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Al-Awad AS, Batet L, Rives R, Sedano L. Stochastic computer experiments of the thermodynamic irreversibility of bulk nanobubbles in supersaturated and weak gas-liquid solutions. J Chem Phys 2024; 161:024503. [PMID: 38984961 DOI: 10.1063/5.0204665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 06/24/2024] [Indexed: 07/11/2024] Open
Abstract
Spontaneous gas-bubble nucleation in weak gas-liquid solutions has been a challenging topic in theory, experimentation, and computer simulations. In analogy with recent advances in crystallization and droplet formation studies, the diffusive-shielding stabilization and thermodynamic irreversibility of bulk nanobubble (bNB) mechanisms are revisited and deployed to characterize nucleation processes in a stochastic framework of computer experiments using the large-scale atomic/molecular massively parallel simulator code. Theoretical bases, assumptions, and limitations underlying the irreversibility hypothesis of bNBs, and their computational counterparts, are extensively described and illustrated. In essence, it is established that the irreversibility hypothesis can be numerically investigated by converging the system volume (due to the finiteness of interatomic forces) and the initial dissolved-gas concentration in the solution (due to the single-bNB limitation). Helium nucleation in liquid Pb17Li alloy is selected as a representative case study, where it exhibits typical characteristics of noble-gas/liquid-metal systems. The proposed framework lays down the bases on which the stability of gas-bNBs in weak and supersaturated gas-liquid solutions can be inferred and explained from a novel perspective. In essence, it stochastically marches toward a unique irreversible state along out-of-equilibrium nucleation/growth trajectories. Moreover, it does not attempt to characterize the interface or any interface-related properties, neither theoretically nor computationally. It was concluded that bNBs of a few tens of He-atoms are irreversible when dissolved-He concentrations in the weak gas-liquid solution are at least ∼50 and ∼105 mol m-3 at 600 and 1000 K (and ∼80 MPa), respectively, whereas classical molecular dynamics -estimated solubilities are at least two orders of magnitude smaller.
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Affiliation(s)
- Abdulrahman S Al-Awad
- Department of Physics, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), Barcelona 08028, Spain
| | - Lluis Batet
- Department of Physics, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), Barcelona 08028, Spain
| | - Ronny Rives
- Department of Physics, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), Barcelona 08028, Spain
| | - Luis Sedano
- Department of Physics, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), Barcelona 08028, Spain
- Instituto de Ciencia de Materiales de Barcelona (ICMAB/CSIC), Bellaterra 08193, Spain
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Karmakar T, Finney AR, Salvalaglio M, Yazaydin AO, Perego C. Non-Equilibrium Modeling of Concentration-Driven processes with Constant Chemical Potential Molecular Dynamics Simulations. Acc Chem Res 2023; 56:1156-1167. [PMID: 37120847 DOI: 10.1021/acs.accounts.2c00811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
ConspectusConcentration-driven processes in solution, i.e., phenomena that are sustained by persistent concentration gradients, such as crystallization and surface adsorption, are fundamental chemical processes. Understanding such phenomena is crucial for countless applications, from pharmaceuticals to biotechnology. Molecular dynamics (MD), both in- and out-of-equilibrium, plays an essential role in the current understanding of concentration-driven processes. Computational costs, however, impose drastic limitations on the accessible scale of simulated systems, hampering the effective study of such phenomena. In particular, due to these size limitations, closed system MD of concentration-driven processes is affected by solution depletion/enrichment that unavoidably impacts the dynamics of the chemical phenomena under study. As a notable example, in simulations of crystallization from solution, the transfer of monomers between the liquid and crystal phases results in a gradual depletion/enrichment of solution concentration, altering the driving force for phase transition. In contrast, this effect is negligible in experiments, given the macroscopic size of the solution volume. Because of these limitations, accurate MD characterization of concentration-driven phenomena has proven to be a long-standing simulation challenge. While disparate equilibrium and nonequilibrium simulation strategies have been proposed to address the study of such processes, the methodologies are in continuous development.In this context, a novel simulation technique named constant chemical potential molecular dynamics (CμMD) was recently proposed. CμMD employs properly designed, concentration-dependent external forces that regulate the flux of solute species between selected subregions of the simulation volume. This enables simulations of systems under a constant chemical drive in an efficient and straightforward way. The CμMD scheme was originally applied to the case of crystal growth from solution and then extended to the simulation of various physicochemical processes, resulting in new variants of the method. This Account illustrates the CμMD method and the key advances enabled by it in the framework of in silico chemistry. We review results obtained in crystallization studies, where CμMD allows growth rate calculations and equilibrium shape predictions, and in adsorption studies, where adsorption thermodynamics on porous or solid surfaces was correctly characterized via CμMD. Furthermore, we will discuss the application of CμMD variants to simulate permeation through porous materials, solution separation, and nucleation upon fixed concentration gradients. While presenting the numerous applications of the method, we provide an original and comprehensive assessment of concentration-driven simulations using CμMD. To this end, we also shed light on the theoretical and technical foundations of CμMD, underlining the novelty and specificity of the method with respect to existing techniques while stressing its current limitations. Overall, the application of CμMD to a diverse range of fields provides new insight into many physicochemical processes, the in silico study of which has been hitherto limited by finite-size effects. In this context, CμMD stands out as a general-purpose method that promises to be an invaluable simulation tool for studying molecular-scale concentration-driven phenomena.
