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The dihydroazulene/vinylheptafulvene (DHA/VHF) photocouple is a promising candidate for molecular solar heat batteries, storing and releasing energy in a closed cycle. Much work has been done on improving the energy storage capacity and the half-life of the high-energy isomer via substituent functionalization, but similarly important is keeping these improved properties in common polar solvents, along with being soluble in these, which is tied to the dipole properties. However, the number of possible derivatives makes an overview of this combinatorial space impossible both for experimental work and traditional computational chemistry. Due to the time-consuming nature of running many thousands of computations, we look to machine learning, which bears the advantage that once a model has been trained, it can be used to rapidly estimate approximate values for the given system. Applying a convolutional neural network, we show that it is possible to reach good agreement with traditional computations on a scale that allows us to rapidly screen tens of thousands of the DHA/VHF photocouple, eliminating bad candidates and allowing computational resources to be directed toward meaningful compounds.

The single-molecule conductance of saturated molecules can potentially be fully suppressed by destructive quantum interference in their σ-system. However, only few molecules with σ-interference have been identified and the structure-property relationship remains to be elucidated. Here, we explore the role of substituents in modulating the electronic transmission of saturated molecules. In functionalized bicyclo[2.2.2]octanes, the transmission is suppressed by σ- interference when fluorine substituents are applied. For bicyclo[2.2.2]octasilane and - octagermanes the transmission is suppressed when carbon-based substituents are used, and such molecules are likely to be highly insulating. For the carbon-based substituents we find a strong correlation between the appropriate Hammett constants and the transmission. The substituent effect enables systematic optimization of the insulating properties of saturated molecular cores.

Identifying synthetic routes for molecules of interest is a crucial step when discovering new drugs or materials. To find synthetic routes, we can use computer-assisted synthesis planning using expansion policy networks trained on reaction templates extracted from patents and the literature. However, experience has shown that these networks are biased towards frequently reported reactions. This study shows that changing the molecular representation from an extended-connectivity fingerprint to a simple graph representation can increase the accuracy for templates used less than five times by 5.0- 8.5% points. We also illustrate that a simple oversampling of the training set yielded a top-1 accuracy increase in the 17-20% point range for templates used five times or less.

We present a computational methodology for the screening of a chemical space of 10²⁵ substituted norbornadiene molecules for promising kinetically stable molecular solar thermal (MOST) energy storage systems with high energy densities that absorb in the visible part of the solar spectrum. We use semiempirical tight-binding methods to construct a dataset of nearly 34,000 molecules and train graph convolutional networks to predict energy densities, kinetic stability, and absorption spectra and then use the models together with a genetic algorithm to search the chemical space for promising MOST energy storage systems. We identify 15 kinetically stable molecules, five of which have energy densities greater than 0.45 MJ/kg and the main conclusion of this study is that the largest energy density that can be obtained for a single norbornadiene moiety with the substituents considered here, while maintaining a long half-life and absorption in the visible spectrum, is around 0.55 MJ/kg.

The loss of a Cl atom from metastable CH2Cl2+ in the mass-analyzed ion kinetic energy experiment is characterized by a borderline zero kinetic energy release and large kinetic isotope effects on chlorine and hydrogen. Ab initio calculations are employed to assist the interpretation in terms of a nonadiabatic reaction involving electronic predissociation of the electronically excited state 2A1 and two-dimensional reaction dynamics. Strong curvature in the reaction coordinate leads to a bobsled effect that accounts for the low kinetic energy release. The kinetic isotope effects enter via the predissociation rate and are interpreted in terms of vibrational overlap integrals.

Molecules comprised of three covalently linked bi-stable switches can exist in states described by a combination of binary numbers, one for each individual switch: ⟨000⟩, ⟨001⟩, etc. Here we have linked three photo-/thermoswitches together in a rigid macrocyclic structure, one azobenzene (bit no 1) and two dihydroazulenes (DHAs; bits no 2 and 3) and demonstrate how electronic interactions and unfavorable strain in some states can be used to control the speed by which a certain state is reached. More specifically, upon irradiation of state ⟨000⟩, the AZB isomerizes from trans to cis and the two DHAs to vinylheptafulvenes (VHFs), generating ⟨111⟩. The thermal VHF-to-DHA back-reactions from this state also occur stepwise and can be accelerated by photo-induced AZB cis-to-trans conversion, proceeding via ⟨011⟩ to ultimately furnish ⟨000⟩. Overall, the accessibility to a specific state of one bit was found to depend on the states of its neighboring bits.

We investigate the performance of four different density functional theory (DFT) functionals (M06-2X, ωB97X-D, PBE0, and B3LYP-D3BJ) for calculating the structural and thermochemical properties of the dihydroazulene/vinylheptafulvene photoswitch (DHA/VHF). We find that all the tested DFT functionals yield equilibrium geometries in good agreement with higher level CCSD/cc-pVDZ calculations and that the basis set had little influence on the geometries of the photoswitch. We found a negligible difference in the thermal contribution to the Gibbs free energy between the tested functionals, indicating that the largest source of error when calculating storage free energies originates from errors in the calculated single point energies. It was found that ωB97X-D and M06-2X performed decently for predicting storage energies. While B3LYP-D3BJ and PBE0 generally underestimated the storage energy compared to CCSD(T)-F12a/VDZ-F12 results. Therefore, we tested if domain based local pair natural orbital coupled-cluster (DLPNO-CCSD(T)) provided an improvement over density functional theory methods for the single point energies. We observed that the DLPNO-CCSD(T) storage energies were in better agreement with CCSD(T)-F12a/VDZ-F12 results than the DFT results. The DLPNO-CCSD(T) results already converged at cc-pVTZ quality basis set, making it possible to perform accurate estimates of the thermochemical properties in a time frame that makes the DLPNO-CCSD(T) method feasible for routine calculations on the photoswitch. Using DLPNO-CCSD(T)/cc-pVTZ, we calculate accurate storage energies for currently synthesized derivatives of the DHA/VHF photoswitch.

