AisNet: A Universal Interatomic Potential Neural Network with Encoded Local Environment Features.

This paper proposes a new interatomic potential energy neural network, AisNet, which can efficiently predict atomic energies and forces covering different molecular and crystalline materials by encoding universal local environment features, such as elements and atomic positions. Inspired by the framework of SchNet, AisNet consists of an encoding module combining autoencoder with embedding, the triplet loss function and an atomic central symmetry function (ACSF), an interaction module with a periodic boundary condition (PBC), and a prediction module. In molecules, the prediction accuracy of AisNet is comparabel with SchNet on the MD17 dataset, mainly attributed to the effective capture of chemical functional groups through the interaction module. In selected metal and ceramic material datasets, the introduction of ACSF improves the overall accuracy of AisNet by an average of 16.8% for energy and 28.6% for force. Furthermore, a close relationship is found between the feature ratio (i.e., ACSF and embedding) and the force prediction errors, exhibiting similar spoon-shaped curves in the datasets of Cu and HfO2. AisNet produces highly accurate predictions in single-commponent alloys with little data, suggesting the encoding process reduces dependence on the number and richness of datasets. Especially for force prediction, AisNet exceeds SchNet by 19.8% for Al and even 81.2% higher than DeepMD on a ternary FeCrAl alloy. Capable of processing multivariate features, our model is likely to be applied to a wider range of material systems by incorporating more atomic descriptions.

PEG-interspersed nitrilotriacetic acid-functionalized quantum dots for site-specific labeling of prion proteins expressed on cell surfaces.

A strategy has been put forward to fabricate PEG-interspersed nitrilotriacetic acid (NTA)-functionalized QDs by one-step self-assembly using a mixture of self-synthesized NTA-terminated amphiphilic polymer and 1,2-Distearoyl-sn-Glycero-3-Phosphoethanolamine-N-[Carboxy(Polyethylene Glycol)2000] (DSPE-PEG-COOH). The process was highly reproducible for facile functionalization of QDs via simultaneous self-assembly of biocompatible PEG molecules onto their surface. An optimized molar ratio of NTA-terminated amphiphilic polymer to DSPE-PEG-COOH was used to obtain NTA-functionalized QDs for site-specific labeling of prion proteins (PrP(C)) expressed on cell surfaces. Fabricated NTA-functionalized QDs can be a good candidate used for real-time visualization of PrP(C) in single live cells so as to clarify the nosogenesis of pathogenic scrapie prion protein (PrP(Sc)).