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Semiconducting conjugated polymers (CPs) are pivotal in advancing organic electronics, offering tunable properties for solar cells and field-effect transistors. Here, we carry out first-principle calculations to study individual cis-polyacetylene (cis-PA) oligomers and their ensembles. The ground electronic structures are obtained using density functional theory (DFT), and excited state dynamics are explored by computing nonadiabatic couplings (NACs) between electronic and nuclear degrees of freedom. We compute the nonradiative relaxation of charge carriers and photoluminescence (PL) using the Redfield theory. Our findings show that electrons relax faster than holes. The ensemble of oligomers shows faster relaxation compared to the single oligomer. The calculated PL spectra show features from both interband and intraband transitions. The ensemble shows broader line widths, redshift of transition energies, and lower intensities compared to the single oligomer. This comparative study suggests that the dispersion forces and orbital hybridizations between chains are the leading contributors to the variation in PL. It provides insights into the fundamental behaviors of CPs and the molecular-level understanding for the design of more efficient optoelectronic devices. 

Inorganic mixed-halogen perovskites exhibit excellent photovoltaic properties and stability; yet, their photoelectric conversion efficiency is limited by inherent surface defects. In this work, we study the impact of defects on properties of CsPbI2Br slabs using first-principles calculations, focusing on specific defects such as I vacancy (VI), I interposition (Ii), and I substitution by Pb (PbI). Our findings reveal that these defects affect the geometric and optoelectronic properties as well as dynamics of charge carriers of slabs. We employ two theoretical frameworks (surface hopping and Redfield theory) of nonadiabatic molecular dynamics simulations to comprehensively study relaxation processes and obtain consistent results. The presence of VI reduces carrier lifetimes, while the influence of PbI on carrier lifetimes is negligible. In contrast, Ii defects lead to prolonged carrier lifetimes. These insights provide valuable guidance for the rational design of perovskite photovoltaic devices, aiming to enhance their efficiency and stability. 

The development of reusable polymeric materials inspires an attempt to combine renewable biomass with upcycling to form a biorenewable closed system. It has been reported that 2,5-furandicarboxylic acid (FDCA) can be recovered for recycling when incorporated as monomers into photodegradable polymeric systems. Here, we develop a procedure to better understand the photodegradation reactions combining density functional theory (DFT) based time-dependent excited-state molecular dynamics (TDESMD) studies with machine learning-based quantitative structure–activity relationships (QSAR) methodology. This procedure allows for the unveiling of hidden structural features between active orbitals that affect the rate of photodegradation and is coined InfoTDESMD. Findings show that electrotopological features are influential factors affecting the rate of photodegradation in differing environments. Additionally, statistical validations and knowledge-based analysis of descriptors are conducted to further understand the structural features’ influence on the rate of photodegradation of polymeric materials. 

An exploration of the “on-the-fly” nonadiabatic couplings (NACs) for nonradiative relaxation and recombination of excited states in 2D Dion–Jacobson (DJ) lead halide perovskites (LHPs) is accelerated by a machine learning approach. Specifically, ab initio molecular dynamics (AIMD) of nanostructures composed of heavy elements is performed with the use of machine-learning force-fields (MLFFs), as implemented in the Vienna Ab initio Simulation Package (VASP). The force field parametrization is established using on-the-fly learning, which continuously builds a force field using AIMD data. At each time step of the molecular dynamics (MD) simulation, the total energy and forces are predicted based on the MLFF and if the Bayesian error estimate exceeds a threshold, an ab initio calculation is performed, which is used to construct a new force field. Model training of MLFF and evaluation were performed for a range of DJ-LHP models of different thicknesses and halide compositions. The MLFF-MD trajectories were evaluated against pure AIMD trajectories to assess the level of discrepancy and error accumulation. To examine the practical effectiveness of this approach, we have used the MLFF-based MD trajectories to compute NAC and excited-state dynamics. At each stage, results based on machine learning are compared to traditional ab initio based electronic dissipative dynamics. We find that MLFF-MD provides comparable results to AIMDs when MLFF is trained in an NPT ensemble. 

