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| iunet [2020/12/23 13:36] – Michele GIUGLIANO | iunet [2020/12/23 13:42] – Michele GIUGLIANO |
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| The “Consorzio Nazionale Interuniversitario per la Nanoelettronica” (IUNET, Italian Universities Nano-Electronics Team), is a non-profit organization, aimed to lead and coordinate the effort of the major Italian university teams in the field of nanoelectronic device modelling and characterization. Current members of IUNET are the Universities of Bologna, Calabria, Ferrara, Modena e Reggio Emilia, Padova, Perugia, Pisa, Roma, Udine, Politecnico of Milano and Politecnico of Torino. They offer complementary expertise in the fields of modelling, simulation and characterization of CMOS-based, memory and Beyond CMOS nanometer-size devices. IUNET technical reputation is confirmed by many projects where it has been partner in the 5th, 6th and 7th FP and H2020 programmes, and the ENIAC and ECSEL JU calls, including, among others, the NANOFUNCTION project on sensors and energy harvesting, the SINANO and NANOSIL networks, the STEEPER and E2SWITCH projects on energy efficient nanoelectronics. IUNET is also member of AENEAS and SINANO Institute. | The “Consorzio Nazionale Interuniversitario per la Nanoelettronica” (IUNET, Italian Universities Nano-Electronics Team), is a non-profit organization, aimed to lead and coordinate the effort of the major Italian university teams in the field of nanoelectronic device modelling and characterization. Current members of IUNET are the Universities of Bologna, Calabria, Ferrara, Modena e Reggio Emilia, Padova, Perugia, Pisa, Roma, Udine, Politecnico of Milano and Politecnico of Torino. They offer complementary expertise in the fields of modelling, simulation and characterization of CMOS-based, memory and Beyond CMOS nanometer-size devices. IUNET technical reputation is confirmed by many projects where it has been partner in the 5th, 6th and 7th FP and H2020 programmes, and the ENIAC and ECSEL JU calls, including, among others, the NANOFUNCTION project on sensors and energy harvesting, the SINANO and NANOSIL networks, the STEEPER and E2SWITCH projects on energy efficient nanoelectronics. IUNET is also member of AENEAS and SINANO Institute. |
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| * A. Bandiziol, et al., “A TCAD-Based Methodology to Model the Site-Binding Charge at ISFET/Electrolyte Interfaces”, IEEE T-ED, 2015, doi: 10.1109/TED.2015.2464251. | * A. Bandiziol, et al., “A TCAD-Based Methodology to Model the Site-Binding Charge at ISFET/Electrolyte Interfaces”, IEEE T-ED, 2015, doi: 10.1109/TED.2015.2464251. |
| * P. Scarbolo et al., “Characterization and modelling of differential sensitivity of nanoribbon-based pH-sensors”, Proc. 2015 Transducers, pp. 2188-2191. | * P. Scarbolo et al., “Characterization and modelling of differential sensitivity of nanoribbon-based pH-sensors”, Proc. 2015 Transducers, pp. 2188-2191. |
| * P. Palestri, et al., ''Sensitivity of Silicon Nanowire Biochemical Sensors'', in Beyond-CMOS Nanodevices, Wiley, pag. 43-63, 2014, ISBN 978-1-848216549. | * P. Palestri, et al., Sensitivity of Silicon Nanowire Biochemical Sensors, in Beyond-CMOS Nanodevices, Wiley, pag. 43-63, 2014, ISBN 978-1-848216549. |
| * E.Accastelli, et al., “Multi-Wire Tri-Gate Silicon Nanowires Reaching Milli-pH Unit Resolution in One Micron Square Footprint”, Biosensors 2016, 6(1), 9; doi:10.3390/bios6010009. | * E.Accastelli, et al., “Multi-Wire Tri-Gate Silicon Nanowires Reaching Milli-pH Unit Resolution in One Micron Square Footprint”, Biosensors 2016, 6(1), 9; doi:10.3390/bios6010009. |
| * A.Cossettini et al., “On the Response of Nanoelectrode Impedance Spectroscopy Measures to Plant, Animal, and Human Viruses”, accepted for publication, IEEE Trans. on NanoBioScience, 2018, doi: 10.1109/TNB.2018.2826919. | * A.Cossettini et al., “On the Response of Nanoelectrode Impedance Spectroscopy Measures to Plant, Animal, and Human Viruses”, accepted for publication, IEEE Trans. on NanoBioScience, 2018, doi: 10.1109/TNB.2018.2826919. |
| * F. M. Puglisi et al., "Energy-Efficient Logic-in-Memory 1-bit Full Adder Enabled by a Physics-Based RRAM Compact Model", accepted for publication, Proc. ESSDERC 2018. | * F. M. Puglisi et al., "Energy-Efficient Logic-in-Memory 1-bit Full Adder Enabled by a Physics-Based RRAM Compact Model", accepted for publication, Proc. ESSDERC 2018. |
| * J. Woo et al., "Linking Conductive Filament Properties and Evolution to Synaptic Behavior of RRAM Devices for Neuromorphic Applications," IEEE EDL, pp. 1220, 2017, doi: 10.1109/LED.2017.2731859. | * J. Woo et al., "Linking Conductive Filament Properties and Evolution to Synaptic Behavior of RRAM Devices for Neuromorphic Applications," IEEE EDL, pp. 1220, 2017, doi: 10.1109/LED.2017.2731859. |
| L. Larcher et al., "Multiscale modeling of neuromorphic computing: From materials to device operations," Proc. IEEE IEDM 2017, doi: 10.1109/IEDM.2017.8268374. | * L. Larcher et al., "Multiscale modeling of neuromorphic computing: From materials to device operations," Proc. IEEE IEDM 2017, doi: 10.1109/IEDM.2017.8268374. |
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