Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-Optimization.

Quality diversity algorithms can be used to efficiently create a diverse set of solutions to inform engineers' intuition. But quality diversity is not efficient in very expensive problems, needing hundreds of thousands of evaluations. Even with the assistance of surrogate models, quality diversity needs hundreds or even thousands of evaluations, which can make its use infeasible. In this study, we try to tackle this problem by using a pre-optimization strategy on a lower-dimensional optimization problem and then map the solutions to a higher-dimensional case. For a use case to design buildings that minimize wind nuisance, we show that we can predict flow features around 3D buildings from 2D flow features around building footprints. For a diverse set of building designs, by sampling the space of 2D footprints with a quality diversity algorithm, a predictive model can be trained that is more accurate than when trained on a set of footprints that were selected with a space-filling algorithm like the Sobol sequence. Simulating only 16 buildings in 3D, a set of 1,024 building designs with low predicted wind nuisance is created. We show that we can produce better machine learning models by producing training data with quality diversity instead of using common sampling techniques. The method can bootstrap generative design in a computationally expensive 3D domain and allow engineers to sweep the design space, understanding wind nuisance in early design phases.

Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization.

Force field-based models are a Newtonian mechanics approximation of reality and are inherently noisy. Coupling models from different molecular scale domains (including single, gas-phase molecules up to multimolecule, condensed phase ensembles) is difficult, which is also the case for finding solutions that transfer well between the scales. In this contribution, we introduce a surrogate-assisted algorithm to optimize Lennard-Jones parameters for target data from different scale domains to overcome the difficulties named above. Specifically, our approach combines a surrogate-assisted global evolutionary optimization method with a presampling phase that takes advantage of one scale domain being less computationally expensive to evaluate. The algorithm's components were evaluated individually, elucidating their individual merits. Our findings show that the process of parametrizing force fields can significantly benefit from both the presampling method, which alleviates the need to have a good initial guess for the parameters, and the surrogate model, which improves efficiency.

Initial Crystallization Effects in Coarse-Grained Polyethylene Systems After Uni- and Biaxial Stretching in Blow-Molding Cooling Scenarios.

This study investigates the initial stage of the thermo-mechanical crystallization behavior for uni- and biaxially stretched polyethylene. The models are based on a mesoscale molecular dynamics approach. We take constraints that occur in real-life polymer processing into account, especially with respect to the blowing stage of the extrusion blow-molding process. For this purpose, we deform our systems using a wide range of stretching levels before they are quenched. We discuss the effects of the stretching procedures on the micro-mechanical state of the systems, characterized by entanglement behavior and nematic ordering of chain segments. For the cooling stage, we use two different approaches which allow for free or hindered shrinkage, respectively. During cooling, crystallization kinetics are monitored: We precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influence crystallization behavior. Our models reveal that the main stretching direction dominates microscopic states of the different systems. We are able to show that crystallization mainly depends on the (dis-)entanglement behavior. Nematic ordering plays a secondary role.

Investigation of Crystallization and Relaxation Effects in Coarse-Grained Polyethylene Systems after Uniaxial Stretching.

In this study, we investigate the thermo-mechanical relaxation and crystallization behavior of polyethylene using mesoscale molecular dynamics simulations. Our models specifically mimic constraints that occur in real-life polymer processing: After strong uniaxial stretching of the melt, we quench and release the polymer chains at different loading conditions. These conditions allow for free or hindered shrinkage, respectively. We present the shrinkage and swelling behavior as well as the crystallization kinetics over up to 600 ns simulation time. We are able to precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influences crystallization and relaxation behavior. From our models, we determine the temperature dependent crystallization rate of polyethylene, including crystallization onset temperature.

3D-Printed Replica and Porcine Explants for Pre-Clinical Optimization of Endoscopic Tumor Treatment by Magnetic Targeting.

