Amino acids as bio-organocatalysts in ring-opening copolymerization for eco-friendly synthesis of biobased oligomers from vegetable oils.

Herein, we present an innovative synthetic approach for producing a diverse set of biobased oligomers. This method begins with olive oil and employs a wide variety of commercially available amino acids (AAs) as bio-organocatalysts, in addition to tetrabutylammonium iodide (TBAI) as a cocatalyst, to synthesize various biobased oligomers. These biobased oligomers were strategically prepared starting from epoxidized olive oil (EOO) and a variety of cyclic anhydrides (phthalic, PA; maleic, MA; succinic, SA; and glutaric, GA). Among the amino acids tested as bio-organocatalysts, L-glutamic acid (L-Glu) showed the best performance for the synthesis of both poly(EOO-co-PA) and poly(EOO-co-MA), exhibiting 100% conversion at 80 °C in 2 hours, whereas the formation of poly(EOO-co-SA) and poly(EOO-co-GA) required more extreme reaction conditions (72 hours under toluene reflux conditions). Likewise, we have succeeded in obtaining the trans isomer exclusively for the MA based-oligomer within the same synthetic framework. The obtained oligomers were extensively characterized using techniques including NMR, FT-IR, GPC and TGA. A series of computational simulations based on density functional theory (DFT) and post-Hartree Fock (post-HF) methods were performed to corroborate our experimental findings and to obtain an understanding of the reaction mechanisms.

Machine Learning Interatomic Potentials for Reactive Hydrogen Dynamics at Metal Surfaces Based on Iterative Refinement of Reaction Probabilities.

The reactive chemistry of molecular hydrogen at surfaces, notably dissociative sticking and hydrogen evolution, plays a crucial role in energy storage and fuel cells. Theoretical studies can help to decipher underlying mechanisms and reaction design, but studying dynamics at surfaces is computationally challenging due to the complex electronic structure at interfaces and the high sensitivity of dynamics to reaction barriers. In addition, ab initio molecular dynamics, based on density functional theory, is too computationally demanding to accurately predict reactive sticking or desorption probabilities, as it requires averaging over tens of thousands of initial conditions. High-dimensional machine learning-based interatomic potentials are starting to be more commonly used in gas-surface dynamics, yet robust approaches to generate reliable training data and assess how model uncertainty affects the prediction of dynamic observables are not well established. Here, we employ ensemble learning to adaptively generate training data while assessing model performance with full uncertainty quantification (UQ) for reaction probabilities of hydrogen scattering on different copper facets. We use this approach to investigate the performance of two message-passing neural networks, SchNet and PaiNN. Ensemble-based UQ and iterative refinement allow us to expose the shortcomings of the invariant pairwise-distance-based feature representation in the SchNet model for gas-surface dynamics.

NQCDynamics.jl: A Julia package for nonadiabatic quantum classical molecular dynamics in the condensed phase.

Accurate and efficient methods to simulate nonadiabatic and quantum nuclear effects in high-dimensional and dissipative systems are crucial for the prediction of chemical dynamics in the condensed phase. To facilitate effective development, code sharing, and uptake of newly developed dynamics methods, it is important that software implementations can be easily accessed and built upon. Using the Julia programming language, we have developed the NQCDynamics.jl package, which provides a framework for established and emerging methods for performing semiclassical and mixed quantum-classical dynamics in the condensed phase. The code provides several interfaces to existing atomistic simulation frameworks, electronic structure codes, and machine learning representations. In addition to the existing methods, the package provides infrastructure for developing and deploying new dynamics methods, which we hope will benefit reproducibility and code sharing in the field of condensed phase quantum dynamics. Herein, we present our code design choices and the specific Julia programming features from which they benefit. We further demonstrate the capabilities of the package on two examples of chemical dynamics in the condensed phase: the population dynamics of the spin-boson model as described by a wide variety of semiclassical and mixed quantum-classical nonadiabatic methods and the reactive scattering of H2 on Ag(111) using the molecular dynamics with electronic friction method. Together, they exemplify the broad scope of the package to study effective model Hamiltonians and realistic atomistic systems.

Plasmonic enhancement of molecular hydrogen dissociation on metallic magnesium nanoclusters.

Light-driven plasmonic enhancement of chemical reactions on metal catalysts is a promising strategy to achieve highly selective and efficient chemical transformations. The study of plasmonic catalyst materials has traditionally focused on late transition metals such as Au, Ag, and Cu. In recent years, there has been increasing interest in the plasmonic properties of a set of earth-abundant elements such as Mg, which exhibit interesting hydrogenation chemistry with potential applications in hydrogen storage. This work explores the optical, electronic, and catalytic properties of a set of metallic Mg nanoclusters with up to 2057 atoms using time-dependent density functional tight-binding and density functional theory calculations. Our results show that Mg nanoclusters are able to produce highly energetic hot electrons with energies of up to 4 eV. By electronic structure analysis, we find that these hot electrons energetically align with electronic states of physisorbed molecular hydrogen, occupation of which by hot electrons can promote the hydrogen dissociation reaction. We also find that the reverse reaction, hydrogen evolution on metallic Mg, can potentially be promoted by hot electrons, but following a different mechanism. Thus, from a theoretical perspective, Mg nanoclusters display very promising behaviour for their use in light promoted storage and release of hydrogen.

