Experimental and numerical simulation of lignite chemical looping gasification with phosphogypsum as oxygen carrier in a fluidized bed

Phosphogypsum (PG) is a solid waste produced in the wet process of producing phosphoric acid.Lignite is a kind of promising chemical raw material.However,the high sulfur of lignite limits the utilization of lig-nite as a resource.Based on fluidized bed experiments,the optimal reaction conditions for the production syngas by lignite chemical looping gasification (CLG) with PG as oxygen carrier were studied.The study found that the optimal reaction temperature should not exceed 1123 K;the mole ratio of water vapor to lignite should be about 0.2;the mole ratio of PG oxygen carrier to lignite should be about 0.6.Meanwhile,commercial software Comsol was used to establish a fuel reaction kinetics model.Through computational fluid dynamics (CFD) numerical simulation,the process of reaction in fluidized bed were well captured.The model was based on a two-fluid model and coupled mass transfer,heat transfer and chemical reac-tions.This study showed that the fluidized bed presents a flow structure in which gas and solid coexist.There was a high temperature zone in the middle and lower parts of the fluidized bed.It could be seen from the results of the flow field simulated that the fluidized bed was beneficial to the progress of the gasification reaction.     

基于有限元方法的CeCl3和NdCl3在LiCl-KCl熔盐中的电极动力学模拟

充分理解锕系元素和镧系元素在熔盐中的行为和性质是实现反应堆乏燃料熔盐电解后处理的关键,然而熔盐电解实验所需的高温环境、腐蚀性熔盐甚至放射性物质等条件限制了实验的广泛开展。为寻求一种低成本且可靠的获取元素在熔盐中性质的途径,采用有限元方法在不同温度下模拟了不同浓度的三氯化铈和三氯化钕在LiCl-KCl熔盐中的循环伏安曲线,并与实验数据做了对比。结果表明,有限元方法能够较为准确地反映实际电化学过程,继而为乏燃料熔盐电解后处理提供数据支持。     

Functional and Molecular Properties of DYT-SGCE Myoclonus-Dystonia Patient-Derived Striatal Medium Spiny Neurons

Myoclonus-dystonia (DYT-SGCE, formerly DYT11) is characterized by alcohol-sensitive, myoclonic-like appearance of fast dystonic movements. It is caused by mutations in the SGCE gene encoding ε-sarcoglycan leading to a dysfunction of this transmembrane protein, alterations in the cerebello-thalamic pathway and impaired striatal plasticity. To elucidate underlying pathogenic mechanisms, we investigated induced pluripotent stem cell (iPSC)-derived striatal medium spiny neurons (MSNs) from two myoclonus-dystonia patients carrying a heterozygous mutation in the SGCE gene (c.298T>G and c.304C>T with protein changes W100G and R102X) in comparison to two matched healthy control lines. Calcium imaging showed significantly elevated basal intracellular Ca²⁺ content and lower frequency of spontaneous Ca²⁺ signals in SGCE MSNs. Blocking of voltage-gated Ca²⁺ channels by verapamil was less efficient in suppressing KCl-induced Ca²⁺ peaks of SGCE MSNs. Ca²⁺ amplitudes upon glycine and acetylcholine applications were increased in SGCE MSNs, but not after GABA or glutamate applications. Expression of voltage-gated Ca²⁺ channels and most ionotropic receptor subunits was not altered. SGCE MSNs showed significantly reduced GABAergic synaptic density. Whole-cell patch-clamp recordings displayed elevated amplitudes of miniature postsynaptic currents and action potentials in SGCE MSNs. Our data contribute to a better understanding of the pathophysiology and the development of novel therapeutic strategies for myoclonus-dystonia.     

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.     

Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies

Toll-like receptor (TLR) signaling plays a critical role in the induction and progression of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematous, experimental autoimmune encephalitis, type 1 diabetes mellitus and neurodegenerative diseases. Deciphering antigen recognition by antibodies provides insights and defines the mechanism of action into the progression of immune responses. Multiple strategies, including phage display and hybridoma technologies, have been used to enhance the affinity of antibodies for their respective epitopes. Here, we investigate the TLR4 antibody-binding epitope by computational-driven approach. We demonstrate that three important residues, i.e., Y328, N329, and K349 of TLR4 antibody binding epitope identified upon in silico mutagenesis, affect not only the interaction and binding affinity of antibody but also influence the structural integrity of TLR4. Furthermore, we predict a novel epitope at the TLR4-MD2 interface which can be targeted and explored for therapeutic antibodies and small molecules. This technique provides an in-depth insight into antibody–antigen interactions at the resolution and will be beneficial for the development of new monoclonal antibodies. Computational techniques, if coupled with experimental methods, will shorten the duration of rational design and development of antibody therapeutics.     

