Compact beam expander based on planar structure to avoid inner focus

Optical Review - Based on the planar optical theory, compact beam expanders are proposed to miniaturize the dimension of an optical system. Both simulated and experimental results have demonstrated...     

Synthesis of aqueous dispersion of graphenes via reduction of graphite oxide in the solution of conductive polymer

Graphene sheets were produced by chemical reduction of graphite oxides in the solution of ionic conductive polymer, Nafion. The obtained graphene, coated with Nafion, can be re-dispersed in water, and readily forms stable dispersed state. The polymer-coated graphene had been characterized by FT-IR spectroscopy, UV-vis and X-ray photoelectron spectroscopy (XPS). The PEDOT film with Nafion-coated graphene increased significantly from 0.25 S/cm for pure PEDOT film and reached 12 S/cm. Further, the films of PEDOT doped Nafion-coated graphene had also higher conductivities compared to films doped PSS-coated graphene.     

Energy deposition model for I-125 photon radiation in water

In this study, an electron-tracking Monte Carlo algorithm developed by us is combined with established photon transport models in order to simulate all primary and secondary particle interactions in water for incident photon radiation. As input parameters for secondary electron interactions, electron scattering cross sections by water molecules and experimental energy loss spectra are used. With this simulation, the resulting energy deposition can be modelled at the molecular level, yielding detailed information about localization and type of single collision events. The experimental emission spectrum of I-125 seeds, as used for radiotherapy of different tumours, was used for studying the energy deposition in water when irradiating with this radionuclide.     

Circumventing the OCl versus OOH scaling relation in the chlorine evolution reaction: Beyond dimensionally stable anodes

The development of selective electrocatalysts for the chlorine evolution reaction (CER) is majorly restrained by a scaling relation between the OCl and OOH adsorbates, rendering that active CER catalysts are also reasonably active in the competing oxygen evolution reaction (OER). While theory predicts that the OCl versus OOH scaling relation can be circumvented as soon as the elementary reaction steps in the CER comprise the Cl rather than the OCl adsorbate, it was demonstrated recently that PtN₄ sites embedded in a carbon nanotube follow this theoretical prediction. Advanced experimental analyses illustrate that the PtN₄ sites also reveal a different reaction kinetics compared to the industrial benchmark of dimensionally stable anodes (DSA). A reverse Volmer–Heyrovsky mechanism was identified, in which the rate-determining Volmer step for small overpotentials is followed by the kinetically limiting Heyrovsky step for larger overpotentials. Since the PtN₄ sites excel DSA in terms of activity and chlorine selectivity, we suggest the Cl intermediate as well as the reverse Volmer–Heyrovsky mechanism as the design criteria for the development of next-generation electrode materials beyond DSA.     

Systematic Modulation of Thiol Functionalities in Inexpensive Porous Polymers for Effective Mercury Removal

Through accumulation, mercury contamination in aquatic systems still poses serious health risks despite the strict regulations on drinking water and industrial discharge. One effective strategy against this is adsorptive removal, in which a suitably functionalized porous material is added to water treatment protocols. Thiol (SH) group-grafted structures perform commendably; however, insufficient attention is paid to the cost, scalability, and reusability or how the arrangement of sulfur atoms could affect the Hg^II binding strength. We used an inexpensive and scalable porous covalent organic polymer (COP-130) to systematically introduce thiol functional groups with precise chain lengths and sulfur content. Thiol-functionalized COP-130 demonstrates enhanced wettability and excellent Hg^II uptake of up to 936 mg g⁻¹, with fast kinetics and exceptionally high selectivity. These Hg adsorbents are easily regenerated with HCl and can be used at least six times without loss of capacity even after treatment with strong acid, a rare performance in the domain of Hg-removal research.     

Drug-likeness scoring based on unsupervised learning

Drug-likeness prediction is important for the virtual screening of drug candidates. It is challenging because the drug-likeness is presumably associated with the whole set of necessary properties to pass through clinical trials, and thus no definite data for regression is available. Recently, binary classification models based on graph neural networks have been proposed but with strong dependency of their performances on the choice of the negative set for training. Here we propose a novel unsupervised learning model that requires only known drugs for training. We adopted a language model based on a recurrent neural network for unsupervised learning. It showed relatively consistent performance across different datasets, unlike such classification models. In addition, the unsupervised learning model provides drug-likeness scores that well separate distributions with increasing mean values in the order of datasets composed of molecules at a later step in a drug development process, whereas the classification model predicted a polarized distribution with two extreme values for all datasets presumably due to the overconfident prediction for unseen data. Thus, this new concept offers a pragmatic tool for drug-likeness scoring and further can be applied to other biochemical applications.

A new quantification method of drug-likeness based on unsupervised learning. The method only uses drug molecules as training set without any non-drug-like molecules.