BACKGROUND: Animal models have limitations in cancer research, especially regarding anatomy-specific questions. An example is the exact endoscopic placement of magnetic field traps for the targeting of therapeutic nanoparticles. Three-dimensional-printed human replicas may be used to overcome these pitfalls. METHODS: We developed a transparent method to fabricate a patient-specific replica, allowing for a broad scope of application. As an example, we then additively manufactured the relevant organs of a patient with locally advanced pancreatic ductal adenocarcinoma. We performed experimental design investigations for a magnetic field trap and explored the best fixation methods on an explanted porcine stomach wall. RESULTS: We describe in detail the eight-step development of a 3D replica from CT data. To guide further users in their decisions, a morphologic box was created. Endoscopies were performed on the replica and the resulting magnetic field was investigated. The best fixation method to hold the magnetic field traps stably in place was the fixation of loops at the stomach wall with endoscopic single-use clips. CONCLUSIONS: Using only open access software, the developed method may be used for a variety of cancer-related research questions. A detailed description of the workflow allows one to produce a 3D replica for research or training purposes at low costs.

High-order semi-Lagrangian kinetic scheme for compressible turbulence.

Turbulent compressible flows are traditionally simulated using explicit time integrators applied to discretized versions of the Navier-Stokes equations. However, the associated Courant-Friedrichs-Lewy condition severely restricts the maximum time-step size. Exploiting the Lagrangian nature of the Boltzmann equation's material derivative, we now introduce a feasible three-dimensional semi-Lagrangian lattice Boltzmann method (SLLBM), which circumvents this restriction. While many lattice Boltzmann methods for compressible flows were restricted to two dimensions due to the enormous number of discrete velocities in three dimensions, the SLLBM uses only 45 discrete velocities. Based on compressible Taylor-Green vortex simulations we show that the new method accurately captures shocks or shocklets as well as turbulence in 3D without utilizing additional filtering or stabilizing techniques other than the filtering introduced by the interpolation, even when the time-step sizes are up to two orders of magnitude larger compared to simulations in the literature. Our new method therefore enables researchers to study compressible turbulent flows by a fully explicit scheme, whose range of admissible time-step sizes is dictated by physics rather than spatial discretization.

Semi-Lagrangian lattice Boltzmann method for compressible flows.

This work thoroughly investigates a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows. In contrast to other LBM for compressible flows, the vertices are organized in cells, and interpolation polynomials up to fourth order are used to attain the off-vertex distribution function values. Differing from the recently introduced Particles on Demand (PoD) method [Dorschner, Bösch, and Karlin, Phys. Rev. Lett. 121, 130602 (2018)PRLTAO0031-900710.1103/PhysRevLett.121.130602], the method operates in a static, nonmoving reference frame. Yet the SLLBM in the present formulation grants supersonic flows and exhibits a high degree of Galilean invariance. The SLLBM solver allows for an independent time step size due to the integration along characteristics and for the use of unusual velocity sets, like the D2Q25, which is constructed by the roots of the fifth-order Hermite polynomial. The properties of the present model are shown in diverse example simulations of a two-dimensional Taylor-Green vortex, a Sod shock tube, a two-dimensional Riemann problem, and a shock-vortex interaction. It is shown that the cell-based interpolation and the use of Gauss-Lobatto-Chebyshev support points allow for spatially high-order solutions and minimize the mass loss caused by the interpolation. Transformed grids in the shock-vortex interaction show the general applicability to nonuniform grids.

Pseudoentropic derivation of the regularized lattice Boltzmann method.

The lattice Boltzmann method (LBM) facilitates efficient simulations of fluid turbulence based on advection and collision of local particle distribution functions. To ensure stable simulations on underresolved grids, the collision operator must prevent drastic deviations from local equilibrium. This can be achieved by various methods, such as the multirelaxation time, entropic, quasiequilibrium, regularized, and cumulant schemes. Complementing a part of a unified theoretical framework of these schemes, the present work presents a derivation of the regularized lattice Boltzmann method (RLBM), which follows a recently introduced entropic multirelaxation time LBM by Karlin, Bösch, and Chikatamarla (KBC). It is shown that both methods can be derived by locally maximizing a quadratic Taylor expansion of the entropy function. While KBC expands around the local equilibrium distribution, the RLBM is recovered by expanding entropy around a global equilibrium. Numerical tests were performed to elucidate the role of pseudoentropy maximization in these models. Simulations of a two-dimensional shear layer show that the RLBM successfully reproduces the largest eddies even on a 16×16 grid, while the conventional LBM becomes unstable for grid resolutions of 128×128 and lower. The RLBM suppresses spurious vortices more effectively than KBC. In contrast, simulations of the three-dimensional Taylor-Green and Kida vortices show that KBC performs better in resolving small scale vortices, outperforming the RLBM by a factor of 1.8 in terms of the effective Reynolds number.

