Benchmark Structures and Conformational Landscapes of Amino Acids in the Gas Phase: A Joint Venture of Machine Learning, Quantum Chemistry, and Rotational Spectroscopy

The accurate characterization of prototypical bricks of life can strongly benefit from the integration of high resolution spectroscopy and quantum mechanical computations. We have selected a number of representative amino acids (glycine, alanine, serine, cysteine, threonine, aspartic acid and asparagine) to validate a new computational setup rooted in quantum-chemical computations of increasing accuracy guided by machine learning tools. Together with low-lying energy minima, the barriers ruling their interconversion are evaluated in order to unravel possible fast relaxation paths. Vibrational and thermal effects are also included in order to estimate relative free energies at the temperature of interest in the experiment. The spectroscopic parameters of all the most stable conformers predicted by this computational strategy, which do not have low-energy relaxation paths available, closely match those of the species detected in microwave experiments. Together with their intrinsic interest, these accurate results represent ideal benchmarks for more approximate methods

Model uncertainty in non-linear numerical analyses of slender reinforced concrete members

The present study aims to characterize the epistemic uncertainty within the use of global non-linear numerical analyses (i.e., NLNAs) for design and assessment purposes of slender reinforced concrete (RC) members. The epistemic uncertainty associated to NLNAs may be represented by approximations and choices performed during the definition of a structural numerical model. In order to quantify epistemic uncertainty associated to a non-linear numerical simulation, the resistance model uncertainty random variable has to be characterized by means of the comparison between experimental and numerical results. With this aim, a set of experimental tests on slender RC columns known from the literature is considered. Then, the experimental results in terms of maximum axial load are compared to the outcomes achieved from NLNAs. Nine different modeling hypotheses are herein considered to characterize the resistance model uncertainty random variable. The probabilistic analysis of the results has been performed according to Bayesian approach accounting also for both the previous knowledge from the scientific literature and the influence of the experimental uncertainty on the estimation of the statistics of the resistance model uncertainty random variable. Finally, the resistance model uncertainty partial safety factor is evaluated in line with the global resistance format of fib Model Code for Concrete Structures 2010 with reference to new and existing RC structures

Fast exploration of potential energy surfaces with a joint venture of quantum chemistry, evolutionary algorithms and unsupervised learning

Contemporary molecular spectroscopy allows the study of flexible molecules, whose conformational behavior is ruled by flat potential energy surfaces (PESs) involving a large number of energy minima with comparable stability. Under such circumstances assignment and interpretation of the spectral signatures can strongly benefit from quantum chemical computations, which face, however, several difficulties. In particular, the mandatory characterization of all the relevant energy minima leads to a huge increase in the number of accurate quantum chemical computations (which may even hamper the feasibility of a study) and the intricate couplings among several soft degrees of freedom can defy simple heuristic approaches and chemical intuition. From this point of view, the exploration of flat PESs is akin to other optimization problems and can be tackled with suitable metaheuristics, which can drive QC computations by reducing the number of necessary calculations and providing effective routes to sample the most relevant regions of the PES. Unfortunately, in spite of the significant reduction of the number of QC calculations, a brute-force approach based on state-of-the-art methods remains infeasible. This problem can be solved effectively by multi-level strategies combining methods of different accuracy in the first PES exploration, refinement of the structures of the most important stationary points and computation of spectroscopic parameters. Building on previous experience, in this contribution we introduce new improvements in an evolutionary algorithm based method using curvilinear coordinates for both intra- and inter-molecular interactions. Two test cases will be analyzed in detail, namely aspartic acid in the gas-phase and the silver cation in aqueous solution. Comparison between fully a priori computed spectroscopic parameters and the experimental counterparts will provide an unbiased validation of the proposed strategy

Modelling failure analysis of RC frame structures with masonry infills under sudden column losses

Robustness of structures is fundamental to limit progressive collapse of buildings in case of accidental loss of columns due to explosions, impacts or materials deterioration. Modelling of progressive collapse response of reinforced concrete (RC) frame structures needs considering extreme geometric and mechanical nonlinearities. Moreover, in the case of infilled frames the collapse mechanism becomes more complex because of the frame-infill interaction. This paper presents a numerical study aimed at proposing: A) an appropriate fiber-section modeling methodology for reinforced concrete frames under large displacement progressive collapse events; b) a new multi-strut fiber macro-element model to account for the influence of masonry infills in the progressive collapse response. Proposed numerical models are developed using the OpenSees software platform. The predictive capacity of the proposed methodology is widely validated in the paper through comparisons with experimental test results and refined numerical simulation pushdown test results. Results show that the new equivalent-strut modeling approach can be suitably employed as a simple assessment method when numerical simulation of progressive collapse scenarios is needed for bare and infilled reinforced concrete frames

Modelling failure analysis of RC frame structures with masonry infills under sudden column losses

