Comput., 2018, 14, 543-556) to evaluate a large number of dimer interaction energies. The resulting quantum mechanically derived FFs are then used in extensive molecular dynamics simulations, in order to evaluate a number of thermodynamic, structural, and dynamic properties of the heterocycle's gas and liquid phases. The comparison with the available experimental data is good and furnishes a validation of the presented approach, which can be confidently exploited for the design of novel and more complex materials.

Noncovalent interactions between homodimers of several aromatic heterocycles (pyrrole, furan, thiophene, pyridine, pyridazine, pyrimidine, and pyrazine) are investigated at the ab initio level, employing the Möller-Plesset second-order perturbation theory, coupled with small Gaussian basis sets (6-31G* and 6-31G**) with specifically tuned polarization exponents. The latter are modified using a systematic and automated procedure, the MP2 approach, based on a comparison with high level CCSD(T) calculations extrapolated to a complete basis set. The MP2 results achieved with the modified 6-31G** basis set show an excellent agreement with CCSD(T)/CBS reference energies, with a standard deviation less than 0.3 kcal/mol. Exploiting its low computational cost, the MP2 approach is then used to explore sections of the intermolecular energy of the considered homodimers, with the aim of rationalizing the results. It is found that the direct electrostatic interaction between the monomers electron clouds is at the origin of some observed features, and in many cases multipoles higher than dipole play a relevant role, although often the interplay with other contributions to the noncovalent forces (as for instance induction, π-π or XH-π interactions) makes a simple rationalization rather difficult.

The reliability of molecular dynamics (MD) simulations in predicting macroscopic properties of complex fluids and soft materials, such as liquid crystals, colloidal suspensions, or polymers, relies on the accuracy of the adopted force field (FF). We present an automated protocol to derive specific and accurate FFs, fully based on ab initio quantum mechanical (QM) data. The integration of the JOYCE and PICKY procedures, recently proposed by our group to provide an accurate description of simple liquids, is here extended to larger molecules, capable of exhibiting more complex fluid phases. While the standard JOYCE protocol is employed to parameterize the intramolecular FF term, a new automated procedure is here proposed to handle the computational cost of the QM calculations required for the parameterization of the intermolecular FF term. The latter is thus obtained by integrating the old PICKY procedure with a fragmentation reconstruction method (FRM) that allows for a reliable, yet computationally feasible sampling of the intermolecular energy surface at the QM level. The whole FF parameterization protocol is tested on a benchmark liquid crystal, and the performances of the resulting quantum mechanically derived (QMD) FF were compared with those delivered by a general-purpose, transferable one, and by the third, "hybrid" FF, where only the bonded terms were refined against QM data. Lengthy atomistic MD simulations are carried out with each FF on extended 5CB systems in both isotropic and nematic phases, eventually validating the proposed protocol by comparing the resulting macroscopic properties with other computational models and with experiments. The QMD-FF yields the best performances, reproducing both phases in the correct range of temperatures and well describing their structure, dynamics, and thermodynamic properties, thus providing a clear protocol that may be explored to predict such properties on other complex fluids or soft materials.

De novo design of self-assembled materials hinges upon our ability to relate macroscopic properties to individual building blocks, thus characterizing in such supramolecular architectures a wide range of observables at varied time/length scales. This work demonstrates that quantum mechanical derived force fields (QMD-FFs) do satisfy this requisite and, most importantly, do so in a predictive manner. To this end, a specific FF, built solely based on the knowledge of the target molecular structure, is employed to reproduce the spontaneous transition to an ordered liquid crystal phase. The simulations deliver a multiscale portrait of such self-assembly processes, where conformational changes within the individual building blocks are intertwined with a 200 ns ensemble reorganization. The extensive characterization provided not only is in quantitative agreement with the experiment but also connects the time/length scales at which it was performed. Realizing QMD-FF predictive power and unmatched accuracy stands as an important leap forward for the bottom-up design of advanced supramolecular materials.

