gels Review Computational Tools to Rationalize and Predict the Self-Assembly Behavior of Supramolecular Gels Ruben Van Lommel 1,2,* , Wim M. De Borggraeve 1 , Frank De Proft 2 and Mercedes Alonso 2,* 1 Molecular Design and Synthesis, Department of Chemistry, KU Leuven, Celestijnenlaan 200F Leuven Chem & Tech, P.O. Box 2404, 3001 Leuven, Belgium; [email protected] 2 Eenheid Algemene Chemie (ALGC), Department of Chemistry, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium; [email protected] * Correspondence: [email protected] (R.V.L.); [email protected] (M.A.) Abstract: Supramolecular gels form a class of soft materials that has been heavily explored by the chemical community in the past 20 years. While a multitude of experimental techniques has demonstrated its usefulness when characterizing these materials, the potential value of computational techniques has received much less attention. This review aims to provide a complete overview of studies that employ computational tools to obtain a better fundamental understanding of the self- assembly behavior of supramolecular gels or to accelerate their development by means of prediction. As such, we hope to stimulate researchers to consider using computational tools when investigating these intriguing materials. In the concluding remarks, we address future challenges faced by the field and formulate our vision on how computational methods could help overcoming them. Keywords: supramolecular gels; LMWG; computational chemistry; molecular dynamics; modeling; self-assembly Citation: Van Lommel, R.; De Borggraeve, W.M.; De Proft, F.; Alonso, M. Computational Tools to Rationalize and Predict the 1. Introduction Self-Assembly Behavior of Supramolecular gels, often referred to as molecular gels or low molecular weight Supramolecular Gels. Gels 2021, 7, 87. gels (LMWGs), are a type of soft material that mostly consists of two constituents: a https://doi.org/10.3390/gels7030087 solvent, which accounts for up to 99% of the material, and a small molecule termed a gelator. Although only present in small amounts, the gelator provides the material with Academic Editor: Pablo H. Di Chenna the typical viscoelastic gel properties, by forming a self-assembled network that spans and immobilizes the solvent [1–4]. While there is a large chemical diversity among reported Received: 27 May 2021 gelators, most of them rely on the ability to form intermolecular noncovalent interactions Accepted: 6 July 2021 Published: 9 July 2021 in an anisotropic fashion. Hence the term supramolecular gels. In the past decade, the field of supramolecular gels has reached its adolescent years, providing researchers with ample Publisher’s Note: MDPI stays neutral well-established experimental techniques to characterize and investigate these materials, with regard to jurisdictional claims in amongst others rheological measurements, various microscopy imaging techniques, NMR published maps and institutional affil- spectroscopy, UV-VIS spectroscopy, etc. [5–8]. Evidently, these experimental techniques iations. have played a critical part in establishing our current understanding and development of supramolecular gels and will remain essential in the forthcoming years. However, the macroscopic properties of these soft materials are governed by weak noncovalent interactions. Gaining direct insights into these interactions via wet-lab experi- ments is challenging. Fortunately, in the past, various computational methods and tools Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. have proven their usefulness when investigating noncovalent interactions in supramolec- This article is an open access article ular materials [9–11]. In this review, we set out to create awareness on the use of compu- distributed under the terms and tational chemistry within the field of supramolecular gels. The first part discusses how conditions of the Creative Commons computational methods can help to improve our understanding of supramolecular gels, Attribution (CC BY) license (https:// often complementing the observations from experimental techniques. Next, several recent creativecommons.org/licenses/by/ computational studies aiming to accelerate the development of supramolecular gels by 4.0/). a priori predictions are highlighted. In the concluding section, we look forward towards Gels 2021, 7, 87. https://doi.org/10.3390/gels7030087 https://www.mdpi.com/journal/gels Gels 2021, 7, x FOR PEER REVIEW 2 of 19 Gels 2021, 7, 87 2 of 18 priori predictions are highlighted. In the concluding section, we look forward towards the theopportunities opportunities and and challenges challenges that that remain remain in the in thefield field of supramolecular of supramolecular gels gels where where com- computationalputational methods methods can can be beof ofconsiderable considerable value. value. 