arXiv subjects

Leonardo Martini

Publications and source records attributed to Leonardo Martini.

12 recordsLinked to original sources

arXiv2026

Graphene Electric Double-Layer Transistors for Enhanced-Sensitivity Label-Free Detection of Human Serum Albumin

Accurate detection of human serum albumin (HSA) is essential for the early diagnosis and monitoring of renal and hepatic disorders. We present a graphene-based electrolyte-gated field-effect transistor (EGFET) for label-free, real-time quantification of HSA under non-Faradaic operation. Devices exploit the high interfacial capacitance of the electric double layer (EDL) to transduce electrostatic perturbations induced by albumin adsorption into measurable conductance modulation. Negatively charged HSA molecules induce systematic modulation of the graphene channel, producing a concentration-dependent displacement of the Dirac voltage consistent with p-type doping. To establish a molecular-level interpretation of the sensing response, Brownian Dynamics simulations show that HSA adsorbs onto graphene through multiple adsorption orientations associated with heterogeneous interfacial charge distributions and variable dipole alignments relative to the surface. Adsorption is energetically stabilized by van der Waals interactions. Analysis of transfer characteristics across concentrations ranging from 0.01 to 30mgmL-1 reveals a correlation between surface charge density and carrier transport modulation within the electric double layer. Optimized devices exhibit a limit of detection of 0.0087 mg mL-1 and a linear dynamic range extending to 10 mg mL-1. The response remains non-Faradaic under sub-volt operation with reversible and reproducible behavior. The use of an inverse-mobility analytical metric highlights the role of disorder-enhanced carrier scattering in signal amplification, enabling sensitive electrostatic detection while preserving reversible device operation. These results establish liquid-gated graphene EGFETs as a promising platform for quantitative protein sensing and provide insight into disorder-mediated transport mechanisms in graphene bioelectronic devices.

cond-mat.mes-hall↗

arXiv2025

Scalable CVD Graphene Field-Effect Transistor Platform for Viral Detection: Application to COVID-19

The rapid and global spread of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), underscored the urgent need for fast, reliable, and adaptable diagnostic tools capable of responding to current and future viral threats. Early diagnosis is key to limiting transmission, and biosensors based on nanomaterials offer promising solutions for accurate and rapid bioanalyte detection. In this work, we present a scalable matrix of graphene-based field-effect transistors (GFETs) for the direct and rapid detection of the SARS-CoV-2 spike protein. High-quality graphene is functionalized in a single step with ACE2-His, enabling detection of the spike protein with a limit of detection as low as 1 fg/mL in phosphate-buffered saline (PBS). A robust statistical analysis, based on measurements from approximately 70 devices per analyte concentration, demonstrates the reproducibility and reliability of the platform. This label-free, scalable, and reproducible COVID-19 antigen sensor can be readily adapted to detect emerging SARS-CoV-2 variants or other viral pathogens, offering a flexible approach for future diagnostic applications.

physics.bio-ph↗

arXiv2023

Scalable High-Mobility Graphene/hBN Heterostructures

Graphene-hexagonal boron nitride (hBN) scalable heterostructures are pivotal for the development of graphene-based high-tech applications. In this work, we demonstrate the realization of high-quality graphene-hBN heterostructures entirely obtained with scalable approaches. hBN continuous films were grown via ion beam-assisted physical vapor deposition directly on commercially available $SiO_2/Si$ and used as receiving substrates for graphene single-crystal matrixes grown by chemical vapor deposition on copper. The structural, chemical, and electronic properties of the heterostructure were investigated by atomic force microscopy, Raman spectroscopy, and electrical transport measurements. We demonstrate graphene carrier mobilities exceeding $10,000 cm^2/Vs$ in ambient conditions, 30% higher than those directly measured on $SiO_{2}/Si$. We prove the scalability of our approach by measuring more than 100 transfer length method devices over a centimeter scale, which present an average carrier mobility of $7500 \pm 850 cm^{2}/Vs$. The reported high-quality all-scalable heterostructures are of relevance for the development of graphene-based high-performing electronic and optoelectronic applications.

