Understanding the Photoprocesses in Biological Systems: Need for Accurate Multireference Treatment.

Light-matter interaction is crucial to life itself and revolves around many of the central processes in biology. The need for understanding these photochemical and photophysical processes cannot be overemphasized. Interaction of light with biological systems starts with the absorption of light and subsequent phenomena that occur in the excited states of the system. However, excited states are typically difficult to understand within the mean field approximation of quantum chemical methods. Therefore, suitable multireference methods and methodologies have been developed to understand these phenomena. In this Perspective, we will describe a few methods and methodologies suitable for these descriptions and discuss some persisting difficulties.

A nine-ring fused terrylene diimide exhibits switching between red TADF and near-IR room temperature phosphorescence.

Herein, we report the first example of a terrylene diimide derivative that switches emission between thermally activated delayed fluorescence (TADF) and room temperature phosphorescence (RTP) in the red region. By design, the molecule TDI-cDBT boasts a symmetrical, consecutively fused nine-ring motif with a kite-like structure. The rigid core formed by the annulated dibenzothiophene moiety favoured efficient intersystem crossing and yielded a narrow-band emission with a full-width half maxima (FWHM) of 0.09 eV, along with high colour purity. A small ΔE S1-T1 of 0.04 eV facilitated thermally activated delayed fluorescence, enhancing the quantum yield to 88% in the red region. Additionally, it also prefers a direct triplet emission from the aggregated state. The room temperature phosphorescence observed from the aggregates has a longer emission lifetime of 1.8 ms, which is further prolonged to 8 ms at 77 K in the NIR region. Thus, the current strategy is successful in not only reducing ΔE S1-T1 to favour TADF but also serves as a novel platform that can switch emission from TADF to RTP depending upon the concentration.

Conformational Effects on the Absorption Spectra of Phytochromes.

Bacteriophytochrome is a photoreceptor protein that contains the biliverdin (BV) chromophore as its active component. The spectra of BV upon mutation remain remarkably unchanged, as far as spectral positions are concerned. This points toward the minimal effect of electrostatic effects on the electronic structure of the chromophore. However, the relative intensities of the Q and Soret bands of the chromophore change dramatically upon mutation. In this work, we delve into the molecular origin of this unusual intensity modulation. Using extensive classical MD and QM/MM calculations, we show that due to mutation, the conformational population of the chromophore changes significantly. The noncovalent interactions, especially the stacking interactions, lead to extra stabilization of the cyclic form in the D207H mutated species as opposed to the open form in the wild-type BV. Thus, unlike the commonly observed direct electrostatic effect on the spectral shift, in the case of BV the difference observed is in varying intensities, and this in turn is driven by a conformational shift due to enhanced stacking interaction.

Structure prediction from spectra amidst dynamical heterogeneity in melanin.

Melanin is a biopolymer pigment that plays a central role in skin photoprotection. Its extensive chemical and dynamical heterogeneity imparts this property through a broad featureless ultraviolet/visible absorption spectrum. Conventionally, the rational design of synthetic photoprotective pigments revolves around establishing the structure-spectra correlation and developing biomimetic materials with desired optical properties. This approach fails to explain the mechanistic details of melanin's absorption spectrum because it arises from an ensemble of structures rather than a local minimum on the potential energy surface. Here, we propose an inverse design approach to elucidate the contributions of dominant chromophoric units in various wavelength domains of the melanin spectrum.

Machine Learning the Quantum Mechanical Wave Function.

Strongly correlated systems have been challenging to computational chemists for a long time. To solve these systems, multireference methods have been developed over the years. Recently, with the fast development of machine learning and artificial intelligence methods, these methods have also influenced the quest for optimal wave function ansatz. Machine learning approaches have been used in many different flavors. From this perspective, we will discuss the different milestones achieved in the use of machine learning for solving the quantum many body problem.

Eliminating all bonds from the ground state gives rise to ionic bonding in high-spin states of heterodiatomics.

