Using Gaussian Process Regression to Simulate the Vibrational Raman Spectra of Molecular Crystals

Vibrational properties of molecular crystals are constantly used as structural fingerprints, in order to identify both the chemical nature and the structural arrangement of molecules. The simulation of these properties is typically very costly, especially when dealing with response properties of materials to e.g. electric fields, which require a good description of the perturbed electronic density. In this work, we use Gaussian process regression (GPR) to predict the static polarizability and dielectric susceptibility of molecules and molecular crystals. We combine this framework with ab initio molecular dynamics to predict their anharmonic vibrational Raman spectra. We stress the importance of data representation, symmetry, and locality, by comparing the performance of different flavors of GPR. In particular, we show the advantages of using a recently developed symmetry-adapted version of GPR. As an examplary application, we choose Paracetamol as an isolated molecule and in different crystal forms. We obtain accurate vibrational Raman spectra in all cases with fewer than 1000 training points, and obtain improvements when using a GPR trained on the molecular monomer as a baseline for the crystal GPR models. Finally, we show that our methodology is transferable across polymorphic forms: we can train the model on data for one structure, and still be able to accurately predict the spectrum for a second polymorph. This procedure provides an independent route to access electronic structure properties when performing force-evaluations on empirical force-fields or machine-learned potential energy surfaces

3D in Suspension versus 2D in Adhesion: molecular profiles in stemness and mesenchymal differentiation of Spheroids from Adipose-derived Stem Cells

Purpose: Adipose stem cells (ASCs) represent a reliable source of stem cells with a widely demonstrated potential in regenerative medicine and tissue engineering applications. New recent insights suggest that three-dimensional (3D) models may closely mimic the native tissue properties; spheroids from adipose derived stem cells (S-ASCs) exhibit enhanced regenerative abilities compared with those of 2D models. Stem cell therapy success is determined by “cell-quality”; for this reason, microRNA profiles, the involvement of stress signals and cellular aging need to be further investigated. Material and Methods: Adipose tissue was collected from healthy individuals, 44 females and 17 males, after signing informed consent. Mean age was 50, 25 years (range: 18-77). Lipoaspirate samples were harvested from different body areas such as abdomen, breast, flanks, trochanteric region, and knee. Here, we performed a comparative analysis, molecular and functional, of miRNA expression pattern profile “stemness and differentiation associated”, genes connected with stemness, aging, telomeric length and oxidative stress, of adipose stem cells in three-dimensional and adhesion conditions, SASCs-3D and ASCs-2D cultures. Results: We have demonstrated that Spheroids from Adipose-derived Stem Cells (SASCs-3D) present express high level of the typical miRNAs and mRNAs of iPS cells, such as miR-142-3p and SOX2/POU5F1/NANOG, in canonical and in long term in vitro culture condition, express low level of the early and late miRNAs and mRNAs typical of chondrocytic, adipocytic and osteoblastic lineages in canonical and in long term in vitro culture condition. The expression levels of stemness-related markers and anti-aging Sirtuin1 were significantly up-regulated (P < 0.001) in SASC-3D while gene expression of aging-related p16INK4a was increased in ASCs-2D (P < 0.001). We found that 3D and 2D cultures also presented a different gene expression profile for those genes related to telomere maintenance (Shelterin complex, RNA Binding proteins and DNA repair genes) (P < 0.01 and P < 0.001) and oxidative stress (aldehyde dehydrogenase class1 and 3) (P < 0.05, P < 0.01 and P < 0.001) and presented a striking large variation in their cellular redox state. Conclusion: Based on our findings, we propose a “cell quality” model of SASCs, highlighting a precise molecular expression of microRNA pattern profiles, several genes involved with stemness (SOX2, POU5F1 and NANOG), anti-aging (SIRT1), oxidative stress (ALDH3) and telomeres maintenance.Purpose: Adipose stem cells (ASCs) represent a reliable source of stem cells with a widely demonstrated potential in regenerative medicine and tissue engineering applications. New recent insights suggest that three-dimensional (3D) models may closely mimic the native tissue properties; spheroids from adipose derived stem cells (S-ASCs) exhibit enhanced regenerative abilities compared with those of 2D models. Stem cell therapy success is determined by “cell-quality”; for this reason, microRNA profiles, the involvement of stress signals and cellular aging need to be further investigated. Material and Methods: Adipose tissue was collected from healthy individuals, 44 females and 17 males, after signing informed consent. Mean age was 50, 25 years (range: 18-77). Lipoaspirate samples were harvested from different body areas such as abdomen, breast, flanks, trochanteric region, and knee. Here, we performed a comparative analysis, molecular and functional, of miRNA expression pattern profile “stemness and differentiation associated”, genes connected with stemness, aging, telomeric length and oxidative stress, of adipose stem cells in three-dimensional and adhesion conditions, SASCs-3D and ASCs-2D cultures. Results: We have demonstrated that Spheroids from Adipose-derived Stem Cells (SASCs-3D) present express high level of the typical miRNAs and mRNAs of iPS cells, such as miR-142-3p and SOX2/POU5F1/NANOG, in canonical and in long term in vitro culture condition, express low level of the early and late miRNAs and mRNAs typical of chondrocytic, adipocytic and osteoblastic lineages in canonical and in long term in vitro culture condition. The expression levels of stemness-related markers and anti-aging Sirtuin1 were significantly up-regulated (P < 0.001) in SASC-3D while gene expression of aging-related p16INK4a was increased in ASCs-2D (P < 0.001). We found that 3D and 2D cultures also presented a different gene expression profile for those genes related to telomere maintenance (Shelterin complex, RNA Binding proteins and DNA repair genes) (P < 0.01 and P < 0.001) and oxidative stress (aldehyde dehydrogenase class1 and 3) (P < 0.05, P < 0.01 and P < 0.001) and presented a striking large variation in their cellular redox state. Conclusion: Based on our findings, we propose a “cell quality” model of SASCs, highlighting a precise molecular expression of microRNA pattern profiles, several genes involved with stemness (SOX2, POU5F1 and NANOG), anti-aging (SIRT1), oxidative stress (ALDH3) and telomeres maintenance

