Binary azeotropes, which contain two chemicals with a relative volatility of 1, are very common in the chemical industry. Understanding azeotropes is essential for effectively separating binary azeotropes containing l...Binary azeotropes, which contain two chemicals with a relative volatility of 1, are very common in the chemical industry. Understanding azeotropes is essential for effectively separating binary azeotropes containing lower alcohols. Experimental techniques and ab initio approaches can produce accurate results;however, these two processes are time consuming and labor intensive. Although thermodynamic equations such as UNIFAC are widely used, experimental values are required, and it is difficult to choose the best groups to represent a complex system. Because of their high efficiency and fast calculation speed, quantitative structure–property relationship(QSPR) tools were used in this work to predict the azeotropic temperatures and compositions of binary azeotropes containing lower alcohols. The QSPR models for 64 binary azeotropes based on centroid approximation and weighted-contribution-factor approximation were established using the genetic function approximation(GFA) procedure in Materials Studio software, and a leave-one-out cross-validation procedure was conducted.External tests of an additional 16 azeotropes were also investigated, and high determination coefficient values were obtained. The best QSPR models were explained in terms of the molecular structure of the azeotropes,and good predictive ability was obtained within acceptable prediction error levels.展开更多
A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to fur...A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to further explore the potency of the compounds, quantitative structure activity relationship study is carried out using genetic function approximation. Statistically significant (r2 = 0.85) and predictive (r2pred=0.89 and r2m=0.74)?QSAR models are developed. It is evident from the QSAR study that majority of the anti-tubercular activity is found to be driven by lipophilicity. Also, molecular solubility, Jurs and shadow descriptors influence the biological activity significantly. Also, positive contribution of molecular shadow descriptors suggests that molecules with bulkier substituents are more likely to enhance anti-tubercular activity. Since the developed QSAR models are found to be statistically significant and predictive, they potentially can be applied for predicting anti-tubercular activity of new molecules for prioritization of molecules for synthesis.展开更多
Adaptive fuzzy neural inference systems are used to illustrate the primary nodal number of plant life-forms. Categorization of two candidate areas is carried out using the water-energy dynamic (for Ecuador, South Amer...Adaptive fuzzy neural inference systems are used to illustrate the primary nodal number of plant life-forms. Categorization of two candidate areas is carried out using the water-energy dynamic (for Ecuador, South America) and Macedonia, Southern Europe), within which the life-form spectra are distributed. Genetic optimization methods are used to expand the primary nodal number to the complete number of life-form categories. The distribution of the elements exhibits a stochastic, binomial distribution and the utopia line and curve are summarized which enhance accuracy of the climatic data and of the consequent numbers of plant species occurrences. Expansion of the distribution of each life-form category is approximated within the Z utopia hyperplane with use of the functional approximation algorithm. This process gives additional structure and informative value to the Z plane, enhancing our ability to make informed policy decisions concerning species and ecosystem conservation.展开更多
评述了4种炸药感度判据,包括最易跃迁法(最小能隙)、最小键级、最弱键离解能、X—NO2(XC,N or O)中硝基的Mulliken电荷。首次提出了基于炸药分子整体稳定性的名为"键&非键耦合分子刚柔度"的新的感度判据。比较了11种典...评述了4种炸药感度判据,包括最易跃迁法(最小能隙)、最小键级、最弱键离解能、X—NO2(XC,N or O)中硝基的Mulliken电荷。首次提出了基于炸药分子整体稳定性的名为"键&非键耦合分子刚柔度"的新的感度判据。比较了11种典型炸药[1,3,5-三硝基苯(TNB)、2,4,6-三硝基甲苯(TNT)、1,3,3-三硝基氮杂环丁烷(TNAZ)、1,3,5-三硝基-1,3,5-三氮杂环己烷(RDX)、1,3,5-三硝基-2-氧-1,3,5-三氮杂环己烷(K6)、2,4,6,8,10,12-六硝基-2,4,6,8,10,12-六氮杂异伍兹烷(CL-20)、2-苦基-1,2,3-三唑(P CTA)、4-硝基-2-苦基-1,2,3-三唑(NPCTA)、2,6-二氨基-3,5-二硝基吡啶-1-氧化物(LLM-105)、4,6-二硝基苯并氧化呋咱(DNBF)、5,7-二氨基-4,6-二硝基苯并氧化呋咱(DADNBF)]的撞击感度与判据之间的相关性。结果表明,在这5种感度判据中,"键!非键耦合分子刚柔度"评价方法的相关性最高。判据组合能提高预测感度的能力。张力能是炸药分子中键!非键耦合能的一种形式,它不仅能够用于衡量炸药的感度,尤其是不含硝基炸药的感度,同时还能用来量度炸药的储能水平,这对新型炸药的设计和评价具有重要意义。展开更多
