Direct Experimental Observation of in situ Dehydrogenation of an Amine-Borane System Using Gas Electron Diffraction

In situ dehydrogenation of azetidine-BH3, which is a candidate for hydrogen storage, was observed with the parent and dehydrogenated analogue subjected to rigorous structural and thermochemical investigations. The structural analyses utilized gas electron diffraction supported by high-level quantum calculations, while the pathway for the unimolecular hydrogen release reaction in the absence and presence of BH3 as a bifunctional catalyst was predicted at the CBS-QB3 level. The catalyzed dehydrogenation pathway has a barrier lower than the predicted B-N bond dissociation energy, hence favoring the dehydrogenation process over the dissociation of the complex. The predicted enthalpy of dehydrogenation at the CCSD(T)/CBS level indicates that mild reaction conditions would be required for hydrogen release and that the compound is closer to thermoneutral than linear amine boranes. The entropy and free energy change for the dehydrogenation process show that the reaction is exergonic, energetically feasible, and will proceed spontaneously toward hydrogen release, all of which are important factors for hydrogen storage

Volatile and thermally stable polymeric tin trifluoroacetates

Tin trifluoroacetates are effective vapor phase single-source precursors for F-doped SnO2, but their structures have been poorly understood for decades. Here we undertook a comprehensive structural analysis of these compounds in both the solid and gas phases through a combined single-crystal X-ray crystallography, gas phase electron diffraction, and density functional theory investigation. Tin(II) bis(trifluoroacetate) (1) thermally decomposes into a 1:1 mixture of 1 and ditin(II) μ-oxybis(μ-trifluoroacetate) (2) during sublimation, which then polymerize into hexatin(II)-di-μ3-oxyoctakis(μ-trifluoroacetate) (3) upon solidification. Reversible depolymerization occurred readily upon heating, making 3 a useful vapor phase precursor itself. Tin(IV) tetrakis(trifluoroacetate) (5) was also found to be polymeric in the solid state, but it evaporated as a monomer over 130 °C lower than 3. This counterintuitive improvement in volatility by polymerization was possibly due to the large entropy change during sublimation, which offers a strategic new design feature for vapor phase deposition precursors

The structure of tris(chloromethyl)amine in the gas phase using quantum chemical calculations and gas electron diffraction and as a solid and melt using Raman spectroscopy

The equilibrium structure of tris(chloromethyl)amine, N(CH2Cl)3, has been determined in the gas phase using electron diffraction. Single-step distance corrections (representing the differences between the interatomic distances from the equilibrium structure and those from the vibrationally averaged structure) and amplitudes of vibration have been computed using semi-empirical molecular dynamics (SE-MD) simulations in order to treat accurately the description of the low-frequency, large-amplitude vibrational modes associated particularly with one CH2Cl group. A series of complementary theoretical calculations using the SOGGA11-X DFT functional with correlation-consistent basis sets of double-, triple-, and quadruple-ζ quality is also presented. The agreement between the experimental and theoretical equilibrium structural parameters attests to the accuracy of the applied theoretical calculations and of our gas-phase structural solution. Raman spectra have been recorded over a range of temperatures, allowing the solid and the melt to be studied, and the Raman-active intramolecular modes to be identified. Free from the influence of intermolecular interaction, the structure of tris(chloromethyl)amine in the gas phase is markedly different to that reported in the literature for the single crystal. This is discussed, and evidence for the anomeric effect in tris(chloromethyl)amine is evaluated

Structure of 4-(Dimethylamino)benzonitrile Using Gas Electron Diffraction : A New Lease of Life for the Only Gas Electron Diffractometer in the UK

