Gianluca Piccinini

In the field of electronics, molecular technologies provide promising opportunities for innovators and scientists to advance technological progress. At the molecular scale, the simulation of ensembles becomes fundamental to advancing the fabrication, design, and prototyping of new technologies. This work proposes a framework leveraging the SCERPA tool and DFT calculation to efficiently evaluate the electronic properties of molecular ensembles. The Molecular Field‐Coupled Nanocomputing (MolFCN) is considered as a case study to validate ab initio‐comparable precision resulting from the SCERPA calculation on charge‐constrained multi‐molecule systems. In addition, it is demonstrated that the SCERPA results can be used as a nonrelativistic initial guess of DFT calculation, eventually reducing the ab initio computation time by 86 %. Finally, a periodic molecular FCN system is proposed, named SelfPolarizer. The proposed framework is employed to demonstrate that the ensemble naturally encodes QCA‐like digital information, providing the first simulated proof of concept for MolFCN technology obtained with DFT precision.

This study uses DFT to show that hydrogen passivation raises energy barriers for Pt, Cu, and Au ALD on silicon, suggesting selective deposition. Gold shows the largest barrier shift; platinum has the most controlled pathways.

The growing interest in tuning the conduction properties of single-molecule junctions has drawn attention to studying their interaction with incident electromagnetic fields. The theoretical complexity of this problem necessitates the use of nonequilibrium statistical mechanics combined with quantum electrodynamics, leading to extremely time-consuming simulations. In this work, we propose a computationally efficient algorithm, which combines EE-BESD—an efficient and effective simulator of current–voltage characteristics in dark conditions—with approximated models for light interaction, specifically the Tien-Gordon and Floquet models. We validate EE-BESD-PAT through comparison with ab initio calculations and experimental data from the literature. Our computational model demonstrates good agreement with both experimental and density functional theory calculations, demonstrating that the proposed method is a promising computationally efficient tool without sacrificing accuracy.

Junctionless Nanosheet gate-all-around Field Effect Transistor (JL-NSGAAFET) is a promising technology characterized by the absence of any junctions between source-channel-drain. This absence allows to further scale down transistors while limiting short-channel effects. In this article, JL-NSGAAFET is explored as a potential candidate for the next 3 nm technology node through 3D TCAD simulations. First, we propose and simulate, through fabrication process simulations, a fabrication strategy for the JL-NSGAAFET compatible with the current manufacturing technology and based on the inversion mode NSGAAFET fabrication process. The high-k gate dielectric (HfO₂) and metal-gate technology (TiN) are also adopted in the fabrication process to enhance the electrostatic gate control over the channel for the n-type and p-type transistors. Then, we perform electrical simulations of the device by also including drift-diffusion model and quantum density gradient correction. We characterize the device in terms of electrical performance and compare with the conventional NSGAAFET. Furthermore, to investigate the impact of the device scaling on the unwanted short channel effects, we simulate and analyze the devices while varying the gate length (L_G) from 20 nm to 12 nm. Our reported simulation results prove that JL-NSGAAFET exhibits near-ideal subthreshold slope, low drain-induced barrier lowering (DIBL) and high on-to-off current ratio (I_ON/I_OFF) with superior advantages of greater drive currents and a simpler fabrication process because of the absence of junctions.

Molecular Field-Coupled Nanocomputing (MolFCN) represents a revolutionary approach to computational technology, exploiting single molecules for encoding and processing logical information. MolFCN permits zero-current logical operations to achieve ultra-low power and hyper-miniaturized computing units. This perspective article explores the current state and future potential of MolFCN, highlighting recent technological advancements, potential applications, and the significant challenges that lie ahead. Despite the challenges, the pathway to practical implementation holds significant promise, with obstacles such as scalability, stability, integration, and practical considerations offering opportunities for innovation and advancement. MolFCN can shape the future of nanocomputing and contribute to current major challenges in nanoelectronics by opening key research directions.

The molecular Field-Coupled Nanocomputing (molFCN) paradigm encodes digital information in the charge distribution of molecules. The information propagates through electrostatic coupling within molecules, permitting minimal power consumption. Although the promising results in the design of molFCN circuits, a prototype is missing. Therefore, this work moves toward molFCN fabrication by presenting a methodology combining Finite Element Modelling with the SCERPA tool, boosting the simulation accuracy by considering both molecule and device physics. First, this work analyzes nano-trench-based molFCN single-line wires, examining information propagation dependencies on the nano-trench geometries. Then, the analysis of nano-trench-based multi-line wires points out the primary prototype specification to achieve this advantageous molFCN solution. Finally, we demonstrate the nano-trench as a valuable solution to achieve the write-in mechanism. Overall, this paper paves the way for molFCN fabrication-aware simulations for future prototyping.

