Monolithic pixel sensors integrate the sensor matrix and readout in the same silicon die, and therefore present several advantages over the more largely used hybrid detectors in high-energy physics. They offer an easier detector assembly, lower cost, lower ...
Organic electrochemical transistors (OECTs) have gained enormous attention due to their potential for bioelectronics and neuromorphic computing. However, their implementation into real-world applications is still impeded by a lack of understanding of the c ...
Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...
Over the last decades, implantable neural interfaces have been extensively explored and effectively deployed to address neurological and mental health disorders. The existing solutions present several limitations. Firstly, the physical size of the implanta ...
The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...
The discovery of a large fab-to-fab variability in the TID response of the CMOS technologies used in the design of ASICs for the particle detectors of the HL-LHC triggered a monitoring effort to verify the consistency of the CMOS production process over ti ...
Factored form is a powerful multi-level representation of a Boolean function that readily translates into an implementation of the function in CMOS technology. In particular, the number of literals in a factored form correlates strongly with the number of ...
This article presents the design of a front-end circuit for monolithic active pixel sensors (MAPSs). The circuit operates with a sensor featuring a small, low-capacitance (