Solvent Fluctuations and Nuclear Quantum Effects Modulate the Molecular Hyperpolarizability of Water

Second-Harmonic Scatteringh (SHS) experiments provide a unique approach to probe non-centrosymmetric environments in aqueous media, from bulk solutions to interfaces, living cells and tissue. A central assumption made in analyzing SHS experiments is that the each molecule scatters light according to a constant molecular hyperpolarizability tensor $\boldsymbol{\beta}^{(2)}$. Here, we investigate the dependence of the molecular hyperpolarizability of water on its environment and internal geometric distortions, in order to test the hypothesis of constant $\boldsymbol{\beta}^{(2)}$. We use quantum chemistry calculations of the hyperpolarizability of a molecule embedded in point-charge environments obtained from simulations of bulk water. We demonstrate that both the heterogeneity of the solvent configurations and the quantum mechanical fluctuations of the molecular geometry introduce large variations in the non-linear optical response of water. This finding has the potential to change the way SHS experiments are interpreted: in particular, isotopic differences between H$_2$O and D$_2$O could explain recent second-harmonic scattering observations. Finally, we show that a simple machine-learning framework can predict accurately the fluctuations of the molecular hyperpolarizability. This model accounts for the microscopic inhomogeneity of the solvent and represents a first step towards quantitative modelling of SHS experiments

