Topological Data Analysis Combined with High-Throughput Computational Screening of Hydrophobic Metal-Organic Frameworks: Application to the Adsorptive Separation of C3 Components.

The shape and topology of pores have significant impacts on the gas storage properties of nanoporous materials. Metal-organic frameworks (MOFs) are ideal materials with which to tailor to the needs of specific applications, due to properties such as their tunable structure and high specific surface area. It is, therefore, particularly important to develop descriptors that accurately identify the topological features of MOF pores. In this work, a topological data analysis method was used to develop a topological descriptor, based on the pore topology, which was combined with the Extreme Gradient Boosting (XGBoost) algorithm to predict the adsorption performance of MOFs for methane/ethane/propane. The final results show that this descriptor can accurately predict the performance of MOFs, and the introduction of the topological descriptor also significantly improves the accuracy of the model, resulting in an increase of up to 17.55% in the R2 value of the model and a decrease of up to 46.1% in the RMSE, compared to commonly used models that are based on the structural descriptor. The results of this study contribute to a deeper understanding of the relationship between the performance and structure of MOFs and provide useful guidelines and strategies for the design of high-performance separation materials.

Deep learning and big data mining for Metal-Organic frameworks with high performance for simultaneous desulfurization and carbon capture.

Carbon capture and desulfurization of flue gases are crucial for the achievement of carbon neutrality and sustainable development. In this work, the "one-step" adsorption technology with high-performance metal-organic frameworks (MOFs) was proposed to simultaneously capture the SO2 and CO2. Four machine learning algorithms were used to predict the performance indicators (NCO2+SO2, SCO2+SO2/N2, and TSN) of MOFs, with Multi-Layer Perceptron Regression (MLPR) showing better performance (R2 = 0.93). To address sparse data of MOF chemical descriptors, we introduced the Deep Factorization Machines (DeepFM) model, outperforming MLPR with a higher R2 of 0.95. Then, sensitivity analysis was employed to find that the adsorption heat and porosity were the key factors for SO2 and CO2 capture performance of MOF, while the influence of open alkali metal sites also stood out. Furthermore, we established a kinetic model to batch simulate the breakthrough curves of TOP 1000 MOFs to investigate their dynamic adsorption separation performance for SO2/CO2/N2. The TOP 20 MOFs screened by the dynamic performance highly overlap with those screened by the static performance, with 76 % containing open alkali metal sites. This integrated approach of computational screening, machine learning, and dynamic analysis significantly advances the development of efficient MOF adsorbents for flue gas treatment.

High-timing-precision detection of single X-ray photons by superconducting nanowires.

Precisely acquiring the timing information of individual X-ray photons is important in both fundamental research and practical applications. The timing precision of commonly used X-ray single-photon detectors remains in the range of one hundred picoseconds to microseconds. In this work, we report on high-timing-precision detection of single X-ray photons through the fast transition to the normal state from the superconductive state of superconducting nanowires. We successfully demonstrate a free-running X-ray single-photon detector with a timing resolution of 20.1 ps made of 100-nm-thick niobium nitride film with an active area of 50 µm by 50 µm. By using a repeated differential timing measurement on two adjacent X-ray single-photon detectors, we demonstrate a precision of 0.87 ps in the arrival-time difference of X-ray photon measurements. Therefore, our work significantly enhances the timing precision in X-ray photon counting, opening a new niche for ultrafast X-ray photonics and many associated applications.

van der Waals Self-Epitaxial Growth of Inch-Sized Superconducting Niobium Diselenide Films.

Ultrathin superconducting films are the basis of superconductor devices. van der Waals (vdW) NbSe2 with noncentrosymmetry exhibits exotic superconductivity and shows promise in superconductor electronic devices. However, the growth of inch-scale NbSe2 films with layer regulation remains a challenge because vdW structural material growth is strongly dependent on the epitaxial guidance of the substrate. Herein, a vdW self-epitaxy strategy is developed to eliminate the substrate driving force in film growth and realize inch-sized NbSe2 film growth with thicknesses from 2.1 to 12.1 nm on arbitrary substrates. The superconducting transition temperature of 5.1 K and superconducting transition width of 0.30 K prove the top homogeneity and quality of superconductivity among all of the synthetic NbSe2 films. Coupled with a large area and substrate compatibility, this work paves the way for developing NbSe2 superconductor electronics.

Interpretable Machine-Learning and Big Data Mining to Predict Gas Diffusivity in Metal-Organic Frameworks.