The continued demand for gas-phase molecular structures has led to the recommissioning of a gas electron diffractometer, formerly housed at the University of Reading. The gas electron diffractometer, now the only one of its kind in the U.K., is currently housed at the University of York, where it is now used routinely to determine directly structures of isolated molecules in the gas phase. The instrument has been fitted with an air-heated nozzle assembly to increase the range of molecules accessible to study in the gas phase; the efficacy of this assembly is demonstrated in this article via the determination of the gas-phase structure of 4-(dimethylamino)benzonitrile (DMABN) at high temperature. A series of complementary theoretical calculations using the B2PLYP DFT functional of Grimme et al. with correlation-consistent basis sets of double, triple, and quadruple-ζ quality are also presented. The agreement between the experimental and theoretical structural parameters attests to the accuracy of the applied theoretical calculations and of our gas-phase structural solution

Structure retrieval in liquid-phase electron scattering

Electron scattering on liquid samples has been enabled recently by the development of ultrathin liquid sheet technologies. The data treatment of liquid-phase electron scattering has been mostly reliant on methodologies developed for gas electron diffraction, in which theoretical inputs and empirical fittings are often needed to account for the atomic form factor and remove the inelastic scattering background. The accuracy and impact of these theoretical and empirical inputs has not been benchmarked for liquid-phase electron scattering data. In this work, we present an alternative data treatment method that requires neither theoretical inputs nor empirical fittings. The merits of this new method are illustrated through the retrieval of real-space molecular structure from experimental electron scattering patterns of liquid water, carbon tetrachloride, chloroform, and dichloromethane

Structure retrieval in liquid-phase electron scattering

Electron scattering on liquid samples has been enabled recently by the development of ultrathin liquid sheet technologies. The data treatment of liquid-phase electron scattering has been mostly reliant on methodologies developed for gas electron diffraction, in which theoretical inputs and empirical fittings are often needed to account for the atomic form factor and remove the inelastic scattering background. In this work, we present an alternative data treatment method that is able to retrieve the radial distribution of all the charged particle pairs without the need of either theoretical inputs or empirical fittings. The merits of this new method are illustrated through the retrieval of real-space molecular structure from experimental electron scattering patterns of liquid water, carbon tetrachloride, chloroform, and dichloromethane. Shown here is the arXiv version

Atmospheric breakdown chemistry of the new "green" solvent 2,2,5,5-tetramethyloxolane via gas-phase reactions with OH and Cl radicals

The atmospheric chemistry of 2,2,5,5-tetramethyloxolane (TMO), a promising "green"solvent replacement for toluene, was investigated in laboratory-based experiments and computational calculations. Results from both absolute and relative rate studies demonstrated that the reaction OH + TMO (Reaction R1) proceeds with a rate coefficient k1(296 K) = (3.1±0.4) ×10-12 cm3 molecule-1 s-1, a factor of 3 smaller than predicted by recent structure-activity relationships. Quantum chemical calculations (CBS-QB3 and G4) demonstrated that the reaction pathway via the lowest-energy transition state was characterised by a hydrogen-bonded pre-reaction complex, leading to thermodynamically less favoured products. Steric hindrance from the four methyl substituents in TMO prevents formation of such H-bonded complexes on the pathways to thermodynamically favoured products, a likely explanation for the anomalous slow rate of Reaction (R1). Further evidence for a complex mechanism was provided by k1(294-502 K), characterised by a local minimum at around T=340 K. An estimated atmospheric lifetime of τ1 ≈3 d was calculated for TMO, approximately 50 % longer than toluene, indicating that any air pollution impacts from TMO emission would be less localised. An estimated photochemical ozone creation potential (POCPE) of 18 was calculated for TMO in north-western Europe conditions, less than half the equivalent value for toluene. Relative rate experiments were used to determine a rate coefficient of k2(296 K) = (1.2±0.1) ×10-10 cm3 molecule-1 s-1 for Cl + TMO (Reaction R2); together with Reaction (R1), which is slow, this may indicate an additional contribution to TMO removal in regions impacted by high levels of atmospheric chlorine. All results from this work indicate that TMO is a less problematic volatile organic compound (VOC) than toluene