Electronic structure benchmark calculations of CO2 fixing elementary chemical steps in RuBisCO using the projector-based embedding approach.

Ribulose 1,5-bisphosphate carboxylase-oxygenase (RuBisCO) is the main enzyme involved in atmospheric carbon dioxide (CO2 ) fixation in the biosphere. This enzyme catalyzes a set of five chemical steps that take place in the same active-site within magnesium (II) coordination sphere. Here, a set of electronic structure benchmark calculations have been carried out on a reaction path proposed by Gready et al. by means of the projector-based embedding approach. Activation and reaction energies for all main steps catalyzed by RuBisCO have been calculated at the MP2, SCS-MP2, CCSD, and CCSD(T)/aug-cc-pVDZ and cc-pVDZ levels of theory. The treatment of the magnesium cation with post-HF methods is explored to determine the nature of its involvement in the mechanism. With the high-level ab initio values as a reference, we tested the performance of a set of density functional theory (DFT) exchange-correlation (xc) functionals in reproducing the reaction energetics of RuBisCO carboxylase activity on a set of model fragments. Different DFT xc-functionals show large variation in activation and reaction energies. Activation and reaction energies computed at the B3LYP level are close to the reference SCS-MP2 results for carboxylation, hydration and protonation reactions. However, for the carbon-carbon bond dissociation reaction, B3LYP and other functionals give results that differ significantly from the ab initio reference values. The results show the applicability of the projector-based embedding approach to metalloenzymes. This technique removes the uncertainty associated with the selection of different DFT xc-functionals and so can overcome some of inherent limitations of DFT calculations, complementing, and potentially adding to modeling of enzyme reaction mechanisms with DFT methods.

Physico-chemistry of a successful micro-reactor: Random coils of chitosan backbones used to synthesize size-controlled silver nanoparticles.

The synthetic system to produce silver nanoparticles (AgNP) based on the thermally activated reduction of aqueous silver ions by chitosan (CS) polysaccharide is investigated to unravel the physicochemical processes controlling AgNP nucleation and growth. An anomalous preeminence of AgNP nucleation over growth is found for conditions under which the opposite trend is obeyed for AgNP synthesized from soluble precursors in homogeneous media. The behavior is modeled assuming the formation of a tridimensional supramolecular structure from silver ions / CS´s amino groups coordination complexes, driving the crosslinking within polymer folding and aggregation in shaping random coils. These structures become reactive precursor structures, that behave as microreactors during thermal treatment, and AgNP size are modulated by controlling the amino groups to silver ion ratio. Stabilized AgNP of high quality are easily produced from an environment-friendly synthetic system, which requires low cost reagents and demands simple and safe laboratory procedures.

Plasmon-induced hot-carrier generation differences in gold and silver nanoclusters.

In the last thirty years, the study of plasmonic properties of noble metal nanostructures has become a very dynamic research area. The design and manipulation of matter in the nanometric scale demands a deep understanding of the underlying physico-chemical processes that operate in this size regimen. Here, a fully atomistic study of the spectroscopic and photodynamic properties of different icosahedral silver and gold nanoclusters has been carried out by using a Time-Dependent Density Functional Tight-Binding (TD-DFTB) model. The optical absorption spectra of different icosahedral silver and gold nanoclusters of diameters between 1 and 4 nanometers have been simulated. Furthermore, the energy absorption process has been quantified by means of calculating a fully quantum absorption cross-section using the information contained in the reduced single-electron density matrix. This approach allows us take into account the quantum confinement effects dominating in this size regime. Likewise, the plasmon-induced hot-carrier generation process under laser illumination has been explored from a fully dynamical perspective. We have found noticeable differences in the energy absorption mechanisms and the plasmon-induced hot-carrier generation process in both metals which can be explained by their respective electronic structures. These differences can be attributed to the existence of ultra-fast electronic dissipation channels in gold nanoclusters that are absent in silver nanoclusters. To the best of our knowledge, this is the first report that addresses this topic from a real time fully atomistic time-dependent approach.

Electronic structure benchmark calculations of inorganic and biochemical carboxylation reactions.