The wide range of time/length scales covered by self-assembly in soft matter makes molecular dynamics (MD) the ideal candidate for simulating such a supramolecular phenomenon at an atomistic level. However, the reliability of MD outcomes heavily relies on the accuracy of the adopted force-field (FF). The spontaneous re-ordering in liquid crystalline materials stands as a clear example of such collective self-assembling processes, driven by a subtle and delicate balance between supramolecular interactions and single-molecule flexibility. General-purpose transferable FFs often dramatically fail to reproduce such complex phenomena, for example, the error on the transition temperatures being larger than 100 K. Conversely, quantum-mechanically derived force-fields (QMD-FFs), specifically tailored for the target system, were recently shown (J. Phys. Chem. Lett. 2022, 13, 243) to allow for the required accuracy as they not only well reproduced transition temperatures but also yielded a quantitative agreement with the experiment on a wealth of structural, dynamic, and thermodynamic properties. The main drawback of this strategy stands in the computational burden connected to the numerous quantum mechanical (QM) calculations usually required for a target-specific parameterization, which has undoubtedly hampered the routine application of QMD-FFs. In this work, we propose a fragment-based strategy to extend the applicability of QMD-FFs, in which the amount of QM calculations is significantly reduced, being a single-molecule-optimized geometry and its Hessian matrix the only QM information required. To validate this route, a new FF is assembled for a large mesogen, exploiting the parameters obtained for two smaller liquid crystalline molecules, in this and previous work. Lengthy MD simulations are carried out with the new transferred QMD-FF, observing again a spontaneous re-orientation in the correct range of temperatures, with good agreement with the available experimental measures. The present results strongly suggest that a partial transfer of QMD-FF parameters can be invoked without a significant loss of accuracy, thus paving the way to exploit the method’s intrinsic predictive capabilities in the simulation of novel soft materials.

The Spin Component Scaled (SCS) MP2 method using a reduced and optimized basis set (scs-mp2 mod ) is employed to compute the interaction energies of nine homo-dimers, formed by aromatic hetero-cyclic molecules (pyrrole, furan, thiophene, oxazole, isoxazole, pyridine, pyridazine, pyrimidine and pyrazine). The coefficients of the same-spin and opposite-spin correlation energies and the GTO polarization exponents of the 6-31G** basis set are simultaneously optimized in order to minimize the energy differences with respect to the CCSD(T) reference interaction energies, extrapolated to complete basis set. It is demonstrated that the optimization of the spin scale factors leads to a noticeable improvement of the accuracy with a root mean square deviation less than 0.1 kcal/mol and a largest unsigned deviation smaller than 0.25 kcal/mol. The pyrrole dimer provides an exception, with slightly higher deviation from the reference data. Given the high benefit in terms of computational time with respect to the CCSD(T) technique and the small loss of accuracy, the scs-mp2 mod method appears to be particularly indicated for extensive sampling of intermolecular potential energy surfaces at a quantum mechanical level. Within this framework, the results of exponents and scaling factors optimization for the whole set of molecules are again accurate, showing a good level of transferability to this class of molecules.

No abstract

This study addresses the strategies used by students to develop a design brief during the 2018 edition of the Global Studio, a cross-institutional project. In the Global Studio, students from different universities around the world work in paired teams simultaneously as clients and designers. In 2018, the theme was "local mobilities", challenging design students to propose a solution for a local problem presented by their counterparts. Then the teams were asked to define an initial problem and prepare their design brief. This process involved common design activities and techniques such as contextual research, desktop research, and problem definition. The design briefs were published at their counterparts' blogs and analysed before the teams started their work as designers. Three teams from Brazil, worked with two teams from Turkey and one team from Japan. The analysis of how these students designed their design brief was the main objective of this study. The study adopted the following methods: observations, document analysis and interviews. Results demonstrated different levels of expertise and experience across teams. They suggest that strategies employed are associated both to individual backgrounds and to institutional effects.