2.2. Rationalizing Rationalizing Supramolecular Supramolecular Gelation Gelation GainingGaining a deepera deeper understanding understanding of supramolecularof supramolecular gels gels is not is onlynot only useful useful for scientific for scien- purposes,tific purposes, but it canbut alsoit can aid also in aid their in developmenttheir development and increase and increase their applicability.their applicability. To this To end,this several end, several computational computational techniques techniques have beenhave appliedbeen applied to acquire to acquire knowledge knowledge about about the conformationalthe conformational preference preference of gelators of gelators in a solvent in a environment,solvent environment, possible possible stacking modesstacking of the nano-architectures, the noncovalent interactions in and between gelator molecules modes of the nano-architectures, the noncovalent interactions in and between gelator mol- and additives, etc. Having said that, supramolecular gelation is a multiscale problem, with ecules and additives, etc. Having said that, supramolecular gelation is a multiscale prob- interactions occurring at the atom scale governing macroscale material properties [2,12]. As lem, with interactions occurring at the atom scale governing macroscale material proper- a result, different computational techniques with different levels of accuracy are required to ties [2,12]. As a result, different computational techniques with different levels of accuracy gain information at different scales (Figure1). In this section, an overview of computational are required to gain information at different scales (Figure 1). In this section, an overview methods employed to rationalize the gelation behavior is provided. While this section of computational methods employed to rationalize the gelation behavior is provided. is organized based on the scale and level of accuracy of the computational method, we While this section is organized based on the scale and level of accuracy of the computa- do mention that in order to obtain the most complete picture, a combination of these tional method, we do mention that in order to obtain the most complete picture, a combi- techniques integrated in a multiscale approach is desirable [13–15]. nation of these techniques integrated in a multiscale approach is desirable [13–15]. FigureFigure 1. 1.Computational Computational methods methods with with different different levels levels of of accuracy accuracy can can provide provide information information on on the the supramolecularsupramolecular gelation gelation behavior behavior at at different different length length and and time time scales. scales. 2.1.2.1. Static Static Quantum Quantum Mechanical Mechanical Calculations Calculations ComputationsComputations performed performed with with techniques techniques that that rely rely on quantumon quantum mechanics, mechanics, generally gener- yieldally highlyyield highly accurate accurate properties. properties. Even within Even within quantum quantum mechanical mechanical methods, methods, subdivisions subdi- ofvisions techniques of techniques can be made can be based made on based the manneron the manner in which in which electron electron correlation correlation effects ef- arefects taken are intotaken account into account [16]. [16]. This This means, means, however, however, that that they they also also require require a significanta significant amountamount of of computational computational power. power. Hence,Hence, quantumquantum mechanical calculations in in the the field field of ofsupramolecular supramolecular gels gels are are currently currently limited limited to st toatic static or short or short dynamic dynamic simulations simulations of single of singlegelator gelator molecules molecules or systems or systems of up of to up approximately to approximately 500 500heavy heavy atoms. atoms. Additionally, Additionally, sol- solventvent effects effects (if (if any) any) are are incl includeduded by implicit continuumcontinuum modelsmodels or or explicitly explicitly by by molecular molecular mechanicsmechanics methods methods (QM/MM). (QM/MM). Among Among the the many many quantum quantum mechanical mechanical theories theories available, available, densitydensity functional functional theory theory (DFT) (DFT) has has established established itself itself as as the the primary primary quantum quantum mechanical mechanical workhorseworkhorse to to investigate investigate supramolecular supramolecular systems systems [17 [17–19].–19]. The The popularity popularity of of DFT DFT can can be be attributedattributed to to its its favorable favorable