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Brandolín SE, Scilipoti JA, Magario I. Elucidating solvent effects on lipase-catalyzed peroxyacid synthesis through activity-based kinetics and molecular dynamics. Biotechnol Bioeng 2024; 121:2728-2741. [PMID: 38837223 DOI: 10.1002/bit.28762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/17/2024] [Accepted: 05/21/2024] [Indexed: 06/07/2024]
Abstract
Peroxyacid synthesis is the first step in Prilezhaev epoxidation, which is an industrial method to form epoxides. Motivated by the development of a kinetic model as a tool for solvent selection, the effect of solvent type and acid chain length on the lipase-catalyzed peroxyacid synthesis was studied. A thermodynamic activity-based ping-pong kinetic expression was successfully applied to predict the effect of the reagent loadings in hexane. The activity-based reaction quotients provided a prediction of solvent-independent equilibrium constants. However, this strategy did not achieve satisfactory estimations of initial rates in solvents of higher polarity. The lack of compliance with some assumptions of this methodology could be confirmed through molecular dynamics calculations i.e. independent solvation energies and lack of solvent interaction with the active site. A novel approach is proposed combining the activity-based kinetic expression and the free binding energy of the solvent with the active site to predict kinetics upon solvent change. Di-isopropyl ether generated a strong interaction with the enzyme's active site, which was detrimental to kinetics. On the other hand, toluene or limonene gave moderate interaction with the active site rendering improved catalytic yield compared with less polar solvents, a finding sharpened when peroctanoic acid was produced.
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Affiliation(s)
- Salvador E Brandolín
- Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada (IPQA), Facultad de Ciencias Exactas, Física y Naturales - Universidad Nacional de Córdoba, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Córdoba, Argentina
| | - José A Scilipoti
- Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada (IPQA), Facultad de Ciencias Exactas, Física y Naturales - Universidad Nacional de Córdoba, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Córdoba, Argentina
| | - Ivana Magario
- Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada (IPQA), Facultad de Ciencias Exactas, Física y Naturales - Universidad Nacional de Córdoba, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Córdoba, Argentina
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2
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Lee S, Walker PJ, Velling SJ, Chen A, Taylor ZW, Fiori CJBM, Gandhi V, Wang ZG, Greer JR. Molecular control via dynamic bonding enables material responsiveness in additively manufactured metallo-polyelectrolytes. Nat Commun 2024; 15:6850. [PMID: 39127713 DOI: 10.1038/s41467-024-50860-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 07/23/2024] [Indexed: 08/12/2024] Open
Abstract
Metallo-polyelectrolytes are versatile materials for applications like filtration, biomedical devices, and sensors, due to their metal-organic synergy. Their dynamic and reversible electrostatic interactions offer high ionic conductivity, self-healing, and tunable mechanical properties. However, the knowledge gap between molecular-level dynamic bonds and continuum-level material properties persists, largely due to limited fabrication methods and a lack of theoretical design frameworks. To address this critical gap, we present a framework, combining theoretical and experimental insights, highlighting the interplay of molecular parameters in governing material properties. Using stereolithography-based additive manufacturing, we produce durable metallo-polyelectrolytes gels with tunable mechanical properties based on metal ion valency and polymer charge sparsity. Our approach unveils mechanistic insights into how these interactions propagate to macroscale properties, where higher valency ions yield stiffer, tougher materials, and lower charge sparsity alters material phase behavior. This work enhances understanding of metallo-polyelectrolytes behavior, providing a foundation for designing advanced functional materials.