Two-dimensional organic–inorganic hybrid lead halide perovskites are of interest for photovoltaic and light emitting devices due to their favorable properties that can be tuned. Here we use density functional theory to model two-dimensional lead halide perovskites of different thicknesses and using two different hallogens. Excited-state optoelectronic properties of the perovskite models are examined using excited-state dynamics treated by reduced density matrix method. Nonadiabatic couplings were computed based on the on-the-fly approach along a molecular dynamics trajectory at ambient temperatures. The density matrix-based equation of motion for electronic degrees of freedom was used to determine the dynamics of electronic degrees of freedom. We observe that the thickness of the perovskite layer shows a redshift in the absorption spectra with increasing thickness but has minimal effect on the photoluminescence quantum yield of the material. 

Lead halide perovskites (LHP) are of interest for light-emitting applications due to the tunability of their bandgap across the visible and near-infrared spectrum (IR) coupled with efficient photoluminescence quantum yields (PLQY). It is widely speculated that photoexcited electrons and holes spatially separate into large negative (electron) and positive (hole) polarons. Polarons are expected to be optically active. With the observed optoelectronic signatures expecting to show potential excited states within the polaronic potential well. From the polaron excited-state we predict that large polarons should be capable of spontaneous emission, photoluminescence, in the mid-IR to far-IR regime based on the concept of inverse occupations within the polaron potential well. Here we use density functional theory (DFT), including spin–orbit coupling interactions, for calculations on a two-dimensional Dion-Jacobson (DJ) lead chloride perovskite atomistic model of various sizes as a host material for either negative or positive polarons to examine the effects of size on polaron formation. This work provides computational evidence that polaron formation through selective charge injection does not show the same level of localisation for positive and negative polarons. 

Heterostructure quantum dots (QDs) are composed of two QD nanocrystals (NCs) conjoined at an interface. They are useful in applications such as photovoltaic solar cells. The properties of the interface between the NCs determine the efficiency of electron–hole recombination rates and charge transfer. Therefore, a fundamental understanding of how this interface works between the two materials is useful. To contribute to this understanding, we simulated two isolated heterostructure QD models with Janus-like geometry composed of Cd33Se33 + Pb68Se68 NCs. The first Janus-like model has a bond connection between the two NCs and is approximately 16 × 17 × 29 Å3 in size. The second model has a through-space connection between the NCs and is approximately 16 × 17 × 31 Å3. We use density functional theory to simulate the ground state properties of these models. Nonadiabatic on-the-fly couplings calculations were then used to construct the Redfield Tensor, which described the excited state dynamics due to nonradiative relaxation. From our results, we identified a qualitative trend which shows that having a bond connecting the two NCs reduces hole relaxation time. We also identified for a sample of electron–hole excitations pairs that the through-bond model allows for a net positive or negative numerical net charge transfer, depending on the excitation pair. 

Metal clusters with 10 to 100 atoms supported by a solid surface show electronic structure typical of molecules and require ab initio treatments starting from their atomic structure, and they also can display collective electronic phenomena similar to plasmons in metal solids. We have employed ab initio electronic structure results from two different density functionals (PBE and the hybrid HSE06) and a reduced density matrix treatment of the dissipative photodynamics to calculate light absorbance by the large Ag clusters Ag N , N = 33, 37(open shell) and N = 32, 34 (closed shell), adsorbed at the Si(111) surface of a slab, and forming nanostructured surfaces. Results on light absorption are quite different for the two functionals, and are presented here for light absorbances using orbitals and energies from the hybrid functional giving correct energy band gaps. Absorption of Ag clusters on Si increases light absorbance versus photon energy by large percentages, with peak increases found in regions of photon energies corresponding to localized plasmons. The present metal clusters are large enough to allow for modelling with continuum dielectric treatments of their medium. A mesoscopic Drude–Lorentz model is presented in a version suitable for the present structures, and provides an interpretation of our results. The calculated range of plasmon energies overlaps with the range of solar photon energies, making the present structures and properties relevant to applications to solar photoabsorption and photocatalysis.