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Writing Theory and Modeling Papers For Langmuir – The Good, The Bad and The Ugly David S. Sholl, Zuihof Han, and Shu-Hong Yu Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.7b04236 • Publication Date (Web): 12 Jan 2018 Downloaded from http://pubs.acs.org on January 12, 2018
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LANGMUIR EDITORIAL Writing Theory and Modeling Papers For Langmuir – The Good, The Bad and The Ugly Han Zuilhof1,2, Shu-Hong Yu3, David S. Sholl4 1
School of Pharmaceutical Science & Technology, Health Science Platform, Tianjin University, 92 Weijin Road, Tianjin 300072, P.R. China 2 Laboratory of Organic Chemistry, Wageningen University, 6708 WE Wageningen, The Netherlands 3 Department of Chemistry, University of Science and Technology of China, Hefei 230026, P. R. China 4 School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0100 Langmuir has a long tradition of publishing excellent theory and modeling papers. As of the time of writing, for example, two modeling papers from 2013 are among the most cited 10 papers in Langmuir from that year [1,2] and the most cited paper from Langmuir in 2016 is a theory and modeling paper [3]. At the same time, many manuscripts using theory and modeling are submitted to Langmuir but are ultimately rejected. Although Langmuir has a mandate to publish the highest quality work of all kinds relevant to interface science, there are some issues that exist that are specific to considering work based on theory and modeling. In this Editorial, we give our perspectives as writers, readers and editors on how to write excellent theory and modeling papers for Langmuir. We hope these perspectives will be useful to authors and also to Langmuir’s reviewers. Who Is The Intended Audience? This is, of course, a question the authors of any manuscript should ask themselves. For Langmuir, the majority of readers are experimenters. Therefore excellence in a manuscript based on theory or modeling is defined at least in part by the influence that the work will have on the experimental community. This ‘aim to influence’ should be clear both in the style and the contents, guided by questions like the following: Are the manuscript’s purpose and central conclusion expressed in a way that is understandable and relevant to experimentalists working on similar physical systems? Will the work inspire or guide future experiments? Can the authors think of specific experimental researchers working in the area of Langmuir’s focus who would be interested enough in the outcomes to read and cite the manuscript? If any of these questions are answered negatively, it is likely that the manuscript is not well suited to Langmuir. It can, of course, still be a wonderful paper; there are assuredly modeling papers that do not answer these questions affirmatively and are nonetheless of huge value to the scientific community; many papers introducing new modeling methods fall into this category. There are, however, excellent journals such as the ACS Journal of Chemical Theory and Computation that exist as venues for work aimed predominately at readers from the modeling community. From the perspective of Langmuir (and, we suspect, many other chemistry journals), the potential for a manuscript to be appreciated by readers who identify themselves as experimenters is critical.
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Are Approximations and Limitations Clearly Described? A key difference between a manuscript describing experiments and a manuscript describing a theory or model is that experiments deal with direct measurements of physical reality while models are approximations of reality. In the best cases, modeling is insightful precisely because it uses well-chosen approximations to illuminate the central properties of a complex phenomenon or set of materials. In less effective instances, modeling is subject to the well-known information age adage “garbage in, garbage out”. One feature of an excellent modeling manuscript is that the approximations in each method are clearly stated and the resulting limitations in extending any conclusions to real materials are openly discussed. Hu et al. give an excellent example of clearly stating the assumptions in their models describing the meniscus shape of wetting liquids on structured surfaces [4]. What Physical Insight Is Gained? Computer simulations can generate powerful information about materials that have not (yet) been synthesized or at atomistic scales that cannot be readily interrogated experimentally. The fact that something can be quantified in a simulation, however, does not automatically make it interesting, even if it can be represented by a visually appealing color figure! When writing a modeling manuscript, it is helpful to continually ask what non-obvious physical insight can be derived from the results. The work of Basu et al. predicting that cholera toxin, while five-fold symmetric, first binds with three sites (rather than five) to sugars on a cell membrane is a good example of an insight of this type [5]. Excellent modeling papers that are suitable for Langmuir provide careful tests of specific hypotheses relevant to phenomena that can be directly tested in future experiments or point experimenters towards a path that will discover new materials or properties. Manuscripts that merely confirm existing understanding of well-known phenomena (“Our coarse-grained 2D lattice model shows that micelles are likely to form once a sufficient concentration of surfactants is reached”) are exceedingly unlikely to excite Langmuir’s reviewers or readers. Where Does Theory Touch Reality? Before