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Affiliation(s)
- Seola Lee
- Division of Engineering and Applied Science, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA.
| | - Pierre J Walker
- Division of Chemistry and Chemical Engineering, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Seneca J Velling
- Division of Engineering and Applied Science, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Amylynn Chen
- Division of Engineering and Applied Science, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Zane W Taylor
- Division of Engineering and Applied Science, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Cyrus J B M Fiori
- Division of Chemistry and Chemical Engineering, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Vatsa Gandhi
- Division of Engineering and Applied Science, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
- Kavli Nanoscience Institute, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Zhen-Gang Wang
- Division of Chemistry and Chemical Engineering, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
| | - Julia R Greer
- Division of Engineering and Applied Science, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
- Kavli Nanoscience Institute, California Institute of Technology, 1200 California Boulevard, Pasadena, 91125, CA, USA
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3
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Shiga M, Morishita T, Nishiyama N, Sorai M, Aichi M, Abe A. Atomic-Scale Insights into the Phase Behavior of Carbon Dioxide and Water from 313 to 573 K and 8 to 30 MPa. ACS OMEGA 2024; 9:20976-20987. [PMID: 38764624 PMCID: PMC11097351 DOI: 10.1021/acsomega.4c00133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/17/2024] [Accepted: 04/10/2024] [Indexed: 05/21/2024]
Abstract
We performed molecular dynamics (MD) simulations of CO2 + H2O systems by employing widely used force fields (EPM2, TraPPE, and PPL models for CO2; SPC/E and TIP4P/2005 models for H2O). The phase behavior observed in our MD simulations is consistent with the coexistence lines obtained from previous experiments and SAFT-based theoretical models for the equations of state. Our structural analysis reveals a pronounced correlation between phase transitions and the structural orderliness. Specifically, the coordination number of Ow (oxygen in H2O) around other Ow significantly correlates with phase changes. In contrast, coordination numbers pertaining to the CO2 molecules show less sensitivity to the thermodynamic state of the system. Furthermore, our data indicate that a predominant number of H2O molecules exist as monomers without forming hydrogen bonds, particularly in a CO2-rich mixture, signaling a breakdown in the hydrogen bond network's orderliness, as evidenced by a marked decrease in tetrahedrality. These insights are crucial for a deeper atomic-level understanding of phase behaviors, contributing to the well-grounded design of CO2 injection under high-pressure and high-temperature conditions, where an atomic-scale perspective of the phase behavior is still lacking.
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Affiliation(s)
- Masashige Shiga
- Geological
Survey of Japan, National Institute of Advanced
Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8567, Japan
| | - Tetsuya Morishita
- Research
Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science
and Technology (AIST), Tsukuba, Ibaraki 305-8568, Japan
| | - Naoki Nishiyama
- Geological
Survey of Japan, National Institute of Advanced
Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8567, Japan
| | - Masao Sorai
- Geological
Survey of Japan, National Institute of Advanced
Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8567, Japan
| | - Masaatsu Aichi
- Department
of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba 277-8563, Japan
| | - Ayaka Abe
- Japan
Organization for Metals and Energy Security (JOGMEC), Minato-ku, Tokyo 105-0001, Japan
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4
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Bernet T, Wehbe M, Febra SA, Haslam AJ, Adjiman CS, Jackson G, Galindo A. Modeling the Thermodynamic Properties of Saturated Lactones in Nonideal Mixtures with the SAFT-γ Mie Approach. JOURNAL OF CHEMICAL AND ENGINEERING DATA 2024; 69:650-678. [PMID: 38352073 PMCID: PMC10859965 DOI: 10.1021/acs.jced.3c00358] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/30/2023] [Indexed: 02/16/2024]
Abstract
The prediction of the thermodynamic properties of lactones is an important challenge in the flavor, fragrance, and pharmaceutical industries. Here, we develop a predictive model of the phase behavior of binary mixtures of lactones with hydrocarbons, alcohols, ketones, esters, aromatic compounds, water, and carbon dioxide. We extend the group-parameter matrix of the statistical associating fluid theory SAFT-γ Mie group-contribution method by defining a new cyclic ester group, denoted cCOO. The group is composed of two spherical Mie segments and two association electron-donating sites of type e1 that can interact with association electron-accepting sites of type H in other molecules. The model parameters of the new cCOO group interactions (1 like interaction and 17 unlike interactions) are characterized to represent target experimental data of physical properties of pure fluids (vapor pressure, single-phase density, and vaporization enthalpy) and mixtures (vapor-liquid equilibria, liquid-liquid equilibria, solid-liquid equilibria, density, and excess enthalpy). The robustness of the model is assessed by comparing theoretical predictions with experimental data, mainly for oxolan-2-one, 5-methyloxolan-2-one, and oxepan-2-one (also referred to as γ-butyrolactone, γ-valerolactone, and ε-caprolactone, respectively). The calculations are found to be in very good quantitative agreement with experiments. The proposed model allows for accurate predictions of the thermodynamic properties and highly nonideal phase behavior of the systems of interest, such as azeotrope compositions. It can be used to support the development of novel molecules and manufacturing processes.
