Non-fullerene acceptors (NFAs) are excellent light harvesters, yet the origin of their high optical extinction is not well understood. In this work, we investigate the absorption strength of NFAs by building a database of time-dependent density functional theory (TDDFT) calculations of ∼500 π-conjugated molecules. The calculations are first validated by comparison with experimental measurements in solution and solid state using common fullerene and non-fullerene acceptors. We find that the molar extinction coefficient (ε_d,max) shows reasonable agreement between calculation in vacuum and experiment for molecules in solution, highlighting the effectiveness of TDDFT for predicting optical properties of organic π-conjugated molecules. We then perform a statistical analysis based on molecular descriptors to identify which features are important in defining the absorption strength. This allows us to identify structural features that are correlated with high absorption strength in NFAs and could be used to guide molecular design: highly absorbing NFAs should possess a planar, linear, and fully conjugated molecular backbone with highly polarisable heteroatoms. We then exploit a random decision forest algorithm to draw predictions for ε_d,max using a computational framework based on extended tight-binding Hamiltonians, which shows reasonable predicting accuracy with lower computational cost than TDDFT. This work provides a general understanding of the relationship between molecular structure and absorption strength in π-conjugated organic molecules, including NFAs, while introducing predictive machine-learning models of low computational cost.

Liquid metal catalysts have recently attracted attention for synthesizing high‐quality 2D materials facilitated via the catalysts’ perfectly smooth surface. However, the microscopic catalytic processes occurring at the surface are still largely unclear because liquid metals escape the accessibility of traditional experimental and computational surface science approaches. Hence, numerous controversies are found regarding different applications, with graphene (Gr) growth on liquid copper (Cu) as a prominent prototype. In this work, novel in situ and in silico techniques are employed to achieve an atomic‐level characterization of the graphene adsorption height above liquid Cu, reaching quantitative agreement within 0.1 Å between experiment and theory. The results are obtained via in situ synchrotron X‐ray reflectivity (XRR) measurements over wide‐range q‐vectors and large‐scale molecular dynamics simulations based on efficient machine‐learning (ML) potentials trained to first‐principles density functional theory (DFT) data. The computational insight is demonstrated to be robust against inherent DFT errors and reveals the nature of graphene binding to be highly comparable at liquid Cu and solid Cu(111). Transporting the predictive first‐principles quality via ML potentials to the scales required for liquid metal catalysis thus provides a powerful approach to reach microscopic understanding, analogous to the established computational approaches for catalysis at solid surfaces.

We investigate blended donor:acceptor (D:A) thin films of the two donors diindenoperylene (DIP) and poly(3-hexylthiophene) (P3HT) mixed with the strong acceptor 1,3,4,5,7,8-hexafluorotetracyanonaphthoquinodimethane (F₆TCNNQ) using Polarization-Modulation Infrared Reflection-Absorption Spectroscopy (PMIRRAS). For DIP:F₆TCNNQ thin films we first carry out a comprehensive study of the structure as a function of the D : A mixing ratio, which guides the analysis of the PMIRRAS spectra. In particular, from the red-shift of the nitrile (CN) stretching of F₆TCNNQ in the different mixtures with DIP, we quantify the average ground-state charge-transfer (GS-CT) to be ρ_avg = (0.84 ± 0.04) e. The PMIRRAS data for P3HT:F₆TCNNQ blended films reveal nearly the same shift of the CT-affected CN stretching peak for this system. This points towards a very similar CT strength for the two systems. We extend the analysis to the relative intensity of the CN to the CC stretching modes of F₆TCNNQ in the mixtures with DIP and P3HT, respectively, and support it with DFT calculations for the isolated F₆TCNNQ. Such comparison allows to identify the vibrational signatures of the acceptor mono-anion in P3HT:F₆TCNNQ, thus indicating a much stronger, integer CT-type interactions for this system, in agreement with available optical spectroscopy data. Our findings stress the importance of a simultaneous analysis of CN and CC stretching vibrations in F₆TCNNQ, or similar quinoid systems, for a reliable picture of the nature of GS-CT interactions.