physics.app-ph↗

arXiv2022

Biological Random Walks: multi-omics integration for disease gene prioritization

Motivation: Over the past decade, network-based approaches have proven useful in identifying disease modules within the human interactome, often providing insights into key mechanisms and guiding the quest for therapeutic targets. This is all the more important, since experimental investigation of potential gene candidates is an expensive task, thus not always a feasible option. On the other hand, many sources of biological information exist beyond the interactome and an important research direction is the design of effective techniques for their integration. Results: In this work, we introduce the Biological Random Walks (BRW) approach for disease gene prioritization in the human interactome. The proposed framework leverages multiple biological sources within an integrated framework. We perform an extensive, comparative study of BRW's performance against well-established baselines. Availability and implementation: All code is publicly available and can be downloaded at \url{https://github.com/LeoM93/BiologicalRandomWalks}. We used publicly available datasets, details on their retrieval and preprocessing are provided in the supplementary material.

q-bio.QM↗

arXiv2022

Network Based Approach to Gene Prioritization at Genome-Wide Association Study Loci

Motivation: Genome-wide association studies (GWAS) have successfully identified thousands of genetic risk loci for complex traits and diseases. Most of these GWAS loci lie in regulatory regions of the genome and the gene through which each GWAS risk locus exerts its effects is not always clear. Many computational methods utilizing biological data sources have been proposed to identify putative casual genes at GWAS loci; however, these methods can be improved upon. Results: We present the Relations-Maximization Method, a dense module searching method to identify putative causal genes at GWAS loci through the generation of candidate sub-networks derived by integrating association signals from GWAS data into the gene co-regulation network. We employ our method in a chronic obstructive pulmonary disease GWAS. We perform an extensive, comparative study of Relations-Maximization Method's performance against well-established baselines.

q-bio.QM↗

arXiv2022

Industrial graphene coating of low-voltage copper wires for power distribution

Copper (Cu) is the electrical conductor of choice in many categories of electrical wiring, with household and building installations being the major market of this metal. This work demonstrates the coating of Cu wires - with diameters relevant for low voltage (LV) applications - with graphene. The chemical vapor deposition (CVD) coating process is rapid, safe, scalable and industrially compatible. Graphene-coated Cu wires display oxidation resistance and increased electrical conductivity (up to 1% immediately after coating and up to 3% after 24 months), allowing for wire diameter reduction and thus significant savings in wire production costs. Combined spectroscopic and diffraction analysis indicate that the conductivity increase is due to a change in Cu crystallinity, induced by the coating process conditions, while electrical testing of aged wires shows that graphene plays a major role in maintaining improved electrical performances over long periods of time. Finally, graphene coating of Cu wires using an ambient pressure roll-to-roll (R2R) CVD reactor is demonstrated. This enables the in-line production of graphene-coated metallic wires as required for industrial scale-up.

physics.app-ph↗

arXiv2022

Network and Sequence-Based Prediction of Protein-Protein Interactions

Background:Typically, proteins perform key biological functions by interacting with each other. As a consequence, predicting which protein pairs interact is a fundamental problem. Experimental methods are slow, expensive, and may be error prone.Many computational methods have been proposed to identify candidate interacting pairs. When accurate, they can serve as an inexpensive, preliminary filtering stage, to be followed by downstream experimental validation. Among such methods, sequence-based ones are very promising.Results:We present, a new algorithm that leverages both topological and biological information to predict protein-protein interactions. We comprehensively compare our Framework with state-of-the-art approaches on reliable PPIs datasets, showing that they have competitive or higher accuracy on biologically validated test sets.Conclusion:We shown that topological plus sequence-based computational methods can effectively predict the entire human interactome compared with methods that leverage only one source of biological information.

q-bio.BM↗

arXiv2021

Ultra-clean high-mobility graphene on technologically relevant substrates

Graphene grown via chemical vapour deposition (CVD) on copper foil has emerged as a high-quality, scalable material, that can be easily integrated on technologically relevant platforms to develop promising applications in the fields of optoelectronics and photonics. Most of these applications require low-contaminated high-mobility graphene (i.e., approaching 10 000 $cm^2 V^{-1} s^{-1}$) at room temperature) to reduce device losses and implement compact device design. To date, these mobility values are only obtained when suspending or encapsulating graphene. Here, we demonstrate a rapid, facile, and scalable cleaning process, that yields high-mobility graphene directly on the most common technologically relevant substrate: silicon dioxide on silicon (SiO$_2$/Si). Atomic force microscopy (AFM) and spatially-resolved X-ray photoelectron spectroscopy (XPS) demonstrate that this approach is instrumental to rapidly eliminate most of the polymeric residues which remain on graphene after transfer and fabrication and that have adverse effects on its electrical properties. Raman measurements show a significant reduction of graphene doping and strain. Transport measurements of 50 Hall bars (HBs) yield hole mobility $μ_h$ up to 9000 $cm^2 V^{-1} s^{-1}$ and electron mobility $μ_e$ up to 8000 $cm^2 V^{-1} s^{-1}$, with average values $μ_h$ 7500 $cm^2 V^{-1} s^{-1}$ and $μ_e$ 6300 $cm^2 V^{-1} s^{-1}$. The carrier mobility of ultraclean graphene reach values nearly double of that measured in graphene HBs processed with acetone cleaning, which is the method widely adopted in the field. Notably, these mobility values are obtained over large-scale and without encapsulation, thus paving the way to the adoption of graphene in optoelectronics and photonics.