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Affiliation(s)
- Tarak Karmakar
- Department of Chemistry, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi 110016, India
| | - Aaron R Finney
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, United Kingdom
| | - Matteo Salvalaglio
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, United Kingdom
| | - A Ozgur Yazaydin
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, United Kingdom
| | - Claudio Perego
- Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, via la Santa 1, 6962 Lugano-Viganello, Switzerland
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Blow KE, Quigley D, Sosso GC. The seven deadly sins: When computing crystal nucleation rates, the devil is in the details. J Chem Phys 2021; 155:040901. [PMID: 34340373 DOI: 10.1063/5.0055248] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model-let alone to actually understand-be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavor almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects, such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.
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Affiliation(s)
- Katarina E Blow
- Department of Physics, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - David Quigley
- Department of Physics, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Gabriele C Sosso
- Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
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Karmakar T, Piaggi PM, Parrinello M. Molecular Dynamics Simulations of Crystal Nucleation from Solution at Constant Chemical Potential. J Chem Theory Comput 2019; 15:6923-6930. [DOI: 10.1021/acs.jctc.9b00795] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Tarak Karmakar
- Department of Chemistry and Applied Biosciences, ETH Zürich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Facoltà di Informatica, Istituto di Scienze Computationali, Università della Svizzera Italiana, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
| | - Pablo M. Piaggi
- Department of Chemistry and Applied Biosciences, ETH Zürich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Facoltà di Informatica, Istituto di Scienze Computationali, Università della Svizzera Italiana, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
| | - Michele Parrinello
- Department of Chemistry and Applied Biosciences, ETH Zürich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Facoltà di Informatica, Istituto di Scienze Computationali, Università della Svizzera Italiana, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
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Schmid R, Nielaba P. Stability of nanoparticles in solution: A statistical description of crystallization as a finite particle size effect in a lattice-gas model. J Chem Phys 2019; 150:054504. [DOI: 10.1063/1.5063665] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Ralf Schmid
- Department of Physics, University of Konstanz, D-78457 Konstanz, Germany
| | - Peter Nielaba
- Department of Physics, University of Konstanz, D-78457 Konstanz, Germany
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6
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Patel LA, Kindt JT. Simulations of NaCl Aggregation from Solution: Solvent Determines Topography of Free Energy Landscape. J Comput Chem 2018; 40:135-147. [DOI: 10.1002/jcc.25554] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 07/10/2018] [Accepted: 07/11/2018] [Indexed: 11/10/2022]
Affiliation(s)
- Lara A. Patel
- Department of Chemistry; Emory University; 1515 Dickey Drive, Atlanta Georgia 30322
| | - James T. Kindt
- Department of Chemistry; Emory University; 1515 Dickey Drive, Atlanta Georgia 30322
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7
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Liu C, Wood GPF, Santiso EE. Modelling nucleation from solution with the string method in the osmotic ensemble. Mol Phys 2018. [DOI: 10.1080/00268976.2018.1482016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- Chengxiang Liu
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA
| | | | - Erik E. Santiso
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA
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8
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Karmakar T, Piaggi PM, Perego C, Parrinello M. A Cannibalistic Approach to Grand Canonical Crystal Growth. J Chem Theory Comput 2018; 14:2678-2683. [DOI: 10.1021/acs.jctc.8b00191] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Tarak Karmakar
- Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Facoltià di Informatica, Instituto di Scienze Computationali, Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
| | - Pablo M. Piaggi
- Theory and Simulation of Materials (THEOS), École Polytechnique Fiédérale de Lausanne, CH-1015 Lausanne, Switzerland
- Facoltià di Informatica, Instituto di Scienze Computationali, Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
| | - Claudio Perego
- Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Facoltià di Informatica, Instituto di Scienze Computationali, Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Polymer Theory Department, Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
| | - Michele Parrinello
- Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
