scholarly journals High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 165
Author(s):  
Hao Qin ◽  
Zihao Wang ◽  
Zhen Song ◽  
Xiang Zhang ◽  
Teng Zhou
Keyword(s):  
Ionic Liquids ◽  
Energy Consumption ◽  
High Throughput ◽  
Physical Property ◽  
Extractive Distillation ◽  
High Energy ◽  
Molecular Structures ◽  
Boiling Points ◽  
Computational Screening ◽  
Potential Alternative

The separation of 1,3-butadiene (1,3-C4H6) and 1-butene (n-C4H8) is quite challenging due to their close boiling points and similar molecular structures. Extractive distillation (ED) is widely regarded as a promising approach for such a separation task. For ED processes, the selection of suitable entrainer is of central importance. Traditional ED processes using organic solvents suffer from high energy consumption. To tackle this issue, the utilization of ionic liquids (ILs) can serve as a potential alternative. In this work, a high-throughput computational screening of ILs is performed to find proper entrainers, where 36,260 IL candidates comprising of 370 cations and 98 anions are involved. COSMO-RS is employed to calculate the infinite dilution extractive capacity and selectivity of the 36,260 ILs. In doing so, the ILs that satisfy the prespecified thermodynamic criteria and physical property constraints are identified. After the screening, the resulting IL candidates are sent for rigorous process simulation and design. 1,2,3,4,5-pentamethylimidazolium methylcarbonate is found to be the optimal IL solvent. Compared with the benchmark ED process where the organic solvent N-methyl-2-pyrrolidone is adopted, the energy consumption is reduced by 26%. As a result, this work offers a new IL-based ED process for efficient 1,3-C4H6 production.

scholarly journals Evaluation of Ionic Liquids as In Situ Extraction Agents during the Alcoholic Fermentation of Carob Pod Extracts

Fermentation ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 90 ◽  
Author(s):  
Sergio Sanchez-Segado ◽  
María José Salar-García ◽  
Víctor Manuel Ortiz-Martínez ◽  
Antonia Pérez de los Ríos ◽  
Francisco José Hernández-Fernández ◽  
...  
Keyword(s):  
Ionic Liquids ◽  
Energy Consumption ◽  
Molecular Sieves ◽  
Alcoholic Fermentation ◽  
Current System ◽  
Extractive Distillation ◽  
High Energy ◽  
Anhydrous Ethanol ◽  
Carbohydrate Source ◽  
Promising Alternative

Anhydrous ethanol is a promising alternative to gasoline in fuel engines. However, since ethanol forms an azeotrope with water, high-energy-consumption separation techniques such as azeotropic distillation, extractive distillation, and molecular sieves are needed to produce anhydrous ethanol. This work discusses the potential development of an integrated process for bioethanol production using ionic liquids and Ceratonia siliqua as a carbohydrate source for further fermentation of the aqueous extracts. A four-stage counter-current system was designed to improve the sugar extraction yield to values close to 99%. The alcoholic fermentation of the extracts showed ethanol concentrations of 95 g/L using the microorganism Saccharomyces cerevisae. The production of anhydrous ethanol through extractive distillation with ethylene glycol was simulated using CHEMCAD software, with an energy consumption of 13.23 MJ/Kg of anhydrous ethanol. Finally, several ionic liquids were analyzed and are proposed as potential solvents for the recovery of bioethanol for the design of an integrated extraction–fermentation–separation process, according to their ability to extract ethanol from aqueous solutions and their biocompatibility with the microorganism used in this study.

Research on Synthesis, Characterization and CO2 Absorption of Functional Room Temperature Ionic Liquids

2020 ◽  
Vol 984 ◽  
pp. 189-194
Author(s):  
Zhi Min Sun ◽  
Bing Li
Keyword(s):  
Ionic Liquid ◽  
Blast Furnace ◽  
Ionic Liquids ◽  
Energy Consumption ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
High Energy ◽  
Synthesis Process ◽  
Gas Emissions ◽  
Blast Furnace Gas

Iron and steel making is an industry with high energy consumption and greenhouse gas emissions. The work is to carry out the CO2 capture experimental study as background of the blast furnace gas, increase the calorific value of the blast furnace gas and reduce greenhouse gas emissions and the energy consumption of CO2 gas in the follow-up process cycle. In this paper, according to the principle of acid base neutralization, [EDA]L and [EDA]P contained amino ionic liquids are synthesized in ice water bath condition, which is made from lactic acid, formic acid and ethylenediamine. The synthesis process was explored, the viscosity and infrared spectroscopy of synthetic ionic liquid were characterized, the boiling point of ionic liquids were calculated, CO2 absorption experiments were carried out under normal temperature and pressure. The results indicate that the compositions are ionic liquids having target structures and the maximum molar absorption of ionic liquid to CO2 reaches 0.45 mol.

