Revealing the Influence of Secondary Metals on Redox-Active Palladium Complexes

Incorporation of redox-inactive metals into redox-active complexes and catalysts attracts attention for engendering new reactivity modes, but this strategy has not been extensively investigated beyond the first-row of the transition metals. Here, the isolation and characterization of the first series of heterobimetallic complexes of palladium with mono-, di-, and tri-valent redox-inactive metal ions are reported. A Reinhoudt-type heteroditopic ligand with a salen-derived [N2,O2] binding site for Pd and a crown-ether-derived [O6] site has been used to prepare isolable adducts of the Lewis acidic redox-inactive metal ions (Mn+). Comprehensive data from single-crystal X-ray diffraction analysis reveal distinctive trends in the structural properties of the heterobimetallic species, including an uncommon dependence of the Pd•••M distance on Lewis acidity. The reorganization energy associated with reduction of the heterobimetallic species is strongly modulated by Lewis acidity, with the slowest heterogeneous electron transfer kinetics associated with the strongest incorporated Lewis acids. This hitherto unexplored reorganization energy penalty for electron transfer contrasts with prior thermodynamic studies, revealing that kinetic parameters should be considered in studies of reactivity involving heterobimetallic species.

DFT Based Modeling of Asymmetric Non-Fullerene Acceptors for High-Performance Organic Solar Cell

AbstractFive new asymmetric NFA-based polymer solar cells i.e., N1-N5 are designed by doing modification in terminal groups of the acceptor part of experimentally synthesized reference molecule with (4,4,9,9-tetramethyl-4,9 dihydroselenopheno [2’,3’:5,6]-s-indaceno [1,2-b] thiophene) core. Frontier molecular orbital analysis is used to study their photovoltaic and optoelectronic properties. It confirmed the electrons' transportation from the donor to the acceptor part. It stated that all molecules have a lower bandgap than R and N2 has the lowest bandgap of 2.01 eV. The molecular orbital potential analysis confirmed the electron-withdrawing properties of the terminal groups. Optical properties studies evaluated maximum absorption with transition energies. All newly designed molecules N1-N5 show higher λmax values than R i.e., in the range of 680-740 nm with N2 having the highest λmax of 735 nm and lowest transition energy of 1.69 eV. Dipole moment studies showed that N3 has a maximum dipole moment of 7-40 D with all others having comparable values. TDM plots confirmed the electron shifting from donor to acceptor region. Reorganization energy analysis showed that N1 and N3 have the lowest reorganization energy values thus giving the highest electron mobilities. Voc calculated results of all molecules N1-N5 have lower values than R when coupled with PTB7-Th donor polymer. Charge transport analysis of N2 and PTB7-Th coupled molecule confirmed the acceptor type nature of our designed molecules.

Exciton transport in molecular organic semiconductors boosted by transient quantum delocalization

Designing molecular materials with very large exciton diffusion lengths would remove some of the intrinsic limitations of present-day organic optoelectronic devices. Yet, the nature of excitons in these materials is still not sufficiently well understood. Here we present Frenkel exciton surface hopping, a highly efficient method to propagate excitons through truly nano-scale materials by solving the time-dependent Schrödinger equation coupled to nuclear motion. We find a clear correlation between diffusion constant and quantum delocalization of the exciton. In materials featuring some of the highest diffusion lengths to date, e.g. the non-fullerene acceptor Y6, the exciton propagates via a transient delocalization mechanism, reminiscent to what was recently proposed for charge transport. Yet, the extent of delocalization is rather modest, even in Y6, and found to be limited by the relatively large exciton reorganization energy. On this basis we chart out a path for rationally improving exciton transport in organic optoelectronic materials.

AutoSolvate: A Toolkit for Automating Quantum Chemistry Design and Discovery of Solvated Molecules

The availability of large, high-quality data sets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational data set generation of solution-phase molecular properties at the quantum mechanical level of theory was previously hampered by the complicated simulation procedure. Software toolkits that can automate the procedure to set up high-throughput explicit-solvent quantum chemistry (QC) calculations for arbitrary solutes and solvents in an open-source framework are still lacking. We developed AutoSolvate, an open-source toolkit to streamline the workflow for QC calculation of explicitly solvated molecules. It automates the solvated-structure generation, force field fitting, configuration sampling, and the final extraction of microsolvated cluster structures that QC packages can readily use to predict molecular properties of interest. AutoSolvate is available through both a command line interface and a graphical user interface, making it accessible to the broader scientific community. To improve the quality of the initial structures generated by AutoSolvate, we investigated the dependence of solute-solvent closeness on solute/solvent identities and trained a machine learning model to predict the closeness and guide initial structure generation. Finally, we tested the capability of AutoSolvate for rapid data set curation by calculating the outer-sphere reorganization energy of a large data set of 166 redox couples, which demonstrated the promise of the AutoSolvate package for chemical discovery efforts.

Small reorganization energy acceptors enable low energy losses in non-fullerene organic solar cells

Minimizing the energy loss is of critical importance in the pursuit of attaining high-performance organic solar cells (OSCs). Interestingly, electron-vibration coupling (namely reorganization energy) plays a crucial role in the photo-electric conversion processes. However, a molecular understanding of the relationship between the reorganization energy and the energy loss has rarely been studied. Here, two new acceptors Qx-1 and Qx-2 with quinoxaline (Qx)-containing fused core were designed and synthesized. The results indicate that the reorganization energies of these two acceptors during the photoelectric conversion processes are substantially smaller than the conventional Y6 acceptor, which is beneficial for improving the exciton lifetime and diffusion length, promoting charge transport and reducing the energy loss originating from exciton dissociation and non-radiative recombination. As a result, an outstanding power conversion efficiency (PCE) of 18.2% with high Voc above 0.93 V in the PM6:Qx-2 blend, accompanying a significantly reduced energy loss of 0.48 eV. To the best of our knowledge, the obtained energy loss is the smallest for the binary OSCs with PCEs over 16% reported to date. This work underlines the importance of the reorganization energy in achieving small energy loss in organic active materials and paves a new way to obtain high-performance OSCs.