基金Supported by the National Natural Science Foundation of China(21776145,21676152)Key Research Project of Shandong Province(2016GSF116004)
文摘Binary azeotropes, which contain two chemicals with a relative volatility of 1, are very common in the chemical industry. Understanding azeotropes is essential for effectively separating binary azeotropes containing lower alcohols. Experimental techniques and ab initio approaches can produce accurate results;however, these two processes are time consuming and labor intensive. Although thermodynamic equations such as UNIFAC are widely used, experimental values are required, and it is difficult to choose the best groups to represent a complex system. Because of their high efficiency and fast calculation speed, quantitative structure–property relationship(QSPR) tools were used in this work to predict the azeotropic temperatures and compositions of binary azeotropes containing lower alcohols. The QSPR models for 64 binary azeotropes based on centroid approximation and weighted-contribution-factor approximation were established using the genetic function approximation(GFA) procedure in Materials Studio software, and a leave-one-out cross-validation procedure was conducted.External tests of an additional 16 azeotropes were also investigated, and high determination coefficient values were obtained. The best QSPR models were explained in terms of the molecular structure of the azeotropes,and good predictive ability was obtained within acceptable prediction error levels.
文摘A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to further explore the potency of the compounds, quantitative structure activity relationship study is carried out using genetic function approximation. Statistically significant (r2 = 0.85) and predictive (r2pred=0.89 and r2m=0.74)?QSAR models are developed. It is evident from the QSAR study that majority of the anti-tubercular activity is found to be driven by lipophilicity. Also, molecular solubility, Jurs and shadow descriptors influence the biological activity significantly. Also, positive contribution of molecular shadow descriptors suggests that molecules with bulkier substituents are more likely to enhance anti-tubercular activity. Since the developed QSAR models are found to be statistically significant and predictive, they potentially can be applied for predicting anti-tubercular activity of new molecules for prioritization of molecules for synthesis.
文摘Adaptive fuzzy neural inference systems are used to illustrate the primary nodal number of plant life-forms. Categorization of two candidate areas is carried out using the water-energy dynamic (for Ecuador, South America) and Macedonia, Southern Europe), within which the life-form spectra are distributed. Genetic optimization methods are used to expand the primary nodal number to the complete number of life-form categories. The distribution of the elements exhibits a stochastic, binomial distribution and the utopia line and curve are summarized which enhance accuracy of the climatic data and of the consequent numbers of plant species occurrences. Expansion of the distribution of each life-form category is approximated within the Z utopia hyperplane with use of the functional approximation algorithm. This process gives additional structure and informative value to the Z plane, enhancing our ability to make informed policy decisions concerning species and ecosystem conservation.
文摘评述了4种炸药感度判据,包括最易跃迁法(最小能隙)、最小键级、最弱键离解能、X—NO2(XC,N or O)中硝基的Mulliken电荷。首次提出了基于炸药分子整体稳定性的名为"键&非键耦合分子刚柔度"的新的感度判据。比较了11种典型炸药[1,3,5-三硝基苯(TNB)、2,4,6-三硝基甲苯(TNT)、1,3,3-三硝基氮杂环丁烷(TNAZ)、1,3,5-三硝基-1,3,5-三氮杂环己烷(RDX)、1,3,5-三硝基-2-氧-1,3,5-三氮杂环己烷(K6)、2,4,6,8,10,12-六硝基-2,4,6,8,10,12-六氮杂异伍兹烷(CL-20)、2-苦基-1,2,3-三唑(P CTA)、4-硝基-2-苦基-1,2,3-三唑(NPCTA)、2,6-二氨基-3,5-二硝基吡啶-1-氧化物(LLM-105)、4,6-二硝基苯并氧化呋咱(DNBF)、5,7-二氨基-4,6-二硝基苯并氧化呋咱(DADNBF)]的撞击感度与判据之间的相关性。结果表明,在这5种感度判据中,"键!非键耦合分子刚柔度"评价方法的相关性最高。判据组合能提高预测感度的能力。张力能是炸药分子中键!非键耦合能的一种形式,它不仅能够用于衡量炸药的感度,尤其是不含硝基炸药的感度,同时还能用来量度炸药的储能水平,这对新型炸药的设计和评价具有重要意义。