- Facoltià di Informatica, Instituto di Scienze Computationali, Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900, Lugano, Ticino, Switzerland
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9
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Poon GG, Lemke T, Peter C, Molinero V, Peters B. Soluble Oligomeric Nucleants: Simulations of Chain Length, Binding Strength, and Volume Fraction Effects. J Phys Chem Lett 2017; 8:5815-5820. [PMID: 29116791 DOI: 10.1021/acs.jpclett.7b02651] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Recent theories and simulations suggest that molecular additives can bind to the surfaces of nuclei, lower the surface energy, and accelerate nucleation. Experiments have shown that oligomeric and polymeric additives can also modify nucleation rates of proteins, ice, and minerals; however, general design principles for oligomeric or polymeric promoters do not yet exist. Here we investigate oligomeric additives for which each segment of the oligomer can bind to surfaces of nuclei. We use semigrand canonical Monte Carlo simulations in a Potts lattice gas model to study the effects of oligomer chain length, volume fraction, and binding strength. We find that increasing each of those parameters lowers the nucleation barrier. At extremely low oligomer concentrations, the nucleation kinetics can be modeled as though each oligomer is a heterogeneous nucleation site in solution.
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Affiliation(s)
- Geoffrey G Poon
- Department of Chemical Engineering, University of California , Santa Barbara, California 93106, United States
| | - Tobias Lemke
- Department of Chemistry, University of Konstanz , Konstanz 78457, Germany
| | - Christine Peter
- Department of Chemistry, University of Konstanz , Konstanz 78457, Germany
| | - Valeria Molinero
- Department of Chemistry, The University of Utah , Salt Lake City, Utah 84112, United States
| | - Baron Peters
- Department of Chemical Engineering, University of California , Santa Barbara, California 93106, United States
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10
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Patel LA, Kindt JT. Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases. J Chem Theory Comput 2017; 13:1023-1033. [DOI: 10.1021/acs.jctc.6b01237] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Lara A. Patel
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - James T. Kindt
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States
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11
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Lifanov Y, Vorselaars B, Quigley D. Nucleation barrier reconstruction via the seeding method in a lattice model with competing nucleation pathways. J Chem Phys 2016; 145:211912. [DOI: 10.1063/1.4962216] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Affiliation(s)
- Yuri Lifanov
- Centre for Complexity Science, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Bart Vorselaars
- School of Mathematics and Physics, University of Lincoln, Lincolnshire LN6 7TS, United Kingdom
| | - David Quigley
- Department of Physics and Centre for Scientific Computing, University of Warwick, Coventry CV4 7AL, United Kingdom
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12
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Sosso G, Chen J, Cox SJ, Fitzner M, Pedevilla P, Zen A, Michaelides A. Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations. Chem Rev 2016; 116:7078-116. [PMID: 27228560 PMCID: PMC4919765 DOI: 10.1021/acs.chemrev.5b00744] [Citation(s) in RCA: 369] [Impact Index Per Article: 46.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Indexed: 11/28/2022]
Abstract
The nucleation of crystals in liquids is one of nature's most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insights into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that, in the past few decades, have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state-of-the-art computational methods by reviewing simulations of such processes as ice nucleation and the crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insights into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that, as a result, the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that, by improving (i) existing interatomic potentials and (ii) currently available enhanced sampling methods, the community can move toward accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments.
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Affiliation(s)
- Gabriele
C. Sosso
- Thomas Young Centre, London
Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street WC1E
6BT London, U.K.
| | - Ji Chen
- Thomas Young Centre, London
Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street WC1E
6BT London, U.K.
| | | | - Martin Fitzner
- Thomas Young Centre, London
Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street WC1E
6BT London, U.K.
| | - Philipp Pedevilla
- Thomas Young Centre, London
Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street WC1E
6BT London, U.K.
| | - Andrea Zen
- Thomas Young Centre, London
Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street WC1E
6BT London, U.K.
| | - Angelos Michaelides
- Thomas Young Centre, London
Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street WC1E
6BT London, U.K.