Interactions of Water and Alkanes: Modifying Additive Force Fields to Account for Polarization Effects.

Atomistic biomolecular simulations predominantly utilize additive force fields (FF), where the electrostatic potential is modeled by fixed point charges. Among other consequences, the lack of polarizability in these models undermines the balance of hydrophilic/hydrophobic nonbonded interactions. Simulations of water/alkane systems using the TIP3P water model and CHARMM36 parameters reveal a 1 kcal/mol overestimate of the experimental transfer free energy of water to hexadecane; more recent optimized water models (SPC/E, TIP4P/2005, TIP4P-Ew, TIP3P-FB, TIP4P-FB, OPC, TIP4P-D) overestimate this transfer free energy by approximately 2 kcal/mol. In contrast, the polarizable SWM4-NDP and SWM6 water models reproduce experimental values to within statistical error. As an alternative to explicitly modeling polarizability, this paper develops an efficient automated workflow to optimize pair-specific Lennard-Jones parameters within an additive FF. Water/hexadecane is used as a prototype and the free energy of water transfer to hexadecane as a target. The optimized model yields quantitative agreement with the experimental transfer free energy and improves the water/hexadecane interfacial tension by 6%. Simulations of five different lipid bilayers show a strong increase of water permeabilities compared to the unmodified CHARMM36 lipid FF which consistently improves match with experiment: the order-of-magnitude underestimate for monounsaturated bilayers is rectified and the factor of 2.8-4 underestimate for saturated bilayers is turned into a factor of 1.5-3 overestimate. While agreement with experiment is decreased for the diffusion constant of water in hexadecane, alkane transfer free energies, and the bilayers' area per lipid, the method provides a permeant-specific route to achieve a wide range of heterogeneous observables via rapidly optimized pairwise parameters.

Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies.

Pseudopotential-based lattice Boltzmann models are widely used for numerical simulations of multiphase flows. In the special case of multicomponent systems, the overall dynamics are characterized by the conservation equations for mass and momentum as well as an additional advection diffusion equation for each component. In the present study, we investigate how the latter is affected by the forcing scheme, i.e., by the way the underlying interparticle forces are incorporated into the lattice Boltzmann equation. By comparing two model formulations for pure multicomponent systems, namely the standard model [X. Shan and G. D. Doolen, J. Stat. Phys. 81, 379 (1995)JSTPBS0022-471510.1007/BF02179985] and the explicit forcing model [M. L. Porter et al., Phys. Rev. E 86, 036701 (2012)PLEEE81539-375510.1103/PhysRevE.86.036701], we reveal that the diffusion characteristics drastically change. We derive a generalized, potential function-dependent expression for the transition point from the miscible to the immiscible regime and demonstrate that it is shifted between the models. The theoretical predictions for both the transition point and the mutual diffusion coefficient are validated in simulations of static droplets and decaying sinusoidal concentration waves, respectively. To show the universality of our analysis, two common and one new potential function are investigated. As the shift in the diffusion characteristics directly affects the interfacial properties, we additionally show that phenomena related to the interfacial tension such as the modeling of contact angles are influenced as well.

Small Alcohols Revisited: CCSD(T) Relative Potential Energies for the Minima, First- and Second-Order Saddle Points, and Torsion-Coupled Surfaces.

The elucidation of conformations and relative potential energies (rPEs) of small molecules has a long history across a diverse range of fields. Periodically, it is helpful to revisit what conformations have been investigated and to provide a consistent theoretical framework for which clear comparisons can be made. In this paper, we compute the minima, first- and second-order saddle points, and torsion-coupled surfaces for methanol, ethanol, propan-2-ol, and propanol using consistent high-level MP2 and CCSD(T) methods. While for certain molecules more rigorous methods were employed, the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pV5Z theory level was used throughout to provide relative energies of all minima and first-order saddle points. The rPE surfaces were uniformly computed at the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ level. To the best of our knowledge, this represents the most extensive study for alcohols of this kind, revealing some new aspects. Especially for propanol, we report several new conformations that were previously not investigated. Moreover, two metrics are included in our analysis that quantify how the selected surfaces are similar to one another and hence improve our understanding of the relationship between these alcohols.

