Field-effect at electrical contacts to two-dimensional materials (preprint)

The inferior electrical contact to two-dimensional (2D) materials is a critical challenge for their application in post-silicon very large-scale integrated circuits. Electrical contacts were generally related to their resistive effect, quantified as contact resistance. With a systematic investigation, this work demonstrates a capacitive metal-insulator-semiconductor (MIS) field-effect at the electrical contacts to 2D materials: the field-effect depletes or accumulates charge carriers, redistributes the voltage potential, and give rise to abnormal current saturation and nonlinearity. On the one hand, the current saturation hinders the devices' driving ability, which can be eliminated with carefully engineered contact configurations. On the other hand, by introducing the nonlinearity to monolithic analog artificial neural network circuits, the circuits' perception ability can be significantly enhanced, as evidenced using a COVID-19 critical illness prediction model. This work provides a comprehension of the field-effect at the electrical contacts to 2D materials, which is fundamental to the design, simulation, and fabrication of electronics based on 2D material.

A framework for predicting potential host ranges of pathogenic viruses based on receptor ortholog analysis (preprint)

Viral zoonoses are a serious threat to public health and global security, as reflected by the current scenario of the growing number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases. However, as pathogenic viruses are highly diverse, identification of their host ranges remains a major challenge. Here, we present a combined computational and experimental framework, called REceptor ortholog-based POtential virus hoST prediction (REPOST), for the prediction of potential virus hosts. REPOST first selects orthologs from a diverse species by identity and phylogenetic analyses. Secondly, these orthologs is classified preliminarily as permissive or non-permissive type by infection experiments. Then, key residues are identified by comparing permissive and non-permissive orthologs. Finally, potential virus hosts are predicted by a key residue-specific weighted module. We performed REPOST on SARS-CoV-2 by studying angiotensin-converting enzyme 2 orthologs from 287 vertebrate animals. REPOST efficiently narrowed the range of potential virus host species (with 95.74% accuracy).