Beyond Structural Insight : A Deep Neural Network for the Prediction of Pt L2/3-edge X-ray Absorption Spectra

X-ray absorption spectroscopy at the L2/3 edge can be used to obtain detailed information about the local electronic and geometric structure of transition metal complexes. By virtue of the dipole selection rules, the transition metal L2/3 edge usually exhibits two distinct spectral regions: (i) the “white line”, which is dominated by bound electronic transitions from metal-centred 2p orbitals into unoccupied orbitals with d character; the intensity and shape of this band consequently reflects the d density of states (d-DOS), which is strongly modulated by mixing with ligand orbitals involved in chemical bonding, and (ii) the post-edge, where oscillations encode the local geometric structure around the X-ray absorption site. In this Article, we extend our recently-developed XANESNET deep neural network (DNN) beyond the K-edge to predict X-ray absorption spectra at the Pt L2/3 edge. We demonstrate that XANESNET is able to predict Pt L2/3 -edge X-ray absorption spectra, including both the parts containing electronic and geometric structural information. The performance of our DNN in practical situations is demonstrated by application to two Pt complexes, and by simulating the transient spectrum of a photoexcited dimeric Pt complex. Our discussion includes an analysis of the feature importance in our DNN which demonstrates the role of key features and assists with interpreting the performance of the network

An 'On-the-Fly' Deep Neural Network for Simulating Time-Resolved Spectroscopy : Predicting the Ultrafast Ring-Opening Dynamics of 1,2-Dithiane

Revolutionary developments in ultrafast light source technology are enabling experimental spectroscopists to probe the structural dynamics of molecules and materials on the femtosecond timescale. The capacity to investigate ultrafast processes afforded by these resources accordingly inspires theoreticians to carry out high-level simulations which facilitate the interpretation of the underlying dynamics probed during these ultrafast experiments. In this Article, we implement a deep neural network (DNN) to convert excited-state molecular dynamics simulations into time-resolved spectroscopic signals. Our DNN is trained on-the-fly from first-principles theoretical data obtained from a set of time-evolving molecular dynamics. The train-test process iterates for each time-step of the dynamics data until the network can predict spectra with sufficient accuracy to replace the computationally intensive quantum chemistry calculations required to produce them, at which point it simulates the time-resolved spectra for longer timescales. The potential of this approach is demonstrated by probing dynamics of the ring opening of 1,2-dithiane using sulphur K-edge X-ray absorption spectroscopy. The benefits of this strategy will be more markedly apparent for simulations of larger systems which will exhibit a more notable computational burden, making this approach applicable to the study of a diverse range of complex chemical dynamics

Enhancing the Analysis of Disorder in X-ray Absorption Spectra : Application of Deep Neural Networks to T-jump-X-ray Probe Experiments

Many chemical and biological reactions, including ligand exchange processes, require thermal energy for the reactants to overcome a transition barrier and reach the product state. Temperature-jump (T-jump) spectroscopy uses a near-infrared (NIR) pulse to rapidly heat a sample, offering an approach for triggering these processes and directly accessing thermally-activated pathways. However, thermal activation inherently increases the disorder of the system under study and, as a consequence, can make quantitative interpretations of structural changes challenging. In this Article, we optimise a deep neural network (DNN) for the instantaneous prediction of Co K-edge X-ray absorption near-edge structure (XANES) spectra. We apply our DNN to analyse T-jump pump/X-ray probe data pertaining to the ligand exchange processes and solvation dynamics of Co2+in chlorinated aqueous solution. Our analysis is greatly facilitated by machine learning, as our DNN is able to predict quickly and cost-effectively the XANES spectra of thousands of geometric configurations sampled fromab initiomolecular dynamics (MD) using nothing more than the local geometric environment around the X-ray absorption site. We identify directly the structural changes following the T-jump, which are dominated by sample heating and a commensurate increase in the Debye-Waller factor