Theoretical modeling of Ring-Locked S-shaped acceptor molecules for High-Performance Organic Solar Cells

The introduction of a bridge element to covalently ring-lock the neighboring aryl or heteroaryl groups connected by a single bond has led to a variety of fascinating multifused ladder-type structures. Here, we have designed a new series of 2H-pyran containing tetracyclic dithienocyclopentapyran compounds (MMA1 to MMA3). Long conjugation at end-capped of designed systems enhances the power conversion efficiencies of non-fullerene-containing organic solar cells. Different geometric parameters of designed systems have been examined through density functional theory and time-dependent density function theory. Designed molecules expressed high absorption maxima values with a reduced energy bandgap. Open circuit voltage along with transition density matrix analysis recommended that charge transfer occurs from lower energy orbitals to higher energy orbitals. Reorganization energy analysis also suggested high charge mobility occurs from donor polymer to acceptor molecules. Results of all parameters advocated that designed molecules are potential candidates for high-performance organic solar cells.

Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics

Exploring excitation energy transfer (EET) in light-harvesting complexes (LHCs) is essential for understanding the natural processes and design of highly-efficient photovoltaic devices. LHCs are open systems, where quantum effects may play a crucial role for almost perfect utilization of solar energy. Simulation of energy transfer with inclusion of quantum effects can be done within the framework of dissipative quantum dynamics (QD), which are computationally expensive. Thus, artificial intelligence (AI) offers itself as a tool for reducing the computational cost. We suggest AI-QD approach using AI to directly predict QD as a function of time and other parameters such as temperature, reorganization energy, etc., completely circumventing the need of recursive step-wise dynamics propagation in contrast to the traditional QD and alternative, recursive AI-based QD approaches. Our trajectory-learning AI-QD approach is able to predict the correct asymptotic behavior of QD at infinite time. We demonstrate AI-QD on seven-sites Fenna–Matthews–Olson (FMO) complex.

Reorganization energies of flexible organic molecules as a challenging target for machine learning enhanced virtual screening

The molecular reorganization energy $\lambda$ strongly influences the charge carrier mobility of organic semiconductors and is therefore an important target for molecular design. Machine learning (ML) models generally have the potential to strongly accelerate this design process (e.g. in virtual screening studies) by providing fast and accurate estimates of molecular properties. While such models are well established for simple properties (e.g. the atomization energy), $\lambda$ poses a significant challenge in this context. In this paper, we address the questions of how ML models for $\lambda$ can be improved and what their benefit is in high-throughput virtual screening (HTVS) studies. We find that, while improved predictive accuracy can be obtained relative to a semiempirical baseline model, the improvement in molecular discovery is somewhat marginal. In particular, the ML enhanced screenings are more effective in identifying promising candidates but lead to a less diverse sample. We further use substructure analysis to derive a general design rule for organic molecules with low $\lambda$ from the HTVS results.

Kinetics and Energetics of Intramolecular Electron Transfer in Single-Point Labeled TUPS-Cytochrome c Derivatives

Electron transfer within and between proteins is a fundamental biological phenomenon, in which efficiency depends on several physical parameters. We have engineered a number of horse heart cytochrome c single-point mutants with cysteine substitutions at various positions of the protein surface. To these cysteines, as well as to several native lysine side chains, the photoinduced redox label 8-thiouredopyrene-1,3,6-trisulfonate (TUPS) was covalently attached. The long-lived, low potential triplet excited state of TUPS, generated with high quantum efficiency, serves as an electron donor to the oxidized heme c. The rates of the forward (from the label to the heme) and the reverse (from the reduced heme back to the oxidized label) electron transfer reactions were obtained from multichannel and single wavelength flash photolysis absorption kinetic experiments. The electronic coupling term and the reorganization energy for electron transfer in this system were estimated from temperature-dependent experiments and compared with calculated parameters using the crystal and the solution NMR structure of the protein. These results together with the observation of multiexponential kinetics strongly support earlier conclusions that the flexible arm connecting TUPS to the protein allows several shortcut routes for the electron involving through space jumps between the label and the protein surface.

Kinetics of V5+/V4+ Redox Reaction – Butler-Volmer and Marcus Models

Kinetics of the V5+/V4+ redox reaction on Vulcan XC-72 modified glassy carbon disk electrode is investigated in a three-electrode configuration. Cyclic voltammograms of V5+/V4+ redox couple suggest that the overpotential range for the kinetic analysis is limited to ±300 mV, after excluding V4+/V3+ redox reaction at the negative overpotential and the oxygen evolution reaction at the positive overpotential. Therefore, the linear sweep-voltammograms (LSVs) are corrected for potential drop due to solution resistance (iRs), mass-transfer resistance, and most importantly, for the back reaction current. These corrections are imperative to estimate the Tafel slope in the limited range of overpotential for V5+/V4+ redox reaction. The charge-transfer coefficient (α) estimated from the Tafel slope deviates significantly from the expected value of 0.5 for the single electron-transfer reaction. Moreover, the instantaneous slope of the Tafel plot suggests that the α is overpotential dependent. Therefore, Marcus theory of electrochemical kinetics is applied to estimate the α. The reorganization energy (λ) calculated from the Arrhenius plots is in the range of values reported in the literature for the other redox couples.