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[AT17]

Michael P. Allen and Dominic J. Tildesley. Computer Simulation of Liquids (second edition). Oxford University Press, 2017. ISBN 9780198803195. doi:10.1093/oso/9780198803195.001.0001.

[BUNO22]

Hiromi Baba, Ryo Urano, Tetsuro Nagai, and Susumu Okazaki. Prediction of self-diffusion coefficients of chemically diverse pure liquids by all-atom molecular dynamics simulations. J. Comput. Chem., 43(28):1892–1900, 2022. doi:10.1002/jcc.26975.

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M. S. Bartlett. Introduction to Stochastic Processes With Special Reference to Methods and Applications. Cambridge University Press, 1980. ISBN 9780521215855.

[BS13]

Joseph E. Basconi and Michael R. Shirts. Effects of temperature control algorithms on transport properties and kinetics in molecular dynamics simulations. J. Chem. Theory Comput., 9(7):2887–2899, 2013. doi:10.1021/ct400109a.

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J. O'M. Bockris and G. W. Hooper. Self-diffusion in molten alkali halides. Discuss. Faraday Soc., 32:218–236, 1961. doi:10.1039/DF9613200218.

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Paul Boone, Hasan Babaei, and Christopher E. Wilmer. Heat flux for many-body interactions: corrections to lammps. J. Chem. Theory Comput., 15(10):5579–5587, August 2019. URL: http://dx.doi.org/10.1021/acs.jctc.9b00252, doi:10.1021/acs.jctc.9b00252.

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Loris Ercole, Aris Marcolongo, and Stefano Baroni. Accurate thermal conductivities from optimally short molecular dynamics simulations. Sci. Rep., 7:15835, 2017. doi:10.1038/s41598-017-15843-2.

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Daan Frenkel and Berend Smit. Understanding Molecular Simulation. Elsevier, 2002. ISBN 9780122673511. doi:10.1016/b978-0-12-267351-1.x5000-7.

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Federico Grasselli and Stefano Baroni. Topological quantization and gauge invariance of charge transport in liquid insulators. Nat. Phys., 15(9):967–972, 2019. doi:10.1038/s41567-019-0562-0.

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Jean-Pierre Hansen and Ian R. McDonald. Theory of Simple Liquids (Fourth Edition). Academic Press, 2013. ISBN 978-0-12-387032-2. doi:10.1016/B978-0-12-387032-2.00013-1.

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Eugene Helfand. Transport coefficients from dissipation in a canonical ensemble. Phys. Rev., 119(1):1–9, 1960. doi:10.1103/physrev.119.1.

[JWB+19]

Seyed Hossein Jamali, Ludger Wolff, Tim M. Becker, Mariëtte de Groen, Mahinder Ramdin, Remco Hartkamp, André Bardow, Thijs J. H. Vlugt, and Othonas A. Moultos. Octp: a tool for on-the-fly calculation of transport properties of fluids with the order-nalgorithm in lammps. J. Chem. Inf. Model., 59(4):1290–1294, February 2019. URL: http://dx.doi.org/10.1021/acs.jcim.8b00939, doi:10.1021/acs.jcim.8b00939.

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[KGL+22]

Qia Ke, Xiaoting Gong, Shouwei Liao, Chongxiong Duan, and Libo Li. Effects of thermostats/barostats on physical properties of liquids by molecular dynamics simulations. J. Mol. Liq., 365:120116, November 2022. URL: http://dx.doi.org/10.1016/j.molliq.2022.120116, doi:10.1016/j.molliq.2022.120116.

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A. Kratzer. Die ultraroten rotationsspektren der halogenwasserstoffe. Z. Phys., 3(5):289–307, 1920. doi:10.1007/bf01327754.

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Ryogo Kubo. Statistical-mechanical theory of irreversible processes. i. general theory and simple applications to magnetic and conduction problems. J. Phys. Soc. Jpn., 12(6):570–586, 1957. doi:10.1143/JPSJ.12.570.

[Mac05]

David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press, 2005. ISBN 9780521642989.

[MMC+20]

Edward J. Maginn, Richard A. Messerly, Daniel J. Carlson, Daniel R. Roe, and J. Richard Elliot. Best practices for computing transport properties 1. self-diffusivity and viscosity from equilibrium molecular dynamics [article v1.0]. Living J. Comput. Mol. Sci., 2(1):6324, 2020. doi:10.33011/livecoms.1.1.6324.

[MLK04a]

Karsten Meier, Arno Laesecke, and Stephan Kabelac. Transport coefficients of the lennard-jones model fluid. i. viscosity. J. Chem. Phys., 121(8):3671–3687, 2004. doi:10.1063/1.1770695.

[MLK04b]

Karsten Meier, Arno Laesecke, and Stephan Kabelac. Transport coefficients of the lennard-jones model fluid. iii. bulk viscosity. J. Chem. Phys., December 2004. URL: http://dx.doi.org/10.1063/1.1828040, doi:10.1063/1.1828040.

