A high aspect ratio Fin-Ion Sensitive Field Effect Transistor: compromises towards better electrochemical bio-sensing

The development of next generation medicines demand more sensitive and reliable label free sensing able to cope with increasing needs of multiplexing and shorter times to results. Field effect transistor-based biosensors emerge as one of the main possible technologies to cover the existing gap. The general trend for the sensors has been miniaturisation with the expectation of improving sensitivity and response time, but presenting issues with reproducibility and noise level. Here we propose a Fin-Field Effect Transistor (FinFET) with a high heigth to width aspect ratio for electrochemical biosensing solving the issue of nanosensors in terms of reproducibility and noise, while keeping the fast response time. We fabricated different devices and characterised their performance with their response to the pH changes that fitted to a Nernst-Poisson model. The experimental data were compared with simulations of devices with different aspect ratio, stablishing an advantage in total signal and linearity for the FinFETs with higher aspect ratio. In addition, these FinFETs promise the optimisation of reliability and efficiency in terms of limits of detection, for which the interplay of the size and geometry of the sensor with the diffusion of the analytes plays a pivotal role.Comment: Article submitted to Nano Letter

Electrical performance study of a large area multicrystalline silicon solar cell using a current shunt and a micropotentiometer

In this paper, a new technique using a Current Shunt and a Micropotentiometer has been used to study the electrical performance of a large area multicrystalline silicon solar cell at outdoor conditions. The electrical performance is mainly described by measuring both cell short circuit current and open circuit voltage. The measurements of this cell by using multimeters suffer from some problems because the cell has high current intensity with low output voltage. So, the solar cell short circuit current values are obtained by measuring the voltage developed across a known resistance Current Shunt. Samples of the obtained current values are accurately calibrated by using a Micropotentiometer (μpot) thermal element (TE) to validate this new measuring technique. Moreover, the solar cell open circuit voltage has been measured. Besides, the cell output power has been calculated and can be correlated with the measured incident radiation

The iso-response method

Throughout the nervous system, neurons integrate high-dimensional input streams and transform them into an output of their own. This integration of incoming signals involves filtering processes and complex non-linear operations. The shapes of these filters and non-linearities determine the computational features of single neurons and their functional roles within larger networks. A detailed characterization of signal integration is thus a central ingredient to understanding information processing in neural circuits. Conventional methods for measuring single-neuron response properties, such as reverse correlation, however, are often limited by the implicit assumption that stimulus integration occurs in a linear fashion. Here, we review a conceptual and experimental alternative that is based on exploring the space of those sensory stimuli that result in the same neural output. As demonstrated by recent results in the auditory and visual system, such iso-response stimuli can be used to identify the non-linearities relevant for stimulus integration, disentangle consecutive neural processing steps, and determine their characteristics with unprecedented precision. Automated closed-loop experiments are crucial for this advance, allowing rapid search strategies for identifying iso-response stimuli during experiments. Prime targets for the method are feed-forward neural signaling chains in sensory systems, but the method has also been successfully applied to feedback systems. Depending on the specific question, “iso-response” may refer to a predefined firing rate, single-spike probability, first-spike latency, or other output measures. Examples from different studies show that substantial progress in understanding neural dynamics and coding can be achieved once rapid online data analysis and stimulus generation, adaptive sampling, and computational modeling are tightly integrated into experiments