Abstract Robustness of structures is fundamental to limit progressive collapse of buildings in case of accidental loss of columns due to explosions, impacts or materials deterioration. Modelling of progressive collapse response of reinforced concrete (RC) frame structures needs considering extreme geometric and mechanical nonlinearities. Moreover, in the case of infilled frames the collapse mechanism becomes more complex because of the frame-infill interaction. This paper presents a numerical study aimed at proposing: a) an appropriate fiber-section modeling methodology for reinforced concrete frames under large displacement progressive collapse events; b) a new multi-strut fiber macro-element model to account for the influence of masonry infills in the progressive collapse response. Proposed numerical models are developed using the OpenSees software platform. The predictive capacity of the proposed methodology is widely validated in the paper through comparisons with experimental test results and refined numerical simulation pushdown test results. Results show that the new equivalent-strut modeling approach can be suitably employed as a simple assessment method when numerical simulation of progressive collapse scenarios is needed for bare and infilled reinforced concrete frames

Assessment of Multi-Scale Approaches for ComputingUV–Vis Spectra in Condensed Phases: Toward an Effective yetReliable Integration of Variational and Perturbative QM/MM Approaches

Computational simulation of UV/vis spectra in condensed phases can be performed starting from converged molecular dynamics (MD) simulations and then performing quantum mechanical/molecular mechanical (QM/MM) computations for a statistically significant number of snapshots. However, the need of variational solutions (e.g., ONIOM/EE) for a huge number of snapshots makes unpractical the use of state-of-the-art QM Hamiltonians. On the other hand, the effectivity of perturbative approaches (e.g., perturbed matrix method, PMM) comes at the price of poor convergence for configurations strongly different from the reference one. In this paper we introduce an integrated strategy based on a cluster analysis of the MD snapshots. Next, a representative configuration for each cluster is treated at the ONIOM/EE level, whereas local fluctuations within each cluster are described at the PMM level. Some representative systems (uracil in dimethylformamide and in water and tyrosine zwitterion in water) are analyzed to show t..

Integration of Quantum Chemistry, Statistical Mechanics, and Artificial Intelligence for Computational Spectroscopy: The UV-Vis Spectrum of TEMPO Radical in Different Solvents

The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurate strategies for the investigation of the spectroscopic properties of medium-to-large size chromo-phores in condensed phases. In this context we are developing a novel workflow aimed at improving the generality, reliability, and ease of use of the available computational tools. In this paper we report our latest developments with specific reference to unsupervised atomistic simulations employing non periodic boundary conditions (NPBC) followed by clustering of the trajectories employing optimized feature spaces. Next accurate variational computations are performed for a representative point of each cluster, whereas intracluster fluctuations are taken into account by a cheap yet reliable perturbative approach. A number of methodological improvements have been introduced including, e.g., more realistic reaction field effects at the outer boundary of the simulation sphere, automatic definition of the feature space by continuous perception of solute-sol v e n t interactions, full account of polarization and charge transfer in the first solvation shell, and inclusion of vibronic contributions. After its validation, this new approach has been applied to the challenging case of solvatochromic effects on the UV-vis spectra of a prototypical nitroxide radical (TEMPO) in different solvents. The reliability, effectiveness, and robustness of the new platform is demonstrated by the remarkable agreement with experiment of the results obtained through an unsupervised approach characterized by a strongly reduced computational cost as compared to that of conventional quantum mechanics and molecular mechanics models without any accuracy reduction

Fine tuning of atomic point charges classical simulations of pyridine in different environments

Abstract A correct description of electrostatic contributions in force fields for classical simulations is mandatory for an accurate modeling of molecular interactions in pure liquids or solutions. Here, we propose a new protocol for point charge fitting, aimed to take into the proper account different polarization effects due to the environment employing virtual sites and tuning the point charge within the polarizable continuum model framework. The protocol has been validated by means of molecular dynamics simulations on pure pyridine liquid and on pyridine aqueous solution, reproducing a series of experimental observables and providing the information for their correct interpretation at atomic level

Tuning of dye optical properties by environmental effects: a QM/MM and experimental study

The present work is aimed to a deeper investigation of two recently synthesized heteroaromatic fluorophores by means of a computational multilayer approach, integrating quantum mechanics (QM) and molecular mechanics (MM). In particular, dispersion of the title dyes in a polymer matrix is studied in connection with potential applications as photoactive species in luminescent solar concentrators (LSCs). Molecular dynamics simulations, based on accurate QM-derived force fields, reveal increased stiffness of these organic dyes when going from CHCl3 solution to polymer matrix. QM/MM computations of UV spectra for snapshots extracted from MD simulations show that this different flexibility permits to explain the different spectral shapes obtained experimentally for the two different environments. Moreover, the general spectroscopic trends are well reproduced by static computations employing a polarizable continuum description of environmental effects