Identification of amino acids with sensitive nanoporous MoS<sub>2</sub>: towards machine learning-based prediction

2018-05-29T12:50:05+00:00May 29th, 2018|Categories: Publications|Tags: |

Identification of amino acids with sensitive nanoporous MoS2: towards machine learning-based predictionIdentification of amino acids with sensitive nanoporous MoS<sub>2</sub>: towards machine learning-based prediction, Published online: 24 May 2018; doi:10.1038/s41699-018-0060-8Molecular dynamics simulations combined with machine learning techniques enable the prediction of MoS2 nanopore sequencing capabilities. A team led by N. R. Aluru at the University of Illinois at Urbana-Champaign used logistic regression, nearest neighbor, and random forest classifiers to develop a machine learning-based platform capable of predicting the sensing capabilities of nanoporous, atomically thin MoS2. The material was shown to be able to identify individual amino acids in polypeptide chains with high accuracy and distinguishability. Twenty amino acids could be detected and categorized in different classes based on current-residence time training data, with an accuracy of up to 99.6%. These results show promise for the development of amino acid detection platforms with atomically thin materials assisted by machine learning.

Published in: "NPJ 2D Materials and Applications".

Tunable phase stability and contact resistance of monolayer transition metal dichalcogenides contacts with metal

2018-05-16T09:09:01+00:00May 16th, 2018|Categories: Publications|

Tunable phase stability and contact resistance of monolayer transition metal dichalcogenides contacts with metalTunable phase stability and contact resistance of monolayer transition metal dichalcogenides contacts with metal, Published online: 14 May 2018; doi:10.1038/s41699-018-0059-1Interfacial charge calculations enable the prediction of the contact resistance behaviour of MX2/metal structures. A team led by Bin Ouyang at the University of California Berkeley performed a systematic theoretical investigation of the interplay between interface interactions and phase stability in atomically thin MX2/metal systems, where M is a transition metal and X is a chalcogenide. A combination of interfacial charge calculations and contact resistance analysis allowed the identification of twenty-eight MX2/metal structures that can be further categorised in three groups according to their contact nature. Notably, the first type of contact possesses zero tunnel barrier between MX2 and the metal, whereas the second type enables substantial charge transfer accompanied to a 2H-to-1T’ structural phase transition in MX2. These results highlight viable design routes for contact resistance manipulation in MX2 transistors.

Published in: "NPJ 2D Materials and Applications".

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