Dynamic “Molecular Portraits” of Biomembranes Drawn by Their Lateral Nanoscale Inhomogeneities

To date, it has been reliably shown that the lipid bilayer/water interface can be thoroughly characterized by a sophisticated so-called “dynamic molecular portrait”. The latter reflects a combination of time-dependent surface distributions of various physicochemical properties, inherent in both model lipid bilayers and natural multi-component cell membranes. One of the most important features of biomembranes is their mosaicity, which is expressed in the constant presence of lateral inhomogeneities, the sizes and lifetimes of which vary in a wide range—from 1 to 10³ nm and from 0.1 ns to milliseconds. In addition to the relatively well-studied macroscopic domains (so-called “rafts”), the analysis of micro- and nanoclusters (or domains) that form an instantaneous picture of the distribution of structural, dynamic, hydrophobic, electrical, etc., properties at the membrane-water interface is attracting increasing interest. This is because such nanodomains (NDs) have been proven to be crucial for the proper membrane functioning in cells. Therefore, an understanding with atomistic details the phenomena associated with NDs is required. The present mini-review describes the recent results of experimental and in silico studies of spontaneously formed NDs in lipid membranes. The main attention is paid to the methods of ND detection, characterization of their spatiotemporal parameters, the elucidation of the molecular mechanisms of their formation. Biological role of NDs in cell membranes is briefly discussed. Understanding such effects creates the basis for rational design of new prospective drugs, therapeutic approaches, and artificial membrane materials with specified properties.     

Probing the Conformation States of Neurotensin Receptor 1 Variants by NMR Site-Directed Methyl Labeling

G protein-coupled receptors (GPCRs) are key players in mediating signal transduction across the cell membrane. However, due to their intrinsic instability, many GPCRs are not suitable for structural investigations. Various approaches have been developed in recent years to remedy this situation, ranging from the use of more native membrane mimetics to protein-stabilization methods. The latter approach typically results in GPCRs that contain various numbers of mutations. However, probing the functionality of such variants by in vitro and in vivo assays is often time consuming. In addition, to validate the suitability of such GPCRs for structural investigations, an assessment of their conformation state is required. NMR spectroscopy has been proven to be suitable to probe the conformation state of GPCRs in solution. Here, by using chemical labeling with an isotope-labeled methyl probe, we show that the activity and the conformation state of stabilized neurotensin receptor 1 variants obtained from directed evolution can be efficiently assayed in 2D NMR experiments. This strategy enables the quantification of the active and inactive conformation states and the derivation of an estimation of the basal as well as agonist-induced activity of the receptor. Furthermore, this assay can be used as a readout when re-introducing agonist-dependent signaling into a highly stabilized, and thus rigidified, receptor by mutagenesis. This approach will be useful in cases where low production yields do not permit the addition of labeled compounds to the growth medium and where 1D NMR spectra of selectively ¹⁹F-labeled receptors are not sufficient to resolve signal overlap for a more detailed analysis.     

5%Si高硅奥氏体不锈钢元素偏析及均匀化处理

 高硅奥氏体不锈钢由于高含量硅元素的加入使其具有优异的耐高温腐蚀性能和较低的成本,在制酸行业有着潜在的应用价值。然而,该合金中高含量硅元素的加入会促进凝固过程中溶质再分配,进而造成显著的元素偏析,最终导致合金内部产生枝晶组织和大量的有害相。对铸锭组织进行均匀化处理能够有效消除枝晶与元素偏析,促进析出相回溶和枝晶消融,从而改善材料的热塑性,有效应对热变形开裂问题。因此,采用金相显微镜(OM)、扫描电镜能谱分析(SEM/EDS)、电子探针(EPMA)、JMatPro软件计算等方法,研究了实验室条件下制备的5%Si高硅奥氏体不锈钢铸锭的显微组织和元素分布状态,通过残余偏析指数、扩散动力学计算并结合均匀化处理试验验证,最终确定了5%Si高硅奥氏体不锈钢合理的均匀化处理工艺。结果表明,5%Si高硅奥氏体不锈钢凝固过程中钼元素偏析最为严重,通过残余偏析指数模型计算得到的均匀化动力学方程可用来指导该成分合金的均匀化处理工艺;5%Si高硅奥氏体不锈钢经过1 150 ℃×12 h均匀化处理后,铸锭内枝晶消融,元素偏析基本消除,析出相与铁素体回溶到基体中,合金转变为全奥氏体组织,热塑性得到改善;当加热温度达到1 250 ℃时,合金出现过烧现象,晶界开始熔化。     

一种新的位错运动理论及对材料动态力学行为的描述

通过对位错在晶格内运动的动力学过程的全面分析。本文提出了一种考虑到粘性阻尼效应和热激活的位错集体运动统一理论。其特点是可用一简单的方程对从低速到高速运动的大量位错的平均行为进行统一描述。对ＫＣｌ晶体的典型实验怕拟合发现理论描述与实验结果相当一致。     

分子动力学在材料科学中的应用

分子动力学方法是进行物质原子或分子层次计算机模拟时所采用的一种基本方法。通过分子动力学模拟，可以给出原子尺度上材料及其演化过程细节的可能性，具有无先例的准确性，使材料设计和性能预测成为可能。本文分析了分子动力学模拟的基本原理和算法；综述了分子动力学在材料科学中的应用，介绍了最近发展的第一原理分子动力学模拟，指出材料科学中第一原理分子动力学模拟的应用还有待进一步发展。