[MFF23]

Luís Fernando Mercier Franco and Abbas Firoozabadi. Computation of shear viscosity by a consistent method in equilibrium molecular dynamics simulations: applications to 1-decene oligomers. J. Phys. Chem. B, 127(46):10043–10051, 2023. doi:10.1021/acs.jpcb.3c04994.

[Mil11]

Russel B. Millar. Maximum Likelihood Estimation and Inference With Examples in R, SAS and ADMB. John Wiley & Sons, 2011. ISBN 978-0-470-09482-2.

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A.V. Oppenheim, R.W. Schafer, and J.R. Buck. Discrete-time Signal Processing. Prentice Hall, 1999. ISBN 9780137549207.

[PDGB25]

Paolo Pegolo, Enrico Drigo, Federico Grasselli, and Stefano Baroni. Transport coefficients from equilibrium molecular dynamics. J. Chem. Phys., February 2025. URL: http://dx.doi.org/10.1063/5.0249677, doi:10.1063/5.0249677.

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M B Priestley. Spectral analysis and time series, two-volume set: Volume 1-2. Academic Press, October 1982. ISBN 9780125649223.

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Carl Edward Rasmussen and Christopher K I Williams. Gaussian processes for machine learning. MIT Press, November 2005. ISBN 0-262-18253-X.

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G. Rowlands and J. C. Sprott. A simple diffusion model showing anomalous scaling. Phys. Plasmas, 2008. doi:10.1063/1.2969429.

[SSWZ20]

Yunqi Shao, Keisuke Shigenobu, Masayoshi Watanabe, and Chao Zhang. Role of viscosity in deviations from the nernst–einstein relation. J. Phys. Chem. B, 124(23):4774–4780, 2020. doi:10.1021/acs.jpcb.0c02544.

[SS17]

R.H. Shumway and D.S. Stoffer. Time Series Analysis and Its Applications: With R Examples. Springer International Publishing, 2017. ISBN 9783319524528.

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A. Sokal. Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms, pages 131–192. Springer US, Boston, MA, 1997. doi:10.1007/978-1-4899-0319-8_6.

[SMKO19]

Donatas Surblys, Hiroki Matsubara, Gota Kikugawa, and Taku Ohara. Application of atomic stress to compute heat flux via molecular dynamics for systems with many-body interactions. Phys. Rev., May 2019. URL: http://dx.doi.org/10.1103/PhysRevE.99.051301, doi:10.1103/physreve.99.051301.

[SMKO21]

Donatas Surblys, Hiroki Matsubara, Gota Kikugawa, and Taku Ohara. Methodology and meaning of computing heat flux via atomic stress in systems with constraint dynamics. J. Appl. Phys., December 2021. URL: http://dx.doi.org/10.1063/5.0070930, doi:10.1063/5.0070930.

[TF64]

M.P. Tosi and F.G. Fumi. Ionic sizes and born repulsive parameters in the nacl-type alkali halides—ii: the generalized huggins-mayer form. J. Phys. Chem. Solids, 25(1):45–52, 1964. doi:10.1016/0022-3697(64)90160-X.

[Tuc23]

Mark E. Tuckerman. Statistical Mechanics: Theory and Molecular Simulation. Oxford University Press, 2023. ISBN 9780198825562. doi:10.1093/oso/9780198825562.001.0001.

[VSG07a]

S. Viscardy, J. Servantie, and P. Gaspard. Transport and helfand moments in the lennard-jones fluid. i. shear viscosity. J. Chem. Phys., 126(18):184512, 2007. doi:10.1063/1.2724820.

[VSG07b]

S. Viscardy, J. Servantie, and P. Gaspard. Transport and helfand moments in the lennard-jones fluid. ii. thermal conductivity. J. Chem. Phys., 126(18):184513, 2007. doi:10.1063/1.2724821.

[WDZ+20]

Haimeng Wang, Ryan S. DeFever, Yong Zhang, Fei Wu, Santanu Roy, Vyacheslav S. Bryantsev, Claudio J. Margulis, and Edward J. Maginn. Comparison of fixed charge and polarizable models for predicting the structural, thermodynamic, and transport properties of molten alkali chlorides. J. Chem. Phys., 153(21):214502, 12 2020. doi:10.1063/5.0023225.

[WSLY14]

Jia Wang, Ze Sun, Guimin Lu, and Jianguo Yu. Molecular dynamics simulations of the local structures and transport coefficients of molten alkali chlorides. J. Phys. Chem. B, 118(34):10196–10206, 2014. doi:10.1021/jp5050332.

[YH04]

In-Chul Yeh and Gerhard Hummer. System-size dependence of diffusion coefficients and viscosities from molecular dynamics simulations with periodic boundary conditions. J. Phys. Chem. B, 108(40):15873–15879, 2004. doi:10.1021/jp0477147.

[ZZF22]

Lili Zhao, Minna Zhi, and Gernot Frenking. The strength of a chemical bond. Int. J. Quantum Chem., 122(8):e26773, 2022. doi:10.1002/qua.26773.