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Affiliation(s)
- Thomas Bernet
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Malak Wehbe
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Sara A. Febra
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Andrew J. Haslam
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Claire S. Adjiman
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - George Jackson
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Amparo Galindo
- Department
of Chemical Engineering, Sargent Centre for Process Systems Engineering,
Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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Pal S, Bhattacharya M, Dash S, Lee SS, Chakraborty C. A next-generation dynamic programming language Julia: Its features and applications in biological science. J Adv Res 2023:S2090-1232(23)00352-1. [PMID: 37992995 DOI: 10.1016/j.jare.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 11/07/2023] [Accepted: 11/14/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND The advent of Julia as a sophisticated and dynamic programming language in 2012 represented a significant milestone in computational programming, mathematical analysis, and statistical modeling. Having reached its stable release in version 1.9.0 on May 7, 2023, Julia has developed into a powerful and versatile instrument. Despite its potential and widespread adoption across various scientific and technical domains, there exists a noticeable knowledge gap in comprehending its utilization within biological sciences. THE AIM OF REVIEW This comprehensive review aims to address this particular knowledge gap and offer a thorough examination of Julia's fundamental characteristics and its applications in biology. KEY SCIENTIFIC CONCEPTS OF THE REVIEW The review focuses on a research gap in the biological science. The review aims to equip researchers with knowledge and tools to utilize Julia's capabilities in biological science effectively and to demonstrate the gap. It paves the way for innovative solutions and discoveries in this rapidly evolving field. It encompasses an analysis of Julia's characteristics, packages, and performance compared to the other programming languages in this field. The initial part of this review discusses the key features of Julia, such as its dynamic and interactive nature, fast processing speed, ease of expression manipulation, user-friendly syntax, code readability, strong support for multiple dispatch, and advanced type system. It also explores Julia's capabilities in data analysis, visualization, machine learning, and algorithms, making it suitable for scientific applications. The next section emphasizes the importance of using Julia in biological research, highlighting its seamless integration with biological studies for data analysis, and computational biology. It also compares Julia with other programming languages commonly used in biological research through benchmarking and performance analysis. Additionally, it provides insights into future directions and potential challenges in Julia's applications in biology.
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Affiliation(s)
- Soumen Pal
- School of Mechanical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Manojit Bhattacharya
- Department of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore 756020, Odisha, India
| | - Snehasish Dash
- School of Mechanical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Sang-Soo Lee
- Institute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon, Gangwon-Do 24252, Republic of Korea.
| | - Chiranjib Chakraborty
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal 700126, India.
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Biswas S, Chung Y, Ramirez J, Wu H, Green WH. Predicting Critical Properties and Acentric Factors of Fluids Using Multitask Machine Learning. J Chem Inf Model 2023; 63:4574-4588. [PMID: 37487557 DOI: 10.1021/acs.jcim.3c00546] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
Knowledge of critical properties, such as critical temperature, pressure, density, as well as acentric factor, is essential to calculate thermo-physical properties of chemical compounds. Experiments to determine critical properties and acentric factors are expensive and time intensive; therefore, we developed a machine learning (ML) model that can predict these molecular properties given the SMILES representation of a chemical species. We explored directed message passing neural network (D-MPNN) and graph attention network as ML architecture choices. Additionally, we investigated featurization with additional atomic and molecular features, multitask training, and pretraining using estimated data to optimize model performance. Our final model utilizes a D-MPNN layer to learn the molecular representation and is supplemented by Abraham parameters. A multitask training scheme was used to train a single model to predict all the critical properties and acentric factors along with boiling point, melting point, enthalpy of vaporization, and enthalpy of fusion. The model was evaluated on both random and scaffold splits where it shows state-of-the-art accuracies. The extensive data set of critical properties and acentric factors contains 1144 chemical compounds and is made available in the public domain together with the source code that can be used for further exploration.