scholarly journals Representation of Molecular Structures with Persistent Homology Leads to the Discovery of Molecular Groups with Enhanced CO2 Binding

2020 ◽  
Author(s):  
Jacob Townsend ◽  
Cassie Putman Micucci ◽  
John H. Hymel ◽  
Vasileios Maroulas ◽  
Konstantinos Vogiatzis
Keyword(s):  
Machine Learning ◽  
High Throughput ◽  
Persistent Homology ◽  
Molecular Structures ◽  
General Interest ◽  
Molecular Fingerprinting ◽  
Computational Screening ◽  
Chemical Machine ◽  
Separation Of Co2 ◽  
And Performance

<p>Developing alternative strategies for efficient separation of CO2 and N2 is of general interest for the reduction of anthropogenic carbon emissions. In recent years, machine learning and high-throughput computational screening have been valuable tools in accelerated first-principles screening for the discovery of the next generation of functionalized molecules and materials. The application of machine learning for chemical applications requires the conversion of molecular structures to a machine-readable format known as a molecular representation. The choice of such representations impacts the performance and outcomes of chemical machine learning methods. Herein, we present a new concise and size-consistent molecular representation derived from persistent homology,an applied branch of mathematics. We have demonstrated its applicability in a high-throughput computational screening of a large molecular database (GDB-9) with more than 133,000 organic molecules. Our target is to identify novel molecules that selectively interact with CO2. The methodology and performance of the novel molecular fingerprinting method is presented and the new chemically-driven persistence image representation is used to screen the GDB-9 database to suggest molecules and/or functional groups with enhanced properties.</p>

scholarly journals Representation of Molecular Structures with Persistent Homology Leads to the Discovery of Molecular Groups with Enhanced CO2 Binding

2020 ◽  
Author(s):  
Jacob Townsend ◽  
Cassie Putman Micucci ◽  
John H. Hymel ◽  
Vasileios Maroulas ◽  
Konstantinos Vogiatzis
Keyword(s):  
Machine Learning ◽  
High Throughput ◽  
Persistent Homology ◽  
Molecular Structures ◽  
General Interest ◽  
Molecular Fingerprinting ◽  
Computational Screening ◽  
Chemical Machine ◽  
Separation Of Co2 ◽  
And Performance

<p>Developing alternative strategies for efficient separation of CO2 and N2 is of general interest for the reduction of anthropogenic carbon emissions. In recent years, machine learning and high-throughput computational screening have been valuable tools in accelerated first-principles screening for the discovery of the next generation of functionalized molecules and materials. The application of machine learning for chemical applications requires the conversion of molecular structures to a machine-readable format known as a molecular representation. The choice of such representations impacts the performance and outcomes of chemical machine learning methods. Herein, we present a new concise and size-consistent molecular representation derived from persistent homology,an applied branch of mathematics. We have demonstrated its applicability in a high-throughput computational screening of a large molecular database (GDB-9) with more than 133,000 organic molecules. Our target is to identify novel molecules that selectively interact with CO2. The methodology and performance of the novel molecular fingerprinting method is presented and the new chemically-driven persistence image representation is used to screen the GDB-9 database to suggest molecules and/or functional groups with enhanced properties.</p>

scholarly journals SELECTION OF EXTRACTIVE AGENTS FOR THE SEPARATION OF CHLOROFORM - METHANOL - TETRAHYDROFURAN MIXTURE

2018 ◽  
Vol 13 (3) ◽  
pp. 30-40 ◽  
Author(s):  
V. M. Raeva ◽  
D. I. Sukhov
Keyword(s):  
Energy Consumption ◽  
Extractive Distillation ◽  
Industrial Test ◽  
Ideal Behavior ◽  
Component Mixture ◽  
Distillation Columns ◽  
Boiling Points ◽  
Derivative System ◽  
Separating Agents ◽  
Chloroform Methanol