Understanding chemical bonding in second-row diatomics has been central to elucidating the basics of bonding itself. Bond strength and the number of bonds are the two factors that decide the reactivity of molecules. While bond strengths have been theoretically computed accurately and experimentally determined, the number of bonds is a more contentious issue, especially for complicated multi-reference systems like C2. We have developed an experimentally verifiable approach to determine bond numbers from excited spin state potential energy surfaces. On applying this to a series of second-row heterodiatomics, we obtain the surprising phenomenon of an inverted charge transfer ionic state after all the ground state bonds are broken via higher spin states. These ionic states are ubiquitous in all heterodiatomics and unexpected in non-metallic systems.

Efficient Machine Learning Configuration Interaction for Bond Breaking Problems.

Machine learning-assisted configuration interaction (MLCI) has been shown earlier as a promising method in determining the electronic structure of the model and molecular Hamiltonians. In the MLCI approach to molecular Hamiltonians, it has been noticed that prediction is strongly dependent on the connectedness of the training and validation spaces. In this work, we have tested three different models with different output parameters (abs-MLCI, transformed-MLCI, and log-MLCI) to verify the robustness of training these models. We define robustness as the extent of error in prediction even when the spaces (training and validation) are not connected. We notice that the log-MLCI model is best suited to this approach and is therefore a powerful model for accurate one-shot variational energies. This is tested for chemical bond breaking in water, carbon monoxide, nitrogen, and dicarbon molecules.

Machine learning matrix product state ansatz for strongly correlated systems.

Machine learning (ML) has been used to optimize the matrix product state (MPS) ansatz for the wavefunction of strongly correlated systems. The ML optimization of MPS has been tested for the Heisenberg Hamiltonian on one-dimensional and ladder lattices, which correspond to conjugated molecular systems. The input descriptors and output for the supervised ML are lattice configurations and configuration interaction coefficients, respectively. Efficient learning can be achieved from data over the full Hilbert space via exact diagonalization or full configuration interaction, as well as over a much smaller sub-space via Monte Carlo Configuration Interaction. We show that this circumvents the need to calculate energy and operator expectation values and is therefore a computationally efficient alternative to variational optimization.

Active Learning Assisted MCCI to Target Spin States.

Strongly correlated systems and their accurate solutions have been challenging to quantum chemistry. Several methods have been developed over the years for the accurate understanding of such systems, and selected configuration interaction and Monte Carlo configuration interaction (MCCI) form important classes of systems in this category. However, MCCI is plagued by slow convergence. This is further exacerbated by the fact that most of the current MCCI implementations do not target specific spin states. In our work, we use active learning assisted MCCI to speed up the convergence manyfold and also develop a method for spin targeting. This method has been tested with several model Hamiltonian systems akin to molecular systems and has shown improved convergence and accuracy.

Curious Case of Singlet Triplet Gaps in Nonlinear Polyaromatic Hydrocarbons.

The singlet triplet (ST) gap of linear polyacenes decays exponentially with the system size as a result of extended conjugation and reducing highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gaps. These low ST gaps can ideally be leveraged toward energy applications but are hindered by the decreasing stability of the systems. Thus, there is the need to understand the ST gap of nonlinear polyacenes, which are markedly more stable than their linear counterparts. Here, we show that the ST gaps of the nonlinear polyacenes do not decrease with the system size and have no correlation with the HOMO-LUMO gaps or increased conjugation. The reason behind this is identified as the high multireference character of the triplet high-spin state. These unprecedented results are in stark contrast to the observations in linear polyacenes and are due to the combined effects of topology and geometrical factors.

Substitution enables significant new decay channels for a non-canonical amino acid.