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Affiliation(s)
- Sayandeep Biswas
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Yunsie Chung
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Josephine Ramirez
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Haoyang Wu
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - William H Green
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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7
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Rehner P, Bauer G, Gross J. FeO s: An Open-Source Framework for Equations of State and Classical Density Functional Theory. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.2c04561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Affiliation(s)
- Philipp Rehner
- Energy and Process Systems Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Tannenstrasse 3, Zurich 8092, Switzerland
| | - Gernot Bauer
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70569, Germany
| | - Joachim Gross
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70569, Germany
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8
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Bell IH, Deiters UK. Superancillary Equations for Nonpolar Pure Fluids Modeled with the PC-SAFT Equation of State. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.2c02916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Ian H. Bell
- Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, Colorado80305, United States
| | - Ulrich K. Deiters
- Institute of Physical Chemistry, University of Cologne, 50939Köln, Germany
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9
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Walker PJ. Toward Advanced, Predictive Mixing Rules in SAFT Equations of State. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c03464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Pierre J. Walker
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California91125, United States
- Department of Chemical Engineering, Imperial College London, LondonSW7 2AZ, United Kingdom
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10
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Pribylov AA, Postnikov EB. Effects of mixing and molecular packing on the isobaric expansivity of mixtures of n-hexane and 1-hexanol as modelled by FT-EoS, PC-SAFT and SAFT- γ Mie. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.120165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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11
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de Hemptinne JC, Kontogeorgis GM, Dohrn R, Economou IG, ten Kate A, Kuitunen S, Fele Žilnik L, De Angelis MG, Vesovic V. A View on the Future of Applied Thermodynamics. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Georgios M. Kontogeorgis
- Center for Energy Resources Engineering (CERE), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby DK-2800, Denmark
| | - Ralf Dohrn
- Bayer AG, Process Technologies, Building E41, Leverkusen 51368, Germany
| | - Ioannis G. Economou
- Chemical Engineering Program, Texas A&M University at Qatar, Doha P.O. Box 23874, Qatar
| | | | - Susanna Kuitunen
- Neste Engineering Solutions Oy, P.O. Box 310, Porvoo FI-06101, Finland
| | - Ljudmila Fele Žilnik
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, Ljubljana 1001, Slovenia
| | - Maria Grazia De Angelis
- Institute for Materials and Processes, School of Engineering, University of Edinburgh, Sanderson Building, Edinburgh EH9 3FB, UK
- Department of Civil, Chemical, Environmental and Materials Engineering University of Bologna, Bologna 40131 Italy
| | - Velisa Vesovic
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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12
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Ylitalo AS, Chao H, Walker PJ, Crosthwaite J, Fitzgibbons TC, Ginzburg VG, Zhou W, Wang ZG, Di Maio E, Kornfield JA. Competition between CO 2-philicity and Mixing Entropy Leads to CO 2 Solubility Maximum in Polyether Polyols. Ind Eng Chem Res 2022; 61:12835-12844. [PMID: 36065446 PMCID: PMC9438450 DOI: 10.1021/acs.iecr.2c02396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 07/29/2022] [Accepted: 08/01/2022] [Indexed: 11/29/2022]
Affiliation(s)
- Andrew S. Ylitalo
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Huikuan Chao
- Dow, Inc., Midland, Michigan 48667, United States
| | - Pierre J. Walker
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | | | | | | | - Weijun Zhou
- Dow, Inc., Lake Jackson, Texas 77566, United States
| | - Zhen-Gang Wang
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Ernesto Di Maio
- Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale, University of Naples, Federico II, P. le Tecchio 80, 80125 Naples, Italy
| | - Julia A. Kornfield
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States
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13
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Ge K, Ji Y. A thermodynamic approach for predicting thermodynamic phase behaviors of pharmaceuticals in biorelevant media. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.117973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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