Laser damage threshold (LDT) has been considered as a key index, apart from the nonlinear optical (NLO) effect, to characterize the performance of a mid-infrared NLO material. This paper reports and compares the properties of RbIO3 and RbIO2F2 as potential nonlinear optical (NLO) materials to be used in the mid-IR region. RbIO3 is a known compound, and its powder SHG (second harmonic generation) effect is carefully measured in this work for the first time to be as strong as 20 times that of KDP, and its powders show a high damage threshold (LDT) of 125 MW/cm2. In order to investigate the influence on the properties by partially replacing oxygen with fluorine atoms, the new compound RbIO2F2 is synthesized and characterized. Although it also shows relatively strong powder SHG responses 4 times that of KDP, the LDT value of the powders is improved to 156 MW/cm2. The transparent region and the thermal stability of two compounds are also measured with satisfactory results. The electronic structure and the properties of the materials are also investigated by the theoretical approach. All these indicate that RbIO3 and RbIO2F2 are both promising candidates for NLO materials to be used in the mid-IR region and that partially replacing oxygen with fluorine in the molecule can improve the laser damage threshold of the material.

A family of nonlinear optical materials that contain the halide, oxide, and oxyhalide polar units simultaneously in a single structure, namely ABi (IO ) F (A=K (1), Rb (2), and Cs (3)), have been designed and synthesized. They crystallize in the same polar space group (P2 ) with a two-dimensional double-layered framework constructed by [BiF ] and [BiO F ] units connected to each other by four F atoms, in which two [IO ] groups are linked to [BiO F ] unit on the same side. A hanging Bi-F bond of [BiF ] unit is located on the other side via ionic interaction with the layer-inserted alkali metal ions to form three-dimensional structure. The well-ordered alignments of these polar units lead to a very strong second-harmonic generation response of 12 (1), 9.5 (2), and 7.5 (3) times larger than that of potassium dihydrogen phosphate under 1064 nm laser radiation. All of them exhibited a wide energy bandgap over 3.75 eV, suggesting that they will have a high laser damage threshold.

Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67–0.76)] and validation cohorts [0.73 (0.63–0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

We demonstrate a novel synthetic approach to ortho-methyl substituted tetraphenylethene materials, which can be utilised for directly validating the restriction of intramolecular rotation hypothesis as the basic mechanism of aggregation-induced emission phenomenon and cell imaging.

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