Semi-Lagrangian off-lattice Boltzmann method for weakly compressible flows.

The lattice Boltzmann method is a simulation technique in computational fluid dynamics. In its standard formulation, it is restricted to regular computation grids, second-order spatial accuracy, and a unity Courant-Friedrichs-Lewy (CFL) number. This paper advances the standard lattice Boltzmann method by introducing a semi-Lagrangian streaming step. The proposed method allows significantly larger time steps, unstructured grids, and higher-order accurate representations of the solution to be used. The appealing properties of the approach are demonstrated in simulations of a two-dimensional Taylor-Green vortex, doubly periodic shear layers, and a three-dimensional Taylor-Green vortex.

Computer simulations suggest direct and stable tip to tip interaction between the outer membrane channel TolC and the isolated docking domain of the multidrug RND efflux transporter AcrB.

One way by which bacteria achieve antibiotics resistance is preventing drug access to its target molecule for example through an overproduction of multi-drug efflux pumps of the resistance nodulation division (RND) protein super family of which AcrAB-TolC in Escherichia coli is a prominent example. Although representing one of the best studied efflux systems, the question of how AcrB and TolC interact is still unclear as the available experimental data suggest that either both proteins interact in a tip to tip manner or do not interact at all but are instead connected by a hexamer of AcrA molecules. Addressing the question of TolC-AcrB interaction, we performed a series of 100 ns - 1 µs-molecular dynamics simulations of membrane-embedded TolC in presence of the isolated AcrB docking domain (AcrB(DD)). In 5/6 simulations we observe direct TolC-AcrB(DD) interaction that is only stable on the simulated time scale when both proteins engage in a tip to tip manner. At the same time we find TolC opening and closing freely on extracellular side while remaining closed at the inner periplasmic bottleneck region, suggesting that either the simulated time is too short or additional components are required to unlock TolC.

Visualizing potential energy curves and conformations on ultra high-resolution display walls.

In this contribution, we examine how visualization on an ultra high-resolution display wall can augment force-field research in the field of molecular modeling. Accurate force fields are essential for producing reliable simulations, and subsequently important for several fields of applications (e.g. rational drug design and biomolecular modeling). We discuss how using HORNET, a recently constructed specific ultra high-resolution tiled display wall, enhances the visual analytics that are necessary for conformational-based interpretation of the raw data from molecular calculations. Simultaneously viewing multiple potential energy graphs and conformation overlays leads to an enhanced way of evaluating force fields and in their optimization. Consequently, we have integrated visual analytics into our existing Wolf2Pack workflow. We applied this workflow component to analyze how major AMBER force fields (Parm14SB, Gaff, Lipid14, Glycam06j) perform at reproducing the quantum mechanics relative energies and geometries of saturated hydrocarbons. Included in this comparison are the 1996 OPLS force field and our newly developed ExTrM force field. While we focus on atomistic force fields the ideas presented herein are generalizable to other research areas, particularly those that involve numerous representations of large data amounts and whose simultaneous visualization enhances the analysis.

On the nature of interactions between ionic liquids and small amino-acid-based biomolecules.

During the last decade, ionic liquids (ILs) have revealed promising properties and applications in many research fields, including biotechnology and biological sciences. The focus of this contribution is to give a critical review of the phenomena observed and current knowledge of the interactions occurring on a molecular basis. As opposed to the huge advances made in understanding the properties of proteins in ILs, complementary investigations dealing with interactions between ILs and peptides or oligopeptides are underrepresented and are mostly only of phenomenological nature. However, the field has received more attention in the last few years. This Review features a meta-analysis of the available data and findings and should, therefore, provide a basis for a scientifically profound understanding of the nature and mechanisms of interactions between ILs and structured or nonstructured peptides. Fundamental aspects of the interactions between different peptides/oligopeptides and ILs are complemented by sections on the experimental (spectroscopy, structural biology) and theoretical (computational chemistry) possibilities to explain the phenomena reported so far in the literature. In effect, this should lead to the development of novel applications and support the understanding of IL-solute interactions in general.

Why the partition coefficient of ionic liquids is concentration-dependent.