The dihydroazulene/vinylheptafulvene (DHA/VHF) thermocouple is a promising candidate for thermal heat batteries that absorb and store solar energy as chemical energy without the need for insulation. However, in order to be viable the energy storage capacity and stability of the high energy form (the free energy barrier to the back reaction) must be increased significantly. We use semiempirical quantum chemical methods, machine learning, genetic algorithms, and density functional theory to virtually screen roughly 200 billion substituted DHA molecules to identify promising candidates for further study. We identify three molecules with predicted energy densities of (0.34-0.36 kJ/g), which is significantly larger than the 0.14 kJ/g computed for the parent system. The free energy barriers to the back reaction are between 6.8 and 7.7 kJ/mol higher than the parent compound, which should correspond to half-lives of days - sufficiently long for many practical applications.

The dihydroazulene/vinylheptafulvene (DHA/VHF) thermocouple is a promising candidate for thermal heat batteries that absorb and store solar energy as chemical energy without the need for insulation. However, in order to be viable the energy storage capacity and lifetime of the high energy form (i.e. the free energy barrier to the back reaction) of the canonical parent compound must be increased significantly to be of practical use. We use semiempirical quantum chemical methods, machine learning, and density func- tional theory to virtually screen over 230 billion substituted DHA molecules to identify promising candidates. We identify a molecule with a predicted energy density of 0.38 kJ/g, which is significantly larger than the 0.14 kJ/g computed for the parent compound. The free energy barrier to the back reaction is 11 kJ/mol higher than the parent com- pound, which should correspond to a half-life of about 10 days - 4 months. This is considerably longer than the 3-39 hours (depending on solvent) observed for the parent compound and sufficiently long for many practical applications. Our paper makes two main important contributions: 1) a novel and generally applicable methodological approach that makes screening of huge libraries for properties involving chemical reactivity with modest computational resources, and 2) a clear demonstration that the storage capacity of the DHA/VHF thermocouple cannot be increased to >0.5 kJ/g by combining simple substituents.

The electronic transmission through σ-conjugated molecules can be fully suppressed by destructive quantum interference, which makes them potential candidates for single-molecule insulators. The first molecule with clear suppression of the single-molecule conductance due to σ-interference was recently found in the form of a functionalized bicyclo[2.2.2]octasilane. Here we continue the search for potential single-molecule insulators based on saturated group 14 molecules. Using a high-throughput screening approach, we assess the electron transport properties of the bicyclo[2.2.2]octane class by systematically varying the constituent atoms between carbon, silicon, and germanium, thus exploring the full chemical space of 771 different molecules. The majority of the molecules in the bicyclo[2.2.2]octane class are found to be highly insulating molecules. Though the all-silicon molecule is a clear-cut case of σ-interference, it is not unique within its class and there are many potential molecules that we predict to be more insulating. The finding of this class of quantum interference based single-molecule insulators indicates that a broad range of highly insulating saturated group 14 molecules are likely to exist

Upon direct excitation with green light (522 nm), Er3+ ion doped nanoparticles feature a number of radiative and non-radiative decay pathways, leading to distinct and sharp emission lines in the visible and near-infrared (NIR) range. Here we apply, in addition to continuous 522 nm irradiation, a modulated NIR irradiation (1143 nm) to actively control and modulate the red emission intensity (around 650 nm). The modulation of red Er3+ ion emission at a chosen frequency allows us to reconstruct fluorescence images from the Fourier transform amplitude at this particular frequency. Since only the emission from the Er3+ ion is modulated, it allows to selectively recover the lanthanide specific signal, removing any non-modulated auto-fluorescence or background emission resulting from the continuous 522 nm excitation. The modulated emission of specific lanthanides can open up new detection opportunities for selective signal recovery.

Photon upconversion facilitated by triplet–triplet annihilation in molecular systems is a promising path toward utilization of sub bandgap photons in photovoltaic devices. Prior to the challenging synthesis of new molecules, quantum chemical computations can aid the design process and provide suggestions for new and optimal systems. Here, we benchmark time-dependent density functional methods by their ability to describe relevant photophysical quantities of a range of different types of sensitizer/annihilator pairs to provide guidelines for future computational studies of potential new pairs. Using meta-GGA, hybrid, and range-separated hybrid functionals, we find that the hybrid functionals B3LYP and PBE0 (incorporating low to medium fractions of exact exchange of 20% and 25%, respectively) describe singlet absorptions the best, while triplet energetics are best described by the meta-GGA functionals M06-L and M11-L (incorporating no exact exchange), respectively. Furthermore, we find that the Tamm–Dancoff approximation of time-dependent density functional theory in general does not improve the description of neither singlet nor triplet energies of sensitizer/annihilator pairs.