Machine learning of organic solvents reveals an extraordinary axis in Hansen space as indicator of spherical precipitation of polymers

Machine learning is an emerging tool in the field of materials chemistry for uncovering a principle from large datasets.Here,we focus on the spherical precipitation behavior of polymers and computationally extract a hidden trend that is orthogonal to the availability bias in the chemical space.For constructing a dataset,four polymers were precipitated from 416 solvent/nonsolvent combinations,and the morphology of the resulting precipitates were collected.The dataset was subjected to computational investigations consisting of principal component analysis and machine learning based on random forest model and support vector machine.Thereby,we eliminated the effect of the availability bias and found a linear combination of Hansen parameters to be the most suitable variable for predicting precipitation behavior.The predicted appropriate solvents are those with low hydrogen bonding capability,low polarity,and small molecular volume.Furthermore,we found that the capability for spherical precipitation is orthogonal to the availability bias and forms an extraordinary axis in Hansen space,which is the origin of the conventional difficulty in identifying the trend.The extraordinary axis points toward a void region,indicating the potential value of synthesizing novel solvents located therein.

Evaluation and Optimization of Electrode Configuration of Multi-Channel Corona Discharge Plasma for Dye-Containing Wastewater Treatment

A discharge plasma reactor with a point-to-plane structure was widely studied experimentally in wastewater treatment.In order to improve the utilization efficiency of active species and the energy efficiency of this kind of discharge plasma reactor during wastewater treatment,the electrode configuration of the point-to-plane corona discharge reactor was studied by evaluating the effects of discharge spacing and adjacent point distance on discharge power and discharge energy density,and then dye-containing wastewater decoloration experiments were conducted on the basis of the optimum electrode configuration.The experimental results of the discharge characteristics showed that high discharge power and discharge energy density were achieved when the ratio of discharge spacing to adjacent point distance（d/s） was 0.5.Reactive Brilliant Blue（RBB） wastewater treatment experiments presented that the highest RBB decoloration efficiency was observed at d/s of 0.5,which was consistent with the result obtained in the discharge characteristics experiments.In addition,the biodegradability of RBB wastewater was enhanced greatly after discharge plasma treatment under the optimum electrode configuration.RBB degradation processes were analyzed by GC-MS and IC,and the possible mechanism for RBB decoloration was also discussed.

Computational Pharmacology Study of Tougu Xiaotong Granule(透骨消痛颗粒) in Preventing and Treating Knee Osteoarthritis

Objective： To study the pharmacological properties of Tougu Xiaotong Granule （透骨消痛颗粒, TGXTG） in preventing and treating knee osteoarthritis （KOA） at the molecular level. Methods： The computational methods, including principal component analysis, molecular docking, target-ligand space distribution, and the predictions of absorption, distribution, metabolism, excretion and toxicity （ADMET）, were introduced to characterize the molecules in TGXTG. Results： The structural properties of molecules in TGXTG were more diverse than those of the drug/drug-like molecules, and TGXTG could interact with significant target enzymes related to KOA. In addition, the cluster of effective components was preliminarily identified by the target-ligand space distributions. As to the results of ADMET properties, some of them were unsatisfactory, and were merely regarded as references here. Conclusion： Based on this computational pharmacology study, TGXTG is a broad- spectrum recipe inhibiting many important target enzymes, which could effectively postpone the degeneration of cartilage by coordinately inhibiting the biological effects of cytokines, matrix metallopeptidase 3, and oxygen free radicals.

Potential Synergistic and Multitarget Effect of Herbal Pair Chuanxiong Rhizome-Paeonia Albifora Pall on Osteoarthritis Disease:A Computational Pharmacology Approach

Objective：To study the polypharmacological mechanism of herbal pair Chuanxiong Rhizome-Paeonia Albifora Pall（HP CXR-PAP） on the treatment for osteoarthritis（OA）.Methods：Chemical space was used to discuss the similarities and differences between the molecule sets of HP CXR-PAP and drugs.Docking protocol was used to study the interaction between HP CXR-PAP and OA target enzymes.The similarities and differences of HP CXR-PAP and drugs in target spaces were elucidated by network features.Results：The plots between the molecule sets of HP CXR-PAP and drugs in chemical space had the majority in the same region, and compounds from HP CXR-PAP covered a much larger additional region of space than drug molecules, which denoted the diverse structural properties in the molecule set of HP CXR-PAP.The molecules in HP CXR-PAP had the properties of promiscuous drugs and combination drug,and both HP CXR-PAP ligand-target interaction network and drug ligand-target interaction network were similar in the interaction profiles and network features,which revealed the effects of multicomponent and multitarget.Conclusion：The clue of potential synergism was obtained in curing OA disease by Chinese medicine,which revealed the advantages of Chinese medicine for targeting osteoarthritis disease.

Phase-pure two-dimensional Fe_(X)GeTe_(2) magnets with near-room-temperature Tc

Two-dimensional(2D)ferromagnets with out-of-plane(OOP)magnetic anisotropy are potential candidates for realizing the next-generation memory devices with ultra-low power consumption and high storage density.However,a scalable approach to synthesize 2D magnets with OOP anisotropy directly on the complimentary metal-oxide semiconductor(CMOS)compatible substrates has not yet been mainly explored,which hinders the practical application of 2D magnets.This work demonstrates a cascaded space confined chemical vapor deposition(CS-CVD)technique to synthesize 2D FexGeTe_(2) ferromagnets.The weight fraction of iron(Fe)in the precursor controls the phase purity of the as-grown FexGeTe2.As a result,high-quality Fe_(3)GeTe_(2) and Fe_(5)GeTe_(2) flakes have been grown selectively using the CS-CVD technique.Curie temperature(Tc)of the as-grown FexGeTe2 can be up to-280 K,nearly room temperature.The thickness and temperature-dependent magnetic studies on the Fe_(5)GeTe_(2) reveal a 2D Ising to 3D XY behavior.Also,Terahertz spectroscopy experiments on Fe_(5)GeTe_(2) display the highest conductivity among other FexGeTe_(2) 2D magnets.The results of this work indicate a scalable pathway for the direct growth and integration of 2D ternary magnets on CMOS-based substrates to develop spintronic memory devices.