arXiv subjects

Antonio Massimiliano Mio

Publications and source records attributed to Antonio Massimiliano Mio.

4 recordsLinked to original sources

arXiv2026

Analogue Phase Change Computational Memory with High Precision Reads and Energy Efficient Writes

Resistive memory technologies offer a compelling advantage for in-memory computing. However, realizing a device architecture that simultaneously achieves high computational precision, efficiency, and density has remained elusive due to inherent trade-offs among these performance metrics. Here, we introduce a com- pact phase-change memory device architecture that combines an ultra-confined active switching volume for enhanced electro-thermal efficiency with a non-insulating thin film that suppresses temporal conductance fluctuations. We analytically model and back-end integrate these devices into crossbar arrays. Even with conventional, undoped phase-change materials, the device architecture enables a computational precision approaching 6 bits, low conductance values below 50 μS with an adequate conductance window, and a viable pathway toward sub-100 μA programming currents under nominal operating voltages.

cond-mat.mtrl-sci↗

arXiv2024

Laser Annealed SiO2/Si1-xGex Scaffolds for Nanoscaled Devices, Synergy of Experiment and Computation

Ultraviolet nanosecond laser annealing (UV-NLA) proves to be an important technique, particularly when tightly controlled heating and melting are necessary. In the realm of semiconductor technologies, the significance of nanosecond laser annealing (NLA) grows in tandem with the escalating intricacy of integration schemes in nano-scaled devices. Silicon-germanium alloys have been studied for decades for their compatibility with silicon devices. Indeed, they enable the manipulation of properties like strain, carrier mobilities and bandgap. In this framework, they can for instance boost the performances of p-type MOSFETs but also enable near infra-red absorption and emission for applications in photo-detection and photonics. Laser melting on such type of layers, however results, up to now, in the development of extended defects and poor control over layer morphology and homogeneity. In our study, we investigate the laser melting of ~700 nm thick relaxed silicon-germanium samples coated with SiO2 nano-arrays, observing the resulting material to maintain an unaltered lattice. We found the geometrical parameters of the silicon oxide having an impact on the thermal budget samples see, influencing melt threshold, melt depth and germanium distribution.

cond-mat.mes-hall↗

arXiv2021

Simulation of the impact of people mobility, vaccination rate, and virus variants on the evolution of Covid-19 outbreak

We have further extended our compartmental model describing the spread of the infection in Italy. The model is based on the assumption that the time evolution of all of the observable quantities (number of people still positive to the infection, hospitalized and fatalities cases, healed people, and total number of people that has contracted the infection) depend on average parameters, namely people diffusion coefficient, infection cross-section, and population density. The model provides precious information on the tight relationship between the variation of the reported infection cases and a well defined observable physical quantity: the average number of people that lie within the daily displacement area of any single person. The extension of the model now includes self-consistent evaluation of the reproduction index, effect of immunization due to vaccination, and potential impact of virus variants on the dynamical evolution of the outbreak. The model fits very well the epidemic data, and allows us to strictly relate the time evolution of the number of hospitalized case and fatalities to the change of people mobility, vaccination rate, and appearance of an initial concentration of people positives for new variants of the virus.

physics.soc-ph↗

arXiv2020

Phenomenological description of spread of Covid-19 in Italy: people mobility as main factor controlling propagation of infection cases

The spread of the coronavirus (COVID-19), starting in late 2019, has determined in Italy several interventions aimed to prevent saturation of the health system. We have examined the effects of such measures by proposing a mean-field model describing the spread of the infection based on a simple diffusion process where all the observable variables (number of people still positive to the infection, hospitalized and fatalities cases, healed people, and total number of people that has contracted the infection) depend on average parameters, namely diffusion coefficient, infection cross-section, and population density. Although this model is less sophisticated than other models in the literature, it allows us to directly relate the trend of the epidemic statistical information (hospitalized cases, number of fatalities, number of infected people, etc.) to a well defined observable physical quantity: the average number of people that any individual meets per day. The model fits very well the epidemic data, and allows us to strictly relate the time evolution of the number of hospitalized case and fatalities of the outbreak to the change of people mobility, consequent to the implementation of progressive restrictions in Italy, running until the present days (November the 15th, 2020).

physics.soc-ph↗