An Update on Molecularly Imprinted Polymer Design through a Computational Approach to Produce Molecular Recognition Material with Enhanced Analytical Performance

Molecularly imprinted polymer (MIP) computational design is expected to become a routine technique prior to synthesis to produce polymers with high affinity and selectivity towards target molecules. Furthermore, using these simulations reduces the cost of optimizing polymerization composition. There are several computational methods used in MIP fabrication and each requires a comprehensive study in order to select a process with results that are most similar to properties exhibited by polymers synthesized through laboratory experiments. Until now, no review has linked computational strategies with experimental results, which are needed to determine the method that is most appropriate for use in designing MIP with high molecular recognition. This review will present an update of the computational approaches started from 2016 until now on quantum mechanics, molecular mechanics and molecular dynamics that have been widely used. It will also discuss the linear correlation between computational results and the polymer performance tests through laboratory experiments to examine to what extent these methods can be relied upon to obtain polymers with high molecular recognition. Based on the literature search, density functional theory (DFT) with various hybrid functions and basis sets is most often used as a theoretical method to provide a shorter MIP manufacturing process as well as good analytical performance as recognition material.     

Recent advances on the use of active anodes in environmental electrochemistry

Active anodes, especially those consisting of metal mixed oxides (MMOs) containing Ru and/or Ir oxides, have been applied in the treatment of wastewater, especially when chloride ions are present. Their characteristics continuously drive the study of applications of these materials, be they in the degradation of different organic molecules, the preparation of new electrode materials and in the association of various processes to increase pollutant removal. Thus, this brief review aims to present some of the recent advances in the application of active anode materials in environmental electrochemistry. Focussing on the 2018–2020 period, it is possible to note many applied studies, using commercially available materials, covering a wide range of target pollutants. Still other studies aim to modify the catalyst surfaces to increase the mineralization capacity, and the use of these anodes in the production of free chlorine species to mediate indirect organic reduction is observed.     

Springer basic sets and modular Springer correspondence for classical types

We define the notion of basic set data for finite groups (building on the notion of basic set, but including an order on the irreducible characters as part of the structure), and we prove that the Springer correspondence provides basic set data for Weyl groups. Then we use this to determine explicitly the modular Springer correspondence for classical types (defined over a base field of odd characteristic $p$, and with coefficients in a field of odd characteristic $?\ne p$): the modular case is obtained as a restriction of the ordinary case to a basic set. In order to do so, we compare the order on bipartitions introduced by Dipper and James with the order induced by the Springer correspondence. We provide a quick proof, by sorting characters according to the dimension of the corresponding Springer fibre, an invariant which is directly computable from symbols.     

Theoretical study on the mechanism for the excited-state double proton transfer process of an asymmetric Schiff base ligand

Excited-state double proton transfer (ESDPT) in the 1-[(2-hydroxy-3-methoxy-benzylidene)-hydrazonomethyl]-naphthalen-2-ol (HYDRAVH₂) ligand was studied by the density functional theory and time-dependent density functional theory method. The analysis of frontier molecular orbitals, infrared spectra, and non-covalent interactions have cross-validated that the asymmetric structure has an influence on the proton transfer, which makes the proton transfer ability of the two hydrogen protons different. The potential energy surfaces in both S₀ and S₁ states were scanned with varying O-H bond lengths. The results of potential energy surface analysis adequately proved that the HYDRAVH₂ can undergo the ESDPT process in the S₁ state and the double proton transfer process is a stepwise proton transfer mechanism. Our work can pave the way towards the design and synthesis of new molecules.     

First principles investigations of Fe,Co, Ni in model honeycomb carbon networks

The behaviors of ferromagnetic transition metals of the first period: Fe, Co and Ni are examined within density functional theory calculations in two dimensional carbon extended networks using model structure LiC₆. Around geometry optimized structures, the energy-volume equations of states considering non magnetic and spin polarized configurations established ferromagnetic ground states with magnetizations –reduced with respect to the metals’– of 2 μ_B for FeC₆ and 1 μ_B for CoC₆ while no magnetic solution could be identified for NiC₆. In the D_6h point group of the P6/mmm space group l_m decomposition of the d states results with increasing energy into doublet state E_1g with d(x²-y²) and d(xy); singlet state A_1g d(z²) and doublet state E_2g d(xz) and d(yz) lying on E_F and responsible of the onset of magnetic moments. This was mirrored via molecular orbital approach with a construct of Fe embedded between two extended carbon networks thus validating the model structure proposed for TC₆ compounds. The 100% polarization in one spin channel allows proposing potential uses in spintronics applications.     

