scholarly journals Laser induced forward transfer of graphene and other 2D materials and computational modelling of transfer enabling conditions

2021 ◽  
Author(s):  
Adamantia Logotheti ◽  
Symeon Papazoglou ◽  
Dimitrios Kaltsas ◽  
Filimon Zacharatos ◽  
Leonidas Tsetseris ◽  
...  
Keyword(s):  
2D Materials ◽  
Computational Modelling ◽  
Forward Transfer

scholarly journals Highly resolved, on-demand LIFT of graphene and 2D materials and computational modelling of transfer enabling conditions (Conference Presentation)

2020 ◽  
Author(s):  
Mado Logotheti ◽  
Symeon Papazoglou ◽  
Dimitris Kaltsas ◽  
Filimon Zacharatos ◽  
Leonidas Tsetseris ◽  
...  
Keyword(s):  
2D Materials ◽  
Computational Modelling ◽  
On Demand

Schottky diodes based on 2D materials for environmental gas monitoring: a review on emerging trends, recent developments and future perspectives

2021 ◽  
Author(s):  
Minu Mathew ◽  
Chandra Sekhar Rout
Keyword(s):  
Gas Sensing ◽  
2D Materials ◽  
Schottky Diodes ◽  
High Sensitivity ◽  
Future Perspectives ◽  
Working Temperature ◽  
Emerging Trends ◽  
Gas Sensing Properties ◽  
Recent Developments ◽  
Sensitivity And Selectivity

This review details the fundamentals, working principles and recent developments of Schottky junctions based on 2D materials to emphasize their improved gas sensing properties including low working temperature, high sensitivity, and selectivity.

Nanoscopy of 2D materials

2020 ◽  
Author(s):  
Aleksandra Radenovic
Keyword(s):  
2D Materials

Thermally-Induced Dehydrogenative Coupling of Organosilanes and H-Terminated Silicon Quantum Dots onto Germanane Surfaces

2020 ◽  
Author(s):  
Haoyang Yu ◽  
Alyxandra Thiessen ◽  
Md Asjad Hossain ◽  
Marc Julian Kloberg ◽  
Bernhard Rieger ◽  
...  
Keyword(s):  
2D Materials ◽  
Future Generation ◽  
Optical Devices ◽  
Surface Reactivity ◽  
Organic Monolayers ◽  
Present Contribution ◽  
Thermally Induced ◽  
Dehydrogenative Coupling ◽  
Silicon Quantum Dot ◽  
Covalently Bonded

<div><div><div><p>Covalently bonded organic monolayers play important roles in defining the solution processability, ambient stability, and electronic properties of two-dimensional (2D) materials such as Ge nanosheets (GeNSs); they also hold promise of providing avenues for the fabrication of future generation electronic and optical devices. Functionalization of GeNS normally involves surface moieties linked through covalent Ge−C bonds. In the present contribution we extend the scope of surface linkages to include Si−Ge bonding and present the first demonstration of heteronuclear dehydrocoupling of organosilanes to hydride-terminated GeNSs obtained from the deintercalation and exfoliation of CaGe2. We further exploit this new surface reactivity and demonstrated the preparation of directly bonded silicon quantum dot-Ge nanosheet hybrids.</p></div></div></div>

SAMPL7 TrimerTrip Host-Guest Binding Poses and Binding Affinities from Spherical-Coordinates-Biased Simulations

2020 ◽  
Author(s):  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Computational Modelling ◽  
Free Energy Calculations ◽  
Energy Estimates ◽  
Binding Affinities ◽  
Spherical Coordinates ◽  
Collective Variables ◽  
Guest Binding ◽  
Starting Point ◽  
Sampl Challenge

Host-guest binding remains a major challenge in modern computational modelling. The newest 7<sup>th</sup> statistical assessment of the modeling of proteins and ligands (SAMPL) challenge contains a new series of host-guest systems. The TrimerTrip host binds to 16 structurally diverse guests. Previously, we have successfully employed the spherical coordinates as the collective variables coupled with the enhanced sampling technique metadynamics to enhance the sampling of the binding/unbinding event, search for possible binding poses and predict the binding affinities in all three host-guest binding cases of the 6<sup>th</sup> SAMPL challenge. In this work, we employed the same protocol to investigate the TrimerTrip host in the SAMPL7 challenge. As no binding pose is provided by the SAMPL7 host, our simulations initiate from randomly selected configurations and are proceeded long enough to obtain converged free energy estimates and search for possible binding poses. The predicted binding affinities are in good agreement with the experimental reference, and the obtained binding poses serve as a nice starting point for end-point or alchemical free energy calculations.

Co-planar two-dimensional Metal-Insulator-Semiconductor Capacitor: Numerical study of the device electrostatics.

2017 ◽  
Author(s):  
Varun Bheemireddy
Keyword(s):  
Space Charge ◽  
High Performance ◽  
Numerical Study ◽  
2D Materials ◽  
Space Charge Density ◽  
Two Dimensional ◽  
Short Channel ◽  
Metal Insulator ◽  
Metal Insulator Semiconductor ◽  
New Family

The two-dimensional(2D) materials are highly promising candidates to realise elegant and e cient transistor. In the present letter, we conjecture a novel co-planar metal-insulator-semiconductor(MIS) device(capacitor) completely based on lateral 2D materials architecture and perform numerical study of the capacitor with a particular emphasis on its di erences with the conventional 3D MIS electrostatics. The space-charge density features a long charge-tail extending into the bulk of the semiconductor as opposed to the rapid decay in 3D capacitor. Equivalently, total space-charge and semiconductor capacitance densities are atleast an order of magnitude more in 2D semiconductor. In contrast to the bulk capacitor, expansion of maximum depletion width in 2D semiconductor is observed with increasing doping concentration due to lower electrostatic screening. The heuristic approach of performance analysis(2D vs 3D) for digital-logic transistor suggest higher ON-OFF current ratio in the long-channel limit even without third dimension and considerable room to maximise the performance of short-channel transistor. The present results could potentially trigger the exploration of new family of co-planar at transistors that could play a signi significant role in the future low-power and/or high performance electronics.<br>

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning

2018 ◽  
Author(s):  
Sherif Tawfik ◽  
Olexandr Isayev ◽  
Catherine Stampfl ◽  
Joseph Shapter ◽  
David Winkler ◽  
...  
Keyword(s):  
Machine Learning ◽  
Band Gap ◽  
Density Functional ◽  
2D Materials ◽  
Van Der Waals ◽  
Building Blocks ◽  
Machine Learning Techniques ◽  
Interlayer Distance ◽  
Computational Screening ◽  
Wide Range

Materials constructed from different van der Waals two-dimensional (2D) heterostructures offer a wide range of benefits, but these systems have been little studied because of their experimental and computational complextiy, and because of the very large number of possible combinations of 2D building blocks. The simulation of the interface between two different 2D materials is computationally challenging due to the lattice mismatch problem, which sometimes necessitates the creation of very large simulation cells for performing density-functional theory (DFT) calculations. Here we use a combination of DFT, linear regression and machine learning techniques in order to rapidly determine the interlayer distance between two different 2D heterostructures that are stacked in a bilayer heterostructure, as well as the band gap of the bilayer. Our work provides an excellent proof of concept by quickly and accurately predicting a structural property (the interlayer distance) and an electronic property (the band gap) for a large number of hybrid 2D materials. This work paves the way for rapid computational screening of the vast parameter space of van der Waals heterostructures to identify new hybrid materials with useful and interesting properties.

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