cond-mat.mtrl-sci↗

arXiv2020

Ultrafast, Zero-Bias, Graphene Photodetectors with Polymeric Gate Dielectric on Passive Photonic Waveguides

We report compact, scalable, high-performance, waveguide integrated graphene-based photodetectors (GPDs) for telecom and datacom applications, not affected by dark current. To exploit the photothermoelectric (PTE) effect, our devices rely on a graphene-polymer-graphene stack with static top split gates. The polymeric dielectric, poly(vinyl alcohol) (PVA), allows us to preserve graphene quality and to generate a controllable p-n junction. Both graphene layers are fabricated using aligned single-crystal graphene arrays grown by chemical vapor deposition. The use of PVA yields a low charge inhomogeneity 8 x 10$^{10}$ $cm^{-2}$ at the charge neutrality point, and a large Seebeck coefficient 140 $μ$V K$^{-1}$, enhancing the PTE effect. Our devices are the fastest GPDs operating with zero dark current, showing a flat frequency response up to 67 GHz without roll-off. This performance is achieved on a passive, low-cost, photonic platform, and does not rely on nanoscale plasmonic structures. This, combined with scalability and ease of integration, makes our GPDs a promising building block for next-generation optical communication devices.

physics.app-ph↗

arXiv2020

Biological Random Walks: integrating heterogeneous data in disease gene prioritization

This work proposes a unified framework to leverage biological information in network propagation-based gene prioritization algorithms. Preliminary results on breast cancer data show significant improvements over state-of-the-art baselines, such as the prioritization of genes that are not identified as potential candidates by interactome-based algorithms, but that appear to be involved in/or potentially related to breast cancer, according to a functional analysis based on recent literature.

q-bio.MN↗

arXiv2019

Deterministic direct growth of WS2 on CVD graphene arrays

The combination of the exciting properties of graphene with those of monolayer tungsten disulfide (WS2) makes this heterostack of great interest for electronic, optoelectronic and spintronic applications. The scalable synthesis of graphene/WS2 heterostructures on technologically attractive substrates like SiO2 would greatly facilitate the implementation of novel two-dimensional (2D) devices. In this work, we report the direct growth of monolayer WS2 via chemical vapor deposition (CVD) on single-crystal graphene arrays on SiO2. Remarkably, spectroscopic and microscopic characterization reveals that WS2 grows only on top of the graphene crystals so that the vertical heterostack is selectively obtained in a bottom-up fashion. Spectroscopic characterization indicates that, after WS2 synthesis, graphene undergoes compressive strain and hole doping. Tailored experiments show that such hole doping is caused by the modification of the SiO2 stoichiometry at the graphene/SiO2 interface during the WS2 growth. Electrical transport measurements reveal that the heterostructure behaves like an electron-blocking layer at large positive gate voltage, which makes it a suitable candidate for the development of unipolar optoelectronic components.

cond-mat.mtrl-sci↗

arXiv2019

Structure-dependent electrical properties of graphene nanoribbon devices with graphene electrodes

Graphene nanoribbons (GNRs) are a novel and intriguing class of materials in the field of nanoelectronics, since their properties, solely defined by their width and edge type, are controllable with high precision directly from synthesis. Here we study the correlation between the GNR structure and the corresponding device electrical properties. We investigated a series of field effect devices consisting of a film of armchair GNRs with different structures (namely width and/or length) as the transistor channel, contacted with narrowly spaced graphene sheets as the source-drain electrodes. By analyzing several tens of junctions for each individual GNR type, we observe that the values of the output current display a width-dependent behavior, indicating electronic bandgaps in good agreement with the predicted theoretical values. These results provide insights into the link between the ribbon structure and the device properties, which are fundamental for the development of GNR-based electronics.

cond-mat.mes-hall↗