HfO2-based binary lead-free ferroelectrics show promising properties for non-volatile memory applications, providing that their polarization reversal behavior is fully understood. In this work, temperature-dependent polarization hysteresis measured over a wide applied field range has been investigated for Si-doped HfO2 ferroelectric thin films. Our study indicates that in the low and medium electric field regimes (E < twofold coercive field, 2E(c)), the reversal process is dominated by the thermal activation on domain wall motion and domain nucleation; while in the high-field regime (E > 2E(c)), a non-equilibrium nucleation-limited-switching mechanism dominates the reversal process. The optimum field for ferroelectric random access memory (FeRAM) applications was determined to be around 2.0 MV/cm, which translates into a 2.0 V potential applied across the 10 nm thick films

The inert gases Xe and Kr mainly exist in the used nuclear fuel (UNF) with the Xe/Kr ratio of 20:80, which it is difficult to separate. In this work, based on the G-MOFs database, high-throughput computational screening for metal–organic frameworks (MOFs) with high Xe/Kr adsorption selectivity was performed by combining grand canonical Monte Carlo (GCMC) simulations and machine learning (ML) technique for the first time. From the comparison of eight classical ML models, it is found that the XGBoost model with seven structural descriptors has superior accuracy in predicting the adsorption and separation performance of MOFs to Xe/Kr. Compared with energetic or electronic descriptors, structural descriptors are easier to obtain. Note that the determination coefficients R 2 of the generalized model for the Xe adsorption and Xe/Kr selectivity are very close to 1, at 0.951 and 0.973, respectively. In addition, 888 and 896 MOFs have been successfully predicted by the XGBoost model among the top 1000 MOFs in adsorption capacity and selectivity by GCMC simulation, respectively. According to the feature engineering of the XGBoost model, it is shown that the density (ρ), porosity (ϕ), pore volume (Vol), and pore limiting diameter (PLD) of MOFs are the key features that affect the Xe/Kr adsorption property. To test the generalization ability of the XGBoost model, we also tried to screen MOF adsorbents on the CO 2 /CH 4 mixture, it is found that the prediction performance of XGBoost is also much better than that of the traditional machine learning models although with the unbalanced data. Note that the dimension of features of MOFs is low while the quantity of MOF samples in database is very large, which is suitable for the prediction by model such as XGBoost to search the global minimum of cost function rather than the model involving feature creation. The present study represents the first report using the XGBoost algorithm to discover the MOF adsorbates.

Grace Xingxin Gao (M'12) received the B.S. degree in mechanical engineering and the M.S. degree in electrical engineering

T follicular helper (Tfh) cells and T follicular regulatory (Tfr) cells are identified as the new subset of immune cells. This study aims to investigate the role of circulating Tfh cells (cTfh) and Tfr (cTfr) cells in the pathogenesis of non-small cell lung cancer (NSCLC). A total of 27 NSCLC patients and 19 age and sex-matched healthy controls were enrolled. The percentage of cTfh and cTfr was detected by flow cytometric analysis. Compared to healthy controls, a significantly higher percentage of both cTfh and cTfr cells were observed in NSCLC patients (for cTfh, 18.88% ± 16.84% versus 5.98% ± 3.70%, P < 0.01; for cTfr, 2.67% ± 2.20% versus 1.14% ± 0.76%, P < 0.01). Furthermore, there was a positive correlation between cTfh/cTfr ratio and age in NSCLC patients (P < 0.05). When taking age 60 as a cut-off, the percentage of both cTfh cells and cTfr cells were higher in older patients than younger patients. Moreover, our data showed there was lower percentage of cTfh cells in NSCLC patients with early stage disease (I and II) (12.10% ± 12.22%) than that in advanced stage disease (III and IV) (30.41% ± 17.87%) (P < 0.01). However, no significant relationship was observed between cTfr cells and clinical stage in NSCLC patients. A higher percentage of cTfh cells was observed in patients with squamous cell carcinoma compared with adenocarcinoma (31.70% ± 20.73% versus. 13.48% ± 11.78%, P < 0.05). Taken together, there was significantly higher percentage of cTfh and cTfr cells in NSCLC patients. cTfh and cTfr cells might play an important role in the pathogenesis of NSCLC patients.

No abstract