Effect of a Temperature Gradient on the Screening Properties of Ionic Fluids

The electrostatic screening properties of ionic fluids are of paramount importance in countless physical processes. Yet, the behavior of ionic conductors out of thermal equilibrium has to date mainly been studied in the context of thermodiffusion phenomena by virtue of direct extensions of Debye-H\"uckel theories. We investigate how the static response of a symmetric ionic fluid is influenced by the presence of a thermal gradient by introducing a theory of electrostatic screening under a stationary temperature profile. By borrowing mathematical methods commonly used in the semiclassical approximation of quantum particles, we find analytical solutions to the asymptotic decay of the charge density which can be used to describe the non-equilibrium response of the system to external charge perturbations and for arbitrary ionic concentrations. Notably, a transition between monotonic and oscillatory screening regimes is observed as an effect of the temperature variation which generalizes known results of thermal equilibrium to out of equilibrium conditions. A final quantitative example on the screening of charged surfaces in aqueous electrolytes shows that the deviation from thermal equilibrium predicted by our solutions is generally larger than thermodiffusion effects, and should therefore be taken into account for a comprehensive description of the electrical double layer. Our findings pave the way to the rigorous treatment of non-equilibrium steady states in ionic systems with potential applications to the study of energy materials, nanostructured systems and waste-heat-recovery technologies.Comment: 11 pages, 5 figure

CFD simulation of a mixing-sensitive reaction in unbaffled vessels

Stirred tanks are widely used in the process industry, often to carry out complex chemical reactions. In many of such cases the perfect mixing hypothesis is not applicable for modelling purposes, and more detailed modelling approaches are required in order to accurately describe the reactor behaviour. In this work a fully predictive modelling approach, based on Computational Fluid Dynamics, is developed. Model predictions are compared with original experimental data obtained in un unbaffled stirred vessel with a parallel-competitive, mixing sensitive reaction scheme. Notably, satisfactory results are obtained at all injection rates with no recourse to micro-mixing model, thus confirming the major role played by macro-mixing in the investigated system

A Transferable Machine-Learning Model of the Electron Density

The electronic charge density plays a central role in determining the behavior of matter at the atomic scale, but its computational evaluation requires demanding electronic-structure calculations. We introduce an atom-centered, symmetry-adapted framework to machine-learn the valence charge density based on a small number of reference calculations. The model is highly transferable, meaning it can be trained on electronic-structure data of small molecules and used to predict the charge density of larger compounds with low, linear-scaling cost. Applications are shown for various hydrocarbon molecules of increasing complexity and flexibility, and demonstrate the accuracy of the model when predicting the density on octane and octatetraene after training exclusively on butane and butadiene. This transferable, data-driven model can be used to interpret experiments, initialize electronic structure calculations, and compute electrostatic interactions in molecules and condensed-phase systems

Predicting the Charge Density Response in Metal Electrodes

The computational study of energy storage and conversion processes call for simulation techniques that can reproduce the electronic response of metal electrodes under electric fields. Despite recent advancements in machine-learning methods applied to electronic-structure properties, predicting the non-local behaviour of the charge density in electronic conductors remains a major open challenge. We combine long-range and equivariant kernel methods to predict the Kohn-Sham electron density of metal electrodes decomposed on an atom-centered basis. By taking slabs of gold as an example, we show that including long-range correlations into the learning model is essential to accurately reproduce the charge density and potential in bare electrodes of increasing size. A finite-field extension of the method is then introduced, which allows us to predict the charge transfer and the electrostatic potential drop induced by the application of an external electric field. Finally, we demonstrate the capability of the method to extrapolate the non-local electronic polarization generated by the interaction with an ionic species for electrodes of arbitrary thickness. Our study represents an important step forward in the accurate simulation of energy materials that include metallic interfaces.Comment: 6 pages, 4 figure

Free surface oxygen transfer in large aspect ratio unbaffled bio-reactors, with or without draft-tube

It is widely accepted that animal cell damage in aerated bioreactors is mainly related to the bursting of bubbles at the air-liquid interface. A viable alternative to sparged bioreactors may be represented by uncovered unbaffled stirred tanks, which have been recently found to be able to provide sufficient mass transfer through the deep free surface vortex which takes place under agitation conditions. As a matter of fact, if the vortex is not allowed to reach impeller blades, no bubble formation and subsequent bursting at the free-surface, along with relevant cells damage, occurs.In this work oxygen transfer performance of large aspect ratio unbaffled stirred bioreactors, either equipped or not with an internal draft tube, is presented, in view of their use as biochemical reactors especially suited for shear sensitive cell cultivation