a model can make meaningful predictions driving future experiments, the ability of the model (or more broadly, the class of simulation tools used by the model) to describe reality must be established. To achieve this important task, model results should be routinely validated by comparison with experimental results. In some cases this will involve performing calculations for well-defined examples before extending the calculations to the new situations or materials being studied. Hardy and Bock’s recent work on the identification of solvents for dispersing carbon nanotubes is one good example of careful validation of atomistic modeling with extensive experimental data [6]. Recent work by Armas-Perez et al. is an excellent example of using validation between multiple levels and modeling and experimental data [7]. There is a temptation in writing a modeling manuscript to focus on comparing results with other previous calculations. This kind of comparison should, of course, not be discouraged, but it is important to remember that comparing “simulation A” to “simulation B” cannot provide any information about whether these simulations say something meaningful about the real world. How Can Calculations Be Made Reproducible? Most researchers would view the necessity for high quality work to be reproducible. To distinguish science from mere opinion, a great deal of attention has been paid in recent years to
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challenges associated with reproducing published experimental results in science, including recent work on these issues in materials chemistry [8]. In many ways, modeling and simulation research should be more readily reproducible than physical experiments, because it typically relies on software that is widely available. A manuscript should of course report the name and version number of any software that was used, along with sufficient information that another experienced user of that software would not have to make guesses or choices about input parameters to repeat a calculation. However, this is often not sufficient for less experienced users and or interested experimentalists. Therefore we would strongly urge authors to make full use of Supporting Information. The ready availability and lack of any page limits of Supporting Information makes it straightforward to give readers access to input files, raw data and other relevant information. Supporting Information also provides a way for authors to describe tests that have been performed leading to selection of numerical parameters and approximations that were used for the primary calculations reported in a manuscript. A recent example of providing very extensive results from calculations in Supporting Information was given by Aoto et al. [9]. Examples that provide samples of code or input files in Supporting Information such as the work by Rangarajan et al. [10] can be even more useful to readers. Procedures are being developed in some fields for making working versions of codes available to readers [11]. Taking steps in this direction would strengthen theory and modeling papers in Langmuir. Summary We strongly urge authors to explicitly consider the questions posed above when writing a modeling or simulation manuscript for Langmuir so their readers can rephrase Kipling [12]: “Theory is feast, and test is best, but ever the twain shall meet”. We hope that these considerations will help authors to continue Langmuir’s long tradition of publishing excellent modeling, simulation and theory that pushes forward the boundaries of both scientific understanding and experimental practice.
References [1] F. Taherian, V. Marcon, N. F. A. van der Vegt and F. Leroy, What is the contact angle of water on graphene?, Langmuir 29 (2013) 1457-1465 [2] H. Heinz, T.-J. Lin, R. K. Mishra and F. S. Emami, Thermodynamically consistent force fields for the assembly of inorganic, organic and biological nanostructures: The INTERFACE force field, Langmuir 29 (2013) 1754-1765 [3] G. Trefalt, S. H. Behrens and M. Borkovec, Charge regulation in the electrical double layer: Ion adsorption and surface interactions, Langmuir, 32 (2016) 380-400 [4] H. Mu, M. Chakraborty, T. P. Allred, J. A. Weibel and S. V. Garimella, Multiscale modeling of the three-dimensional meniscus shape of a wetting liquid film on micro/nano-structured surfaces, Langmuir 33 (2017) 12028-12037 [5] I. Basu and C. Mukhopadhyay, Insights into binding of cholera toxin to GM1 containing membrane, Langmuir 30 2014, 15244−15252
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[6] A. Hardy and H. Bock, Toward high-throughput computational screening of carbon nanotube solvents, Langmuir 33 (2017) 12267-12275 [7] J. C. Armas-Perez, X. Li, J. A. Martinez-Gonzalez, C. Smith, J. P. Hernandez-Ortiz, P. F. Nealey and J. J. de Pablo, Langmuir 33 (2017) 12516 [8] J. Park, J. Howe and D. S. Sholl, How reproducible are adsorption isotherms in MOFs?, Chemistry of Materials, DOI: 10.1021/acs.chemmater.7b04287 [9] Y. A. Aoto, A. P. d. P. Batista, A. Köhn and A. G. S. de Oliveira-Filho, How to arrive at accurate benchmark values for transition metal compounds: computation or experiment?, J. Chem. Theory. Comput. 13 (2017) 5291 [10] S. Rangarajan, C. T. Maravelias and M. Mavrikakis, Sequential-optimized-based framework for robust modeling and design of heterogeneous catalytic systems, ACS Catalysis 121 (2017) 25487-25863 [11] A. Torfi, S. Y. Iranmanesh, N. Nasrabadi, J. Dawson, IEEE Access 5 (2017) 22081-22091 [12] Rudyard Kipling, “Barrack-room ballads” 1892: "Oh, East is East, and West is West, and never the twain shall meet.".
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