SCERPA Simulation of Clocked Molecular Field-Coupling Nanocomputing

Among all the possible technologies proposed for post-CMOS computing, molecular field-coupled nanocomputing (FCN) is one of the most promising technologies. The information propagation relies on electrostatic interactions among single molecules, overcoming the need for electron transport, significantly reducing energy dissipation. The expected working frequency is very high, and high throughput may be achieved by introducing an efficient pipeline of information propagation. The pipeline could be realized by adding an external clock signal that controls the propagation of data and makes the transmission adiabatic. In this article, we extend the Self-Consistent Electrostatic Potential Algorithm (SCERPA), previously introduced to analyze molecular circuits with a uniform clock field, to clocked molecular devices. The single-molecule is analyzed by ab initio calculations and modeled as an electronic device. Several clocked devices have been partitioned into clock zones and analyzed: the binary wire, the bus, the inverter, and the majority voter. The proposed modification of SCERPA enables linking the functional behavior of the clocked devices to molecular physics, becoming a possible tool for the eventual physical design verification of emerging FCN devices. The algorithm provides some first quantitative results that highlight the clocked propagation characteristics and provide significant feedback for the future implementation of molecular FCN circuits

Multi-Molecule Field-Coupled Nanocomputing for the Implementation of a Neuron

In recent years, several alternatives have been proposed to face CMOS scaling problems. Among these, molecular Field-Coupled Nanocomputing is a paradigm that encodes information in the spatial charges distribution and promises to consume a minimal amount of power. In this technology, circuits have always been designed using the same molecule type, and logic functions are obtained through specific layouts. This work demonstrates that multi-molecule circuits, which use different kinds of molecules in the same layout, enhance the circuit features and set up a new way to conceive molecular Field-Coupled Nanocomputing. In particular, by inserting different molecules with specific characteristics into appropriate layout positions, it is possible to obtain an artificial neuron behavior using the Majority Voter layout

Beyond-CMOS Artificial Neuron: A simulation-based exploration of the molecular-FET

The recent growth of Artificial Neural Networks fueled the design of numerous Artificial Intelligence (AI) dedicated hardware implementations. High power dissipation, computational complexity, and large area footprints currently limit CMOS based real-time embedded AI applications. In this work, we design and simulate through SPICE, for the first time, an artificial analog neuron based on the molecular Field-Effect Transistor (molFET) technology. MolFETs are described by a circuital model whose physical characteristics are extracted from atomistic simulations. The designed neuron is a single column of a crossbar-like circuit representing a layer of seven parallel neurons. The drain currents sum up in a soma-like circuit - modelled through a comparator - and trigger the output pulses. We demonstrate the advantages of the molFET in terms of area, power, and speed by comparing it with a conventional MOSFET implementation. The results confirm the molecular technology is a promising candidate for accomplishing high neuron throughput capability and massive redundancy, still providing high energy efficiency. The obtained results foster further investigation of molFET technology both at the device and circuit level