Variants of the extractive distillation of chloroform - methanol - tetrahydrofuran equimolar mixture with industrial separating agents are considered. The basic system shows opposite deviations from the ideal behavior, because it contains binary azeotropes with minimum and maximum boiling points (3.3.1-4 system according to Serafimov’s classification). The choice of selective substances for extractive distillation was carried out taking into account the concentration dependences of the excess molar Gibbs energy of the binary constituents of the derivative system “chloroform - methanol - tetrahydrofuran - industrial test agent (ethylene glycol (EG), dimethyl sulfoxide (DMSO), N-methylpyrrolidone (N-MP))” at 101.32 kPa. Based on the results of the evaluation of the thermodynamic criterion, DMSO and N-MP are recommended. Both agents show selective effect when separating two binary constituents. EG is selective only with respect to chloroform-tetrahydrofuran mixture. Since the tested agents show different selective effects, the final agent choice determines the qualitative composition of the product flows in the column for the extractive distillation of the three-component mixture (the first column of the flowsheet) and, accordingly, the structure of the total flowsheet. The schemes consist of two two-column complexes for extractive distillation (for the basic three-component mixture and for the binary mixture). The maximum contribution to the total reboiler energy consumption of the distillation columns is made by the first extractive distillation column: 65% (EG), 53% (N-MP) and 24% (DMSO). The use of the most selective agent reduces the energy consumption of this column: the reboiler load is maximal in the case of EG, in comparison with which the load is 47% lower in the case of N-MP and 76% lower in the case of DMSO.

scholarly journals Representation of Molecular Structures with Persistent Homology Leads to the Discovery of Molecular Groups with Enhanced CO2 Binding

2019 ◽  
Author(s):  
Jacob Townsend ◽  
Cassie Putman Micucci ◽  
John H. Hymel ◽  
Vasileios Maroulas ◽  
Konstantinos Vogiatzis
Keyword(s):  
Machine Learning ◽  
High Throughput ◽  
Persistent Homology ◽  
Molecular Structures ◽  
General Interest ◽  
Molecular Fingerprinting ◽  
Computational Screening ◽  
Chemical Machine ◽  
Separation Of Co2 ◽  
And Performance

<p>Developing alternative strategies for efficient separation of CO2 and N2 is of general interest for the reduction of anthropogenic carbon emissions. In recent years, machine learning and high-throughput computational screening have been valuable tools in accelerated first-principles screening for the discovery of the next generation of functionalized molecules and materials. The application of machine learning for chemical applications requires the conversion of molecular structures to a machine-readable format known as a molecular representation. The choice of such representations impacts the performance and outcomes of chemical machine learning methods. Herein, we present a new concise and size-consistent molecular representation derived from persistent homology,an applied branch of mathematics. We have demonstrated its applicability in a high-throughput computational screening of a large molecular database (GDB-9) with more than 133,000 organic molecules. Our target is to identify novel molecules that selectively interact with CO2. The methodology and performance of the novel molecular fingerprinting method is presented and the new chemically-driven persistence image representation is used to screen the GDB-9 database to suggest molecules and/or functional groups with enhanced properties.</p>

scholarly journals Multivariate statistical optimization of the ethanol fuel dehydration process using ionic liquids

2020 ◽  
pp. 35-35
Author(s):  
Cláudia Cavalcanti ◽  
João Queiroz ◽  
Luiz Stragevitch ◽  
de Rodrigues ◽  
Maria Pimentel
Keyword(s):  
Ionic Liquids ◽  
Energy Consumption ◽  
Ethylene Glycol ◽  
Energy Use ◽  
Desirability Function ◽  
Extractive Distillation ◽  
Statistical Technique ◽  
Dehydration Process ◽  
Ethanol Fuel ◽  
Multivariate Statistical

In this work, the ethanol fuel dehydration process was optimized using the Aspen Plus? simulator and a multivariate statistical technique based on the desirability function. The suitability of the ionic liquids 1-methylimidazolium chloride ([Mim][Cl]), 1-ethyl-3-methylimidazolium chloride ([Emim][Cl]), 1-butyl-3-methylimidazolium chloride ([Bmim][Cl]) and 1-hexyl-3-methylimidazolium chloride ([Hmim][Cl]), as extractive distillation entrainers, was also evaluated and compared to the conventional solvents, ethylene glycol and cyclohexane. Among the solvents studied, [Mim][Cl] required the lowest energy consumption, about 8% less energy use when compared to the optimized process using ethylene glycol. The multivariate statistical techniques employed were effective in the optimization of the extractive distillation processes as the process energy consumption could be minimized while achieving ethanol purity in agreement with the current specifications as well as obtaining a high solvent recovery. With the desirability approach it was possible to improve the process performance with little or no modification of existing processing plants.