Vacuum‐driven fluid manipulation by a piezoelectric diaphragm micropump for microfluidic droplet generation with a rapid system response time

Recently, we developed a convenient microfluidic droplet generation device based on vacuum‐driven fluid manipulation with a piezoelectric diaphragm micropump. In the present study built on our previous work, we investigate the influence of settings applied to the piezoelectric pump, such as peak‐to‐peak drive voltage (V_p‐p) and wave frequency, on droplet generation characteristics. Stepwise adjustments to the drive voltage in ±10‐V_p‐p increments over the range of 200?250 V_p‐p during droplet creation revealed that the droplet generation rate could be reproducibly controlled at a specific drive voltage. The droplet generation rate switched within <0.5 s after the input of a new voltage. Although the droplet generation rate depended on the drive voltage, this setting had almost no influence on droplet size. The frequency over the selected range (50?60 Hz) did not markedly influence the droplet generation rate or droplet size. We show that the current fluid manipulation system can be conveniently used for both droplet generation and for rapid droplet reading, which is required in many microfluidic‐based applications.     

Theoretical study of (e,2e) triple differential cross sections of pyrimidine and tetrahydrofurfuryl alcohol molecules using multi-center distorted-wave method

We report theoretical studies of electron impact triple differential cross sections of two bio-molecules,pyrimidine and tetrahydrofurfuryl alcohol,in the coplanar asymmetric kinematic conditions with the impact energy of 250 eV and ejected electron energy of 20 eV at three scattering angles of-5°,-10°,and-15°.Present multi-center distorted-wave method well describes the experimental data,which was obtained by performing(e,2e)experiment.The calculations show that the secondary electron produced by the primary impact electron is strongly influenced by the molecular ionic multi-center potential,which must be considered when the low energy electron interacts with DNA analogues.     

紫色球杆菌视紫红质光谱特性的机器学习研究

近年来，机器学习等人工智能技术被应用于蛋白质工程，其在蛋白质结构、功能预测、催化活性等研究中具有独特优势。在未知蛋白质结构的情况下，将蛋白质序列和功能特性与机器学习相结合，基于序列-活性关系（innovative sequence-activity relationship，ISAR）算法，将蛋白质氨基酸序列数字化，用快速傅里叶变换（fast four transform，FFT）进行预处理，再进行偏最小二乘回归建模，可在数据集较少情况下拟合得到最佳模型。通过机器学习对紫色球杆菌视紫红质（gloeobacter violaceus rhodopsin，GR）的突变体蛋白质氨基酸序列与光谱最大吸收波长进行建模，获得了最佳模型。用最佳索引LEVM760106建模得到的确定系数R² 为0.944，均方误差E为11.64。用小波变换进行的预处理，其R² 虽也约为0.944，但E大于11.64，不及FFT进行的预处理。方法较好地解决了蛋白质序列与功能特性之间的数学建模问题，在蛋白质工程中可为预测更优的突变体提供支持。     

A simple,rapid and sensitive method based on modified multiwalled carbon nanotube for preconcentration and determination of lead ions in aqueous media in natural pHs

In this study, multiwalled carbon nanotube (MWCNT) was modified by the pyridine group using a silane agent and characterized by infrared spectroscopy (IR), thermal analysis (TG/DTA), and elemental analysis (CHN) and scanning electron microscopy (SEM). The application of this sorbent was investigated in determination of lead ions in aqueous samples, using flame atomic absorption spectrometry (FAAS). Through this study, different parameters such as pH and sample flow rate on adsorption process and eluent concentration, volume and flow rate were optimized. The limit of detection (LOD), the relative standard deviation and the recovery of the method were 2 ng mL^?1, 1.3% and 99.7%, respectively. Two standard reference materials (NIST 1571 and NIST 1572) were used to verify accuracy of this method. Finally, the sorbent was successfully applied for extraction and determination of low levels of Pb(II) ions in aqueous samples.