UV-Vis absorption spectra and emission peaks of indole and 7-fluoroindole are measured and it is observed that 7-fluoroindole quenches the fluorescence signals significantly compared to indole. This observation is elucidated via reconstruction of the potential energy surfaces, determination of the conical intersections, and dynamical studies. It is observed that a single fluorine substitution on indole leads to the appearance of several accessible low-energy conical intersections that cause fast nonradiative decay. In this paper, we have investigated the nonradiative processes of Ind and 7F-Ind theoretically using high-level methods, such as EOM-EE-CCSD, SA-CASSCF, MS-CASPT2/6-311++G(d,p) levels of theory, to study these pathways and their feasibility.

Mechanism of Singlet Fission in Carotenoids from a Polyene Model System.

Singlet fission (SF) is the process of formation of multiple excitons (triplet) from a locally excited singlet state. The mechanism of SF in polyacenes has been shown to proceed via a charge transfer intermediate state. However, carotenoids are not understood in the context of SF. This is possibly due to the complicated multireference nature of the low-lying excited states of carotenoids and the presence of a dark 21Ag state below the optically bright 1Bu state. In this work, we show that the dark Ag state in polyenes and/or carotenoids, along with the charge transfer states, plays a pivotal role in the SF process. We notice that the relative importance of these states varies with a change in geometry and the overall presence of multiple pathways is crucial to the success of the SF process in carotenoid aggregates and disordered geometries.

Radiationless Decay Processes of an Unnatural DNA Base: Pyrrole 2-Carbaldehyde.

Pyrrole-2-carbaldehyde (Pa) forms one of the unnatural nucleic acid bases, and as a base pair with 7-(2-thienyl)imidazo[4,5-b]pyridine (Ds), it has been known to be stable in DNA. The Ds-Pa pair is stabilized in DNA via van der Waals' interaction and shape fitting. There are some studies on the origin of its stability and reactivity in the ground state. However, for a successful unnatural base pair, it needs to be stable not only in the ground state but also upon irradiation with UV-visible light. To understand the photoinduced reactivity, we investigate the excited-state properties of the Pa base and understand the energetically feasible photoprocesses that can occur upon excitation in the UV region. Two distinct pathways are obtained. One of the pathways involves an out-of-plane mode and has some similarities with the deactivation channels in the natural pyrimidine bases. On the other hand, the second pathway involves an excited-state proton transfer.

Electron Attachment to Cytosine: The Role of Water.

We present an EOM-CCSD-based quantum mechanical/molecular mechanical (QM/MM) study on the electron attachment process to solvated cytosine. The electron attachment in the bulk solvated cytosine occurs through a doorway mechanism, where the initial electron is localized on water. The electron is subsequently transferred to cytosine by the mixing of electronic and nuclear degrees of freedom, which occurs on an ultrafast time scale. The bulk water environment stabilizes the cytosine-bound anion by an extensive hydrogen-bond network and drastically enhances the electron transfer rate from that observed in the gas phase. Microhydration studies cannot reproduce the effect of the bulk water environment on the electron attachment process, and one needs to include a large number of water molecules in the calculation to obtain converged results. The predicted adiabatic electron affinity and electron transfer rate obtained from our QM/MM calculations are consistent with the available experimental results.

Configuration interaction trained by neural networks: Application to model polyaromatic hydrocarbons.

The main bottleneck of a stochastic or deterministic configuration interaction method is determining the relative weights or importance of each determinant or configuration, which requires large scale matrix diagonalization. Therefore, these methods can be improved significantly from a computational standpoint if the relative importance of each configuration in the ground and excited states of molecular/model systems can be learned using machine learning techniques such as artificial neural networks (ANNs). We have used neural networks to train the configuration interaction coefficients obtained from full configuration interaction and Monte Carlo configuration interaction methods and have tested different input descriptors and outputs to find the more efficient training techniques. These ANNs have been used to calculate the ground states of one- and two-dimensional Heisenberg spin chains along with Heisenberg ladder systems, which are good approximations of polyaromatic hydrocarbons. We find excellent efficiency of training and the model this trained was used to calculate the variational ground state energies of the systems.

Effect of Dimerization on the Nonradiative Processes of Eumelanin Monomer.