scholarly journals A novel gradient current density output mode for effective electrochemical oxidative degradation of dye wastewater by boron-doped diamond (BDD) anode

2020 ◽  
Vol 82 (10) ◽  
pp. 2085-2097
Author(s):  
Ting Liu ◽  
Dongtian Miao ◽  
Guoshuai Liu ◽  
Qiuping Wei ◽  
Kechao Zhou ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Current Efficiency ◽  
Current Density ◽  
High Energy ◽  
Molecular Structures ◽  
Constant Current ◽  
Dye Wastewater ◽  
Output Process ◽  
Boron Doped Diamond ◽  
General Applicability

Abstract In order to solve the problems of high energy consumption and low current efficiency in electrochemical oxidation (EO) degradation under the traditional constant output process (COP), a gradient output process (GOP) of current density is proposed in this paper. That is, the current density is gradually reduced in a fixed degradation time, and the Reactive Blue 19 simulated dye wastewater was used as the degradation target. The general applicability of the process was further confirmed by studying the optimal gradient current density output parameters, the dye concentration, electrolyte concentration and other dye compounds with different molecular structures. The corresponding results show that the chemical oxygen demand (COD) removal (78%) and the color removal (100%) under the GOP are similar to those in the COP, and the overall energy consumption is reduced by about 50% compared with that in the traditional constant current mode. Moreover, the current efficiency in the middle and late stages of EO process has increased by 8.6 times compared with COP.

Separation of Biologically Active Compounds by Membrane Operations

2017 ◽  
Vol 23 (2) ◽  
pp. 218-230 ◽  
Author(s):  
Xiaoying Zhu ◽  
Renbi Bai
Keyword(s):  
Energy Consumption ◽  
Bioactive Compounds ◽  
Membrane Fouling ◽  
Membrane Separation ◽  
Separation Efficiency ◽  
High Energy ◽  
Separation Processes ◽  
Membrane Processes ◽  
Separation Technology ◽  
Pressure Driven

Background: Bioactive compounds from various natural sources have been attracting more and more attention, owing to their broad diversity of functionalities and availabilities. However, many of the bioactive compounds often exist at an extremely low concentration in a mixture so that massive harvesting is needed to obtain sufficient amounts for their practical usage. Thus, effective fractionation or separation technologies are essential for the screening and production of the bioactive compound products. The applicatons of conventional processes such as extraction, distillation and lyophilisation, etc. may be tedious, have high energy consumption or cause denature or degradation of the bioactive compounds. Membrane separation processes operate at ambient temperature, without the need for heating and therefore with less energy consumption. The “cold” separation technology also prevents the possible degradation of the bioactive compounds. The separation process is mainly physical and both fractions (permeate and retentate) of the membrane processes may be recovered. Thus, using membrane separation technology is a promising approach to concentrate and separate bioactive compounds. Methods: A comprehensive survey of membrane operations used for the separation of bioactive compounds is conducted. The available and established membrane separation processes are introduced and reviewed. Results: The most frequently used membrane processes are the pressure driven ones, including microfiltration (MF), ultrafiltration (UF) and nanofiltration (NF). They are applied either individually as a single sieve or in combination as an integrated membrane array to meet the different requirements in the separation of bioactive compounds. Other new membrane processes with multiple functions have also been developed and employed for the separation or fractionation of bioactive compounds. The hybrid electrodialysis (ED)-UF membrane process, for example has been used to provide a solution for the separation of biomolecules with similar molecular weights but different surface electrical properties. In contrast, the affinity membrane technology is shown to have the advantages of increasing the separation efficiency at low operational pressures through selectively adsorbing bioactive compounds during the filtration process. Conclusion: Individual membranes or membrane arrays are effectively used to separate bioactive compounds or achieve multiple fractionation of them with different molecule weights or sizes. Pressure driven membrane processes are highly efficient and widely used. Membrane fouling, especially irreversible organic and biological fouling, is the inevitable problem. Multifunctional membranes and affinity membranes provide the possibility of effectively separating bioactive compounds that are similar in sizes but different in other physical and chemical properties. Surface modification methods are of great potential to increase membrane separation efficiency as well as reduce the problem of membrane fouling. Developing membranes and optimizing the operational parameters specifically for the applications of separation of various bioactive compounds should be taken as an important part of ongoing or future membrane research in this field.

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