The partition coefficient of a substance measures its solubility in octanol compared with water and is widely used to estimate toxicity. If a substance is hardly soluble in octanol, then it is practically impossible for it to enter (human) cells and therefore is less likely to be toxic. For novel drugs it might be important to penetrate the cell through the membrane or even integrate into it. While for most simple substances the partition coefficient is concentration-independent at low concentrations, this is not true for a few important classes of complex molecules, such as ionic liquids or tensides. We present a simple association-dissociation model for concentration dependence of the partition coefficient of ionic liquids. Atomistic computer simulations serve to parametrize our model by calculating solvation free energies in water and octanol using thermodynamic integration. We demonstrate the validity of the method by reproducing the concentration-independent partition coefficients of small alcohols and the concentration-dependent partition coefficient of a commonly used ionic liquid, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide [C4MIM][NTf2]. The concentration dependence is accurately predicted in a concentration range of several orders of magnitude.

Comparison of force fields on the basis of various model approaches--how to design the best model for the [CnMIM][NTf2] family of ionic liquids.

In this contribution, we present two new united-atom force fields (UA-FFs) for 1-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide [C(n)MIM][NTf(2)] (n=1, 2, 4, 6, 8) ionic liquids (ILs). One is parametrized manually, and the other is developed with the gradient-based optimization workflow (GROW). By doing so, we wanted to perform a hard test to determine how researchers could benefit from semiautomated optimization procedures. As with our already published all-atom force field (AA-FF) for [C(n)MIM][NTf(2)] (T. Köddermann, D. Paschek, R. Ludwig, ChemPhysChem- 2007, 8, 2464), the new force fields were derived to fit experimental densities, self-diffusion coefficients, and NMR rotational correlation times for the IL cation and for water molecules dissolved in [C(2)MIM][NTf(2)]. In the manual force field, the alkyl chains of the cation and the CF3 groups of the anion were treated as united atoms. In the GROW force field, only the alkyl chains of the cation were united. All other parts of the structures of the ions remained unchanged to prevent any loss of physical information. Structural, dynamic, and thermodynamic properties such as viscosity, cation rotational correlation times, and heats of vaporization calculated with the new force fields were compared with values simulated with the previous AA-FF and the experimental data. All simulated properties were in excellent agreement with the experimental values. Altogether, the UA-FFs are slightly superior for speed-up reasons. The UA-FF speeds up the simulation by about 100 % and reduces the demanded disk space by about 78 %. More importantly, real time and efforts to generate force fields could be significantly reduced by utilizing GROW. The real time for the GROW parametrization in this work was 2 months. Manual parametrization, in contrast, may take up to 12 months, and this is, therefore, a significant increase in speed, though it is difficult to estimate the duration of manual parametrization.

Wolf2Pack--portal based atomistic force-field development.

In this contribution we introduce the technical concept and implementation details concerning the front end of our force-field optimization workflow package for intramolecular degrees of freedom, called Wolf2Pack. The package's design follows our belief that parameter optimization should be a user-driven, but program guided, workflow with specific modular tasks that reduce human errors and save time. Through this design, parameter optimization becomes more reliable and reproducible. Wolf2Pack can integrate common force fields from different research areas, allowing the user to optimize balanced parameters; alternatively users can develop highly specialized force fields that suite their chemical systems. Included in the package's front end is a force-field and molecular database whose contents facilitate parameter optimization. Wolf2Pack can be accessed at www.wolf2pack.com.

Folding and unfolding characteristics of short beta strand peptides under different environmental conditions and starting configurations.

We analyze the effect of different environmental conditions, sequence lengths and starting configurations on the folding and unfolding pathways of small peptides exhibiting beta turns. We use chignolin and a sequence of peptide G as examples. A variety of different analysis tools allows us to characterize the changes in the folding pathways. It is observed that different harmonic modes dominate not only for different conditions but also for different starting points. The modes remain essentially very similar but their relative importance varies. A detailed analysis from diverse viewpoints including the influence of the particular amino acid sequence, conformational aspects as well as the associated motions yields a global picture that is consistent with experimental evidence and theoretical studies published elsewhere. Patterns of modes that remain stable over a range of temperatures might serve as an additional diagnostic to identify conformations that have reliably adopted a native fold. This could aid in reconstructing the folding process of a complete protein by identifying conformationally determined regions.

Deriving effective mesoscale potentials from atomistic simulations.

We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liquid systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few iterations. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 reduction of the degrees of freedom. This procedure was performed for PI solutions as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concentration regimes.