For gas separation and catalysis by metal-organic frameworks (MOFs), gas diffusion has a substantial impact on the process' overall rate, so it is necessary to determine the molecular diffusion behavior within the MOFs. In this study, an interpretable machine learing (ML) model, light gradient boosting machine (LGBM), is trained to predict the molecular diffusivity and selectivity of 9 gases (Kr, Xe, CH4 , N2 , H2 S, O2 , CO2 , H2 , and He). For these 9 gases, LGBM displays high accuracy (average R2 = 0.962) and superior extrapolation for the diffusivity of C2 H6 . And this model calculation is five orders of magnitude faster than molecular dynamics (MD) simulations. Subsequently, using the trained LGBM model, an interactive desktop application is developed that can help researchers quickly and accurately calculate the diffusion of molecules in porous crystal materials. Finally, the authors find the difference in the molecular polarizability (ΔPol) is the key factor governing the diffusion selectivity by combining the trained LGBM model with the Shapley additive explanation (SHAP). By the calculation of interpretable ML, the optimal MOFs are selected for separating binary gas mixtures and CO2 methanation. This work provides a new direction for exploring the structure-property relationships of MOFs and realizing the rapid calculation of molecular diffusivity.

Highly dispersed Ag and g-C3N4 quantum dots co-decorated 3D hierarchical Fe3O4 hollow microspheres for solar-light-driven pharmaceutical pollutants degradation in natural water matrix.

The efficient removal of pharmaceutical pollutants presents a great challenge for the conventional sewage treatment system. Herein, we document the nanosheets assembled 3D hierarchical Fe3O4 hollow microspheres co-modified by Ag and g-C3N4 quantum dots (Ag/CNQDs@Fe3O4) for efficient degradation of two classic anticancer drugs, i.e., capecitabine (CAP) and 5-fluorouracil (5-FLU) under visible light in 1 h. Benefiting from the unique hierarchically hollow structure, the intrinsic strengths of each component and their interactions, synergistic reinforcing mechanism is constructed, furnishing more accessible reactive places, promoting the diffusion of pollutants/oxidants, improving charge separation ability, and raising light utilization rate. Consequently, Ag/CNQDs@Fe3O4 can not only show superior photocatalytic properties, but also greatly boost PMS activation to yield sufficient oxidative radicals. More notably, the studied system also features excellent stability and strong tolerance to real water samples, and maintains appreciable performance even under natural sunlight illumination. The predominant active species, possible ADs decomposition pathways, and underlying reaction mechanism for the Ag/CNQDs@Fe3O4/PMS/vis system are thoroughly explored. This work presents significant advancement in enabling an integrated technology of PMS and photocatalysis to realize its great potential in environment restoration.

Single-Detector Spectrometer Using a Superconducting Nanowire.

Designing a spectrometer without the need for wavelength multiplexing optics can effectively reduce the complexity and physical footprint. On the basis of the computational spectroscopic strategy and combining a broadband-responsive dynamic detector, we successfully demonstrate an optics-free single-detector spectrometer that maps the tunable quantum efficiency of a superconducting nanowire into a matrix to build a solvable mathematical equation. Such a spectrometer can realize a broadband spectral responsivity ranging from 660 to 1900 nm. The spectral resolution at the telecom is sub-10 nm, exceeding the energy resolving capacity of existing infrared single-photon detectors. Meanwhile, benefiting from the optics-free setup, precise time-of-flight measurements can be simultaneously achieved. We have demonstrated a spectral LiDAR with eight spectral channels. This spectrometer scheme paves the way for applying superconducting nanowire detectors in multifunctional spectroscopy and represents a conceptual advancement for on-chip spectroscopy and spectral imaging.

Fabrication of superconducting niobium nitride nanowire with high aspect ratio for X-ray photon detection.

The niobium nitride (NbN) nanowires fabricated with the high-quality ultra-thin NbN film with a thickness of 3 nm-6 nm were widely used for single photon detectors. These nanowires had a low aspect ratio, less than 1:20. However, increasing the thickness and the aspect ratio of highly-uniformed NbN nanowires without reducing the superconductivity is crucial for the device in detecting high-energy photons. In this paper, a high-quality superconducting nanowire with aspect ratio of 1:1 was fabricated with optimized process, which produced a superconducting critical current of 550 µA and a hysteresis of 36 µA at 2.2 K. With the optimization of the electron beam lithography process of AR-P6200.13 and the adjustion of the chamber pressure, the discharge power, as well as the auxiliary gas in the process of reactive ion etching (RIE), the meandered NbN nanowire structure with the minimum width of 80 nm, the duty cycle of 1:1 and the depth of 100 nm were finally obtained on the silicon nitride substrate. Simultaneously, the sidewall of nanowire was vertical and smooth, and the corresponding depth-width ratio was more than 1:1. The fabricated NbN nanowire will be applied to the detection of soft X-ray photon emitted from pulsars with a sub-10 ps time resolution.

Unveiling the piezoelectric nature of polar α-phase P(VDF-TrFE) at quasi-two-dimensional limit.

