio Giovanni Varricchio, Luis Guillermo Villanueva Torrijo, Stefano Stassi, Damien Maillard, Annalisa De Pastina, Davide Scaiola, Carlo Ricciardi

Suspended nanochannel resonators (SNRs) are promising devices able to characterize mass down to the attogram scale, thus being able to detect nanoparticles or biomolecules. In this paper, we present a flexible fabrication process for SNRs based on a sacrif ...

ELSEVIER2020

Analog Control of Retainable Resistance Multistates in HfO2 Resistive-Switching Random Access Memories (ReRAMs)

Yusuf Leblebici, Jury Sandrini, Elmira Shahrabi, Carlo Ricciardi, Cecilia Giovinazzo, Oguz Tolga Celik

Resistive-switching random access memory (ReRAM) technologies are nowadays a good candidate to overcome the bottleneck of Von Neumann architectures, taking advantage of their logic-in-memory capability and the ability to mimic biological synapse behavior. ...

AMER CHEMICAL SOC2019

Multi-ReRAM synapses for artificial neural network training

Yusuf Leblebici, Elmira Shahrabi, Irem Boybat Kara, Igor Krawczuk, Abu Sebastian, Carlo Ricciardi, Cecilia Giovinazzo, Evangelos Eleftheriou

Metal-oxide-based resistive memory devices (ReRAM) are being actively researched as synaptic elements of neuromorphic co-processors for training deep neural networks (DNNs). However, device-level non-idealities are posing significant challenges. In this wo ...

IEEE2019

Switching Kinetics Control of W-Based ReRAM Cells in Transient Operation by Interface Engineering

Yusuf Leblebici, Thomas La Grange, Mahmoud Hadad, Miguel Ramos, Carlo Ricciardi, Cecilia Giovinazzo

Tungsten (W) is one of the most promising materials to be used in resistive random-access memory electrodes due to its low work function and compatibility with semiconductors, which raises the possibility of device integration, scalability, and low power c ...

WILEY2019