The metal-electrode interface is key to unlocking emergent behaviour in all organic electrified systems, from battery technology to molecular electronics. In the latter, interfacial engineering has enabled efficient transport, higher device stability, and novel functionality. Mechanoresistivity – the change in electrical behaviour in response to a mechanical stimulus and a pathway to extremely sensitive force sensors – is amongst the most studied phenomena in molecular electronics, and the molecule-electrode interface plays a pivotal role in its emergence, reproducibility, and magnitude. In this contribution, we show that organometallic molecular wires incorporating a Pt(II) cation show mechanoresistive behaviour of exceptional magnitude, with conductance modulations of more than three orders of magnitude upon compression by as little as 1 nm. We synthesised series of cyclometalated Pt(II) molecular wires, and used scanning tunnelling microscopy – break junction techniques to characterise their electromechanical behaviour. Mechanoresistivity arises from an interaction between the Pt(II) cation and the Au electrode triggered by mechanical compression of the single-molecule device, and theoretical modelling confirms this hypothesis. Our study provides a new tool for the design of functional molecular wires by exploiting previously unreported ion-metal interactions in single-molecule devices, and develops a new framework for the development of mechanoresistive molecular junctions.

The molecular field-coupled nanocompunting (molFCN) technology encodes the information in the charge distribution of electrostatically coupled molecules, making it an exciting solution for future beyond-CMOS low-power electronics. Recent literature has shown that multi-molecule molFCN enables the design of devices with tailored unconventional characteristics, such as majority voters working as artificial neurons. This work presents a multi-molecule molFCN neuron model based on the weighted-inputs formulation to estimate molFCN neurons behavior. Then, the introduced model is used to design each neuron of molFCN circuits working as neural networks. In particular, we propose a molFCN neural network operating as an input pattern classifier. The results show the model aptitude in predicting the logic output values for individual neurons and, consequently, entire networks. The model accuracy has been evaluated by comparing the results from the neuron mathematical model with those obtained from the circuit-level simulations conducted with the SCERPA tool. Overall, this study highlights the strategic use of diverse molecules in molFCN layouts, customizing circuit operations, and expanding design possibilities for specific molFCN device functioning.

We investigate through ab-initio simulations the gold-8PyrroleDiThiol-gold (Au-8PyDT) molecular quantum dot as an amperometric single-molecule sensor for the aflatoxin B1 (AFB1) detection. We study the chemical-physical interaction of AFB1 with the Au-8PyDT, and we analyze the transport characteristics of the four most probable adsorption configurations. We also investigate the link between transport modulation and adsorption mechanism. Interestingly, the investigated sensor exhibits conduction features similar to other types of quantum dot-based sensors. A significant current suppression occurs in all cases, with almost two orders of magnitude of current decrease in presence of AFB1 at 0.6 V. Considering the sensor robustness w.r.t. the specific adsorption configurations, our study motivates future research in this field.

NanoSheet-Gate-All-Around-FETs (NS-GAAFETs) are commonly recognized as the future technology to push the digital node scaling into the sub-3 nm range. NS-GAAFETs are expected to replace FinFETs in a few years, as they provide highly electrostatic gate control thanks to the GAA structure, with four sides of the NS channel entirely enveloped by the gate. At the same time, the NS rectangular cross-section is demonstrated to be effective in its driving strength thanks to its high saturation current, tunable through the NS width used as a design parameter. In this work, we develop a NS-GAAFET compact model and we use it to link peculiar single-device parameters to digital circuit performance. In particular, we use the well-known BSIM-CMG core solver for multigate transistors as a starting point and develop an ad hoc resistive and capacitive network to model the NS-GAAFET geometrical and physical structure. Then, we employ the developed model to design and optimize a digital inverter and a five-stage ring oscillator, which we use as a performance benchmark for the NS-GAAFET technology. Through Cadence Virtuoso SPICE simulations, we investigate the digital NS-GAAFET performance for both high-performance and low-power nodes, according to the average future node present in the International Roadmap for Devices and Systems. We focus our analysis on the main different technological parameters with regard to FinFET, i.e., the inner and outer spacers. Our results highlight that in future technological nodes, the choice of alternative low-K dielectric materials for the NS spacers will assume increasing importance, being as relevant, or even more relevant, than photolithographic alignment and resolution at the sub-nm scale.