Eumelanin is a polymeric structure made of dihydroxyindole (DHI) as the basic motif. Since the oxidative polymerization of DHI forms the core of eumelanin, understanding the effect of polymerization on its optical and photoprotective properties is crucial to elucidate the structure-function relationship of eumelanin. In this work, we investigate the effect of dimerization of DHI on the photoprocesses of eumelanin. We observe that there are several low-energy conical intersections and energetically favorable pathways for deactivation of photoexcited dimeric DHI species. While the original deactivation modes of the monomers are still important, in dimers the intermonomer dihedral angles seem to play a central role.

Data-driven modeling of S0 → S1 excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design.

Derivatives of BODIPY are popular fluorophores due to their synthetic feasibility, structural rigidity, high quantum yield, and tunable spectroscopic properties. While the characteristic absorption maximum of BODIPY is at 2.5 eV, combinations of functional groups and substitution sites can shift the peak position by ±1 eV. Time-dependent long-range corrected hybrid density functional methods can model the lowest excitation energies offering a semi-quantitative precision of ±0.3 eV. Alas, the chemical space of BODIPYs stemming from combinatorial introduction of-even a few dozen-substituents is too large for brute-force high-throughput modeling. To navigate this vast space, we select 77 412 molecules and train a kernel-based quantum machine learning model providing <2% hold-out error. Further reuse of the results presented here to navigate the entire BODIPY universe comprising over 253 giga (253 × 109) molecules is demonstrated by inverse-designing candidates with desired target excitation energies.

Comprehending the quadruple bonding conundrum in C2 from excited state potential energy curves.

The question of quadruple bonding in C2 has emerged as a hot button issue, with opinions sharply divided between the practitioners of Valence Bond (VB) and Molecular Orbital (MO) theory. Here, we have systematically studied the Potential Energy Curves (PECs) of low lying high spin sigma states of C2, N2, Be2 and HC[triple bond, length as m-dash]CH using several MO based techniques such as CASSCF, RASSCF and MRCI. The analyses of the PECs for the 2S+1Σg/u (with 2S + 1 = 1, 3, 5, 7, 9) states of C2 and comparisons with those of relevant dimers and the respective wavefunctions were conducted. We contend that unlike in the case of N2 and HC[triple bond, length as m-dash]CH, the presence of a deep minimum in the 7Σ+ state of C2 and CN+ suggests a latent quadruple bonding nature in these two dimers. Our investigations reveal that the number of bonds in the ground state can be determined for 2nd row dimers by figuring out at what value of spin symmetry a purely dissociative PEC is obtained. For N2 and HC[triple bond, length as m-dash]CH the purely dissociative PEC appears for the septet spin symmetry as compared to that for the nonet in C2. This is indicative of a higher number of bonds between the two 2nd row atoms in C2 as compared to those of N2 and HC[triple bond, length as m-dash]CH. Hence, we have struck a reconciliatory note between the MO and VB approaches. The evidence provided by us can be experimentally verified, thus providing the window so that the narrative can move beyond theoretical conjectures.

Charge transfer in DHICA eumelanin-like oligomers: role of hydrogen bonds.

Eumelanin is a versatile bio-polymer with a heterogeneous structure and atypical functionalities. The constituent parts of eumelanin can be used to engineer systems with spectacular properties. We will describe some design principles to accentuate the charge transfer properties in eumelanin, especially those containing dihydroxyindole carboxylic acid (DHICA). We will show that the oligomers of DHICA can form isomers (atropisomers) of almost equivalent stability and the difference in charge transfer properties between these isomers is strongly dependent on the presence of inter-monomer hydrogen bonds.

Erratum: Majumder, S. et al. Zinc Oxide Nanoparticles Functionalized on Hydrogel Grafted Silk Fibroin Fabrics as Efficient Composite Dressing. Biomolecules 2020, 10, 710.

The authors wish to make the following correction to this paper [...].