Carboxylation reactions represent a very special class of chemical reactions that is characterized by the presence of a carbon dioxide (CO2 ) molecule as reactive species within its global chemical equation. These reactions work as fundamental gear to accomplish the CO2 fixation and thus to build up more complex molecules through different technological and biochemical processes. In this context, a correct description of the CO2 electronic structure turns out to be crucial to study the chemical and electronic properties associated with this kind of reactions. Here, a systematic study of CO2 electronic structure and its contribution to different carboxylation reaction electronic energies has been carried out by means of several high-level ab initio post-Hartree Fock (post-HF) and density functional theory (DFT) calculations for a set of biochemistry and inorganic systems. We have found that for a correct description of the CO2 electronic correlation energy it is necessary to include post-CCSD(T) contributions (beyond the gold standard). These high-order excitations are required to properly describe the interactions of the four π-electrons associated with the two degenerated π-molecular orbitals of the CO2 molecule. Likewise, our results show that in some reactions it is possible to obtain accurate reaction electronic energy values with computationally less demanding methods when the error in the electronic correlation energy compensates between reactants and products. Furthermore, the provided post-HF reference values allowed to validating different DFT exchange-correlation functionals combined with different basis sets for chemical reactions that are relevant in biochemical CO2 fixing enzymes. © 2019 Wiley Periodicals, Inc.

Communication: Photoinduced carbon dioxide binding with surface-functionalized silicon quantum dots.

Nowadays, the search for efficient methods able to reduce the high atmospheric carbon dioxide concentration has turned into a very dynamic research area. Several environmental problems have been closely associated with the high atmospheric level of this greenhouse gas. Here, a novel system based on the use of surface-functionalized silicon quantum dots (sf-SiQDs) is theoretically proposed as a versatile device to bind carbon dioxide. Within this approach, carbon dioxide trapping is modulated by a photoinduced charge redistribution between the capping molecule and the silicon quantum dots (SiQDs). The chemical and electronic properties of the proposed SiQDs have been studied with a Density Functional Theory and Density Functional Tight-Binding (DFTB) approach along with a time-dependent model based on the DFTB framework. To the best of our knowledge, this is the first report that proposes and explores the potential application of a versatile and friendly device based on the use of sf-SiQDs for photochemically activated carbon dioxide fixation.

Effects of oxidation on the plasmonic properties of aluminum nanoclusters.

The scouting of alternative plasmonic materials able to enhance and extend the optical properties of noble metal nanostructures is on the rise. Aluminum is endowed with a set of interesting properties which turn it into an attractive plasmonic material. Here we present the optical and electronic features of different aluminum nanostructures stemming from a multilevel computational study. Molecular Dynamics (MD) simulations using a reactive force field (ReaxFF), carefully validated with Density Functional Theory (DFT), were employed to mimic the oxidation of icosahedral aluminum nanoclusters. Resulting structures with different oxidation degrees were then studied through the Time-Dependent Density Functional Tight Binding (TD-DFTB) method. A similar approach was used in aluminum nanoclusters with a disordered structure to study how the loss of crystallinity affects the optical properties. To the best of our knowledge, this is the first report that addresses this issue from the fully atomistic time-dependent approach by means of two different and powerful simulation tools able to describe quantum and physicochemical properties associated with nanostructured particles.

Plasmon-driven sub-picosecond breathing of metal nanoparticles.

We present the first real-time atomistic simulation on the quantum dynamics of icosahedral silver nanoparticles under strong laser pulses, using time dependent density functional theory (TDDFT) molecular dynamics. We identify the emergence of sub-picosecond breathing-like radial oscillations starting immediately after laser pulse excitation, with increasing amplitude as the field intensity increases. The ultrafast dynamic response of nanoparticles to laser excitation points to a new mechanism other than equilibrium electron-phonon scattering previously assumed, which takes a much longer timescale. A sharp weakening of all bonds during laser excitation is observed, thanks to plasmon damping into excited electrons in anti-bonding states. This sudden weakening of bonds leads to a uniform expansion of the nanoparticles and launches coherent breathing oscillations.

One-step/one-pot decoration of oxide microparticles with silver nanoparticles.

HYPOTHESIS: Heterogeneous nucleation of silver oxide (Ag2O) onto oxide microparticles (OMPs) followed by spontaneous thermal decomposition produce nanostructures made of OMPs decorated with silver nanoparticles (OMP|AgNPs). EXPERIMENTS: Colloidal chemistry methods have been used to produce the decoration of OMPs with silver nanoparticles (AgNPs), by carrying out the Ag2O precipitation/thermal decomposition. The process is driven in water enriched acetone medium containing NaOH, NH3, AgNO3 and SiO2MPs as substrate. Optical and morphological properties of OMP|AgNPs were characterized by using STEM, EDS, HRTEM and Raman spectroscopy. FINDINGS: A new synthetic method to decorate OMPs (TiO2, SiO2) with metallic AgNPs in a single step/single pot reaction is proven effective to produce OMP|AgNPs either in aqueous or water enriched media.