Singlet fission (SF) is a photophysical process considered as a possible scheme to bypass the Shockley–Queisser limit by generating two triplet-state excitons from one high-energy photon. Polyacene crystals, such as tetracene and pentacene, have shown outstanding SF performance both theoretically and experimentally. However, their instability prevents them from being utilized in SF-based photovoltaic devices. In search of practical SF chromophores, we use many-body perturbation theory within the GW approximation and Bethe–Salpeter equation to study the excitonic properties of a family of pyrene-stabilized acenes. We propose a criterion to define the convergence of exciton wave-functions with respect to the fine k-point grid used in the BerkeleyGW code. An open-source Python code is presented to perform exciton wave-function convergence checks and streamline the double Bader analysis of exciton character. We find that the singlet excitons in pyrene-stabilized acenes have a higher degree of charge transfer character than in the corresponding acenes. The pyrene-fused tetracene and pentacene derivatives exhibit comparable excitation energies to their corresponding acenes, making them potential SF candidates. The pyrene-stabilized anthracene derivative is considered as a possible candidate for triplet–triplet annihilation because it yields a lower SF driving force than anthracene.
Finding predictive models for singlet fission by machine learning
Singlet fission (SF), the conversion of one singlet exciton into two triplet excitons, could significantly enhance solar cell efficiency. Molecular crystals that undergo SF are scarce. Computational exploration may accelerate the discovery of SF materials. However, many-body perturbation theory (MBPT) calculations of the excitonic properties of molecular crystals are impractical for large-scale materials screening. We use the sure-independence-screening-and-sparsifying-operator (SISSO) machine-learning algorithm to generate computationally efficient models that can predict the MBPT thermodynamic driving force for SF for a dataset of 101 polycyclic aromatic hydrocarbons (PAH101). SISSO generates models by iteratively combining physical primary features. The best models are selected by linear regression with cross-validation. The SISSO models successfully predict the SF driving force with errors below 0.2 eV. Based on the cost, accuracy, and classification performance of SISSO models, we propose a hierarchical materials screening workflow. Three potential SF candidates are found in the PAH101 set.
- Award ID(s):
- 2021803
- Publication Date:
- NSF-PAR ID:
- 10381650
- Journal Name:
- npj Computational Materials
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2057-3960
- Publisher:
- Nature Publishing Group
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Hematin crystallization is an essential element of heme detoxification of malaria parasites and its inhibition by antimalarial drugs is a common treatment avenue. We demonstrate at biomimetic conditions in vitro irreversible inhibition of hematin crystal growth due to distinct cooperative mechanisms that activate at high crystallization driving forces. The evolution of crystal shape after limited-time exposure to both artemisinin metabolites and quinoline-class antimalarials indicates that crystal growth remains suppressed after the artemisinin metabolites and the drugs are purged from the solution. Treating malaria parasites with the same agents reveals that three- and six-hour inhibitor pulses inhibit parasite growth with efficacy comparable to that of inhibitor exposure during the entire parasite lifetime. Time-resolved in situ atomic force microscopy (AFM), complemented by light scattering, reveals two molecular-level mechanisms of inhibitor action that prevent β-hematin growth recovery. Hematin adducts of artemisinins incite copious nucleation of nonextendable nanocrystals, which incorporate into larger growing crystals, whereas pyronaridine, a quinoline-class drug, promotes step bunches, which evolve to engender abundant dislocations. Both incorporated crystals and dislocations are known to induce lattice strain, which persists and permanently impedes crystal growth. Nucleation, step bunching, and other cooperative behaviors can be amplified or curtailed as means to control crystalmore »
-
Abstract Self-assembly of molecular building blocks into higher-order structures is exploited in living systems to create functional complexity and represents a powerful strategy for constructing new materials. As nanoscale building blocks, proteins offer unique advantages, including monodispersity and atomically tunable interactions. Yet, control of protein self-assembly has been limited compared to inorganic or polymeric nanoparticles, which lack such attributes. Here, we report modular self-assembly of an engineered protein into four physicochemically distinct, precisely patterned 2D crystals via control of four classes of interactions spanning Ångström to several-nanometer length scales. We relate the resulting structures to the underlying free-energy landscape by combining in-situ atomic force microscopy observations of assembly with thermodynamic analyses of protein-protein and -surface interactions. Our results demonstrate rich phase behavior obtainable from a single, highly patchy protein when interactions acting over multiple length scales are exploited and predict unusual bulk-scale properties for protein-based materials that ensue from such control.
-
Abstract Triplet population dynamics of solution cast films of isolated polymorphs of 6,13‐bis(triisopropylsilylethynyl) pentacene (TIPS‐Pn) provide quantitative experimental evidence that triplet excitation energy transfer is the dominant mechanism for correlated triplet pair (CTP) separation during singlet fission. Variations in CTP separation rates are compared for polymorphs of TIPS‐Pn with their triplet diffusion characteristics that are controlled by their crystal structures. Since triplet energy transfer is a spin‐forbidden process requiring direct wavefunction overlap, simple calculations of electron and hole transfer integrals are used to predict how molecular packing arrangements would influence triplet transfer rates. The transfer integrals reveal how differences in the packing arrangements affect electronic interactions between pairs of TIPS‐Pn molecules, which are correlated with the relative rates of CTP separation in the polymorphs. These findings suggest that relatively simple computations in conjunction with measurements of molecular packing structures may be used as screening tools to predict a priori whether new types of singlet fission sensitizers have the potential to undergo fast separation of CTP states to form multiplied triplets.
-
Abstract Ising superconductivity, observed in NbSe2and similar materials, has generated tremendous interest. Recently, attention was called to the possible role that spin fluctuations (SF) play in this phenomenon, in addition to the dominant electron–phonon coupling (EPC); the possibility of a predominantly triplet state was discussed and led to a conjecture of viable singlet–triplet Leggett oscillations. However, these hypotheses have not been put to a quantitative test. In this paper, we report first principle calculations of the EPC and also estimate coupling with SF, including full momentum dependence. We find that: (1) EPC is strongly anisotropic, largely coming from the
$$K-{K}^{{\prime} }$$ s ++–s ±channel.