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13
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He X, Shen Y, Hung FR, Santiso EE. Molecular simulation of homogeneous nucleation of crystals of an ionic liquid from the melt. J Chem Phys 2015; 143:124506. [PMID: 26429023 DOI: 10.1063/1.4931654] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The homogeneous nucleation of crystals of the ionic liquid [dmim(+)][Cl(-)] from its supercooled liquid phase in the bulk (P = 1 bar, T = 340 K, representing a supercooling of 58 K) was studied using molecular simulations. The string method in collective variables [Maragliano et al., J. Chem. Phys. 125, 024106 (2006)] was used in combination with Markovian milestoning with Voronoi tessellations [Maragliano et al., J. Chem. Theory Comput. 5, 2589-2594 (2009)] and order parameters for molecular crystals [E. E. Santiso and B. L. Trout, J. Chem. Phys. 134, 064109 (2011)] to sketch a minimum free energy path connecting the supercooled liquid and the monoclinic crystal phases, and to determine the free energy and the rates involved in the homogeneous nucleation process. The physical significance of the configurations found along this minimum free energy path is discussed with the help of calculations based on classical nucleation theory and with additional simulation results obtained for a larger system. Our results indicate that, at a supercooling of 58 K, the liquid has to overcome a free energy barrier of the order of 60 kcal/mol and to form a critical nucleus with an average size of about 3.6 nm, before it reaches the thermodynamically stable crystal phase. A simulated homogeneous nucleation rate of 5.0 × 10(10) cm(-3) s(-1) was obtained for our system, which is in reasonable agreement with experimental and simulation rates for homogeneous nucleation of ice at similar degrees of supercooling. This study represents our first step in a series of studies aimed at understanding the nucleation and growth of crystals of organic salts near surfaces and inside nanopores.
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Affiliation(s)
- Xiaoxia He
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - Yan Shen
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - Francisco R Hung
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - Erik E Santiso
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, USA
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Zimmermann NER, Vorselaars B, Quigley D, Peters B. Nucleation of NaCl from Aqueous Solution: Critical Sizes, Ion-Attachment Kinetics, and Rates. J Am Chem Soc 2015; 137:13352-61. [DOI: 10.1021/jacs.5b08098] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
| | - Bart Vorselaars
- Department
of Physics and Centre for Scientific Computing, University of Warwick, Coventry, CV4 7AL, U.K
| | - David Quigley
- Department
of Physics and Centre for Scientific Computing, University of Warwick, Coventry, CV4 7AL, U.K
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15
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Poon GG, Seritan S, Peters B. A design equation for low dosage additives that accelerate nucleation. Faraday Discuss 2015; 179:329-41. [DOI: 10.1039/c4fd00226a] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Additives are used to control nucleation in many natural and industrial environments. However, the mechanisms by which additives inhibit or accelerate solute precipitate nucleation are not well understood. We propose an equation that predicts changes in nucleation barriers based on the adsorption properties and concentrations of trace additives. The equation shows that nucleant efficacy depends on the product of an adsorption equilibrium constant and the reduction in interfacial tension. Moreover, the two factors that determine the potency of additives are related to each other, suggesting that assays of just one property might facilitate additive design. We test the design equation for a Potts lattice gas model with surfactant-like additives in addition to solutes and solvents.
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Affiliation(s)
- Geoffrey G. Poon
- Department of Chemical Engineering
- University of California
- Santa Barbara
- USA
| | - Stefan Seritan
- Department of Chemical Engineering
- University of California
- Santa Barbara
- USA
| | - Baron Peters
- Department of Chemical Engineering
- University of California
- Santa Barbara
- USA
- Department of Chemistry
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16
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Craven GT, Popov AV, Hernandez R. Effective Surface Coverage of Coarse-Grained Soft Matter. J Phys Chem B 2014; 118:14092-102. [DOI: 10.1021/jp505207h] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Galen T. Craven
- Center for Computational
Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
| | - Alexander V. Popov
- Center for Computational
Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
| | - Rigoberto Hernandez
- Center for Computational
Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
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