Piezoelectric response of P(VDF-TrFE), which is modulated by the dipole density due to the polarization switching on applying an electric field, allows it act as the fundamental components for electromechanical systems. As proposed since the 1970s, its polar α-phase is supposed to yield an enhanced piezoelectric activity. However, its experimental verification has never been reported, hampered by a substantial challenge for the achievement of a smooth, neat α-phase film. Here, we prepare ultrathin crystalline α-phase P(VDF-TrFE) films on the AlOx/Al-coated SiO2/Si substrates via a solution-based approach at room temperature. Thus, we unveil the piezoelectric nature of the polar α-phase P(VDF-TrFE) at a quasi-two-dimensional limit. The obtained values of the relative morphological deformation, the local effective piezoelectric coefficient, and the electric field-induced strain reach up to 37 pm, -46.4 pm V-1, and 4.1%, respectively. Such a robust piezoelectric response is even higher than that of the ß-phase. Besides, the evolution of piezoelectricity, which is related to the piezoelectric properties of two polarization states, is also studied. Our work can enable the exploration of the prospective applications of polar α-phase P(VDF-TrFE) films.

Blockade of 11ß-hydroxysteroid dehydrogenase type 1 enzyme inhibits experimental collagenase-induced osteoarthritis.

Osteoarthritis (OA) is a common cause of functional deterioration in the joints of elderly adults and is a significant burden on the health of the aging population. 11ß­hydroxysteroid dehydrogenase type 1 enzyme (11ß­HSD1), which converts cortisone to cortisol, is known to contribute to a number of inflammatory diseases. However, the role of 11ß­HSD1 in human OA remains unclear. The aim of this study was to identify the effects of the selective 11ß­HSD1 inhibitor, BVT­2733, in murine collagenase­induced osteoarthritis (CIOA). CIOA mice were treated with BVT­2733 (100 mg/kg, orally) or control vehicle twice daily for five weeks. Cartilage and bone destruction were subsequently examined. The expression of bone markers and STAT3 phosphorylation in joint tissues were detected using western blot analysis. The concentrations of proinflammatory cytokines were determined by an enzyme­linked immunosorbent assay. Treatment with BVT­2733 attenuated cartilage and bone destruction, and reduced the expression of bone markers and p­STAT3 in the joints of CIOA mice. BVT­2733 also decreased the serum levels of interleukin (IL)­1ß, IL­6, IL­17 and vascular endothelial growth factor. In conclusion, the present study showed that BVT­2733 inhibits multiple inflammatory signaling pathways in the joints of CIOA mice, suggesting that 11ß­HSD1 inhibition may have therapeutic potential in human OA.

Tolerogenic dendritic cells and rheumatoid arthritis: current status and perspectives.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the influxation of synovia and synovial compartments with immune cells including dendritic cells (DCs). DCs that induce autoimmune tolerance are called tolerogenic DCs (tolDCs). As a promising immunotherapeutic strategy for RA, tolDCs have received increasing attention. In this review, we first introduce the significant role of tolDCs in autoimmune regulation and then describe the manipulation strategies to generate tolDCs; next, we summarize recent progress in the experimental application of tolDCs for RA therapy, and finally we discuss the perspectives of tolerogenic vaccination for the treatment for RA in clinic.

Recombinant human erythropoietin prevents motor neuron apoptosis in a rat model of cervical sub-acute spinal cord compression.

The objective of the study was to investigate the effects of recombinant human erythropoietin (rhEPO) in a rat model of cervical sub-acute spinal cord compression. 80 Wistar rats were randomly divided into 4 groups. Rats in the sham group (Group A, n=5) underwent surgical procedures without cervical spinal cord compression; while rats in other groups were subjected to the spinal compression process. In the control group (Group B, n=25), rats received an i.v. injection of 1 mL saline at day 7 post-surgery. Rats in the low-dose group (Group C, n=25) and the high-dose group (Group D, n=25) were treated with rhEPO at 500 units/kg body-weight and 5000 units/kg, respectively, via intravenous injection at day 7 post surgery. Limb motor function was scored by Basso-Beattie-Bresnahan (BBB) standards at 3, 7, 14, 21 and 28 days post-surgery. The distribution and quantities of EPO and its receptor (EPO-R) in the compressed segment of the spinal cord were detected by immunohistochemistry. Motor neuron apoptosis in the spinal cord was evaluated using TUNEL staining and flow cytometry at the indicated time points. Finally, IL-8, TNF-α, IL-6, and IL-1ß levels in the compressed cervical spinal cord were determined by ELISA within the lesion epicenter at each time point post-surgery. The data suggest that expression of EPO-R was significantly increased following sub-acute cervical spinal cord compression; Groups C and D exhibited better BBB scores at all observed time points compared with the control group (p<0.01). Using TUNEL staining and FCM, we observed that rhEPO profoundly inhibited motor neuron apoptosis in the spinal cord at day 21 (p<0.01). Additionally, treatment with rhEPO halted the elevation of inflammatory cytokines. rhEPO administration decreased motor neuron apoptosis in the cervical spinal cord, improved motor functions and reduced the inflammatory response in a sub-acute cervical spinal cord compression model. Moreover, sustained treatment with low doses of rhEPO revealed a positive therapeutic effect.