Understanding crystal surface anisotropy of organic materials via molecular modelling and facet-specific experimental characterization

• Particle Informatics predicts facet-specific surface properties. • OPTIR and s-SNIM validate predictions on single-crystal facets. • Nanomechanical mapping reveals strong anisotropy in Young modulus. • Integrated workflow enables design of crystals with tailored surfaces. The different facets of crystalline particles expose specific functional groups depending on their structure and morphology, thus, influencing surface properties of the resulting materials. As particle surface properties impact product performance, safety, and manufacturing efficiency, it is important to understand how crystal structure influences facet-specific surface properties. In this work, we focused on the effect of crystal structure and morphology on properties such as roughness, mechanical strength, and chemical features. Quercetin-dimethylformamide (QDMF), a solvated form of quercetin, was selected as a single-crystal model compound. By combining computational approaches with experimental validation, we developed a standardized procedure to correlate crystal structure packing and specific surface features. Experimental data collected using various techniques were then used to validate the simulations. First, we utilized Particle Informatics tools to analyse the surface chemistry and topology of specific QDMF crystal facets observed experimentally, namely {1–10}, {001}, and {200}. These computational results were then validated using Atomic Force Microscopy (AFM) integrated with Infrared (IR) spectroscopy, which provided topographical insights, chemical characterization, surface roughness measurements, and mechanical properties characterization (e.g., Young Modulus). For chemical imaging at high spatial resolution, we employed advanced mid-infrared techniques, such as Optical Photothermal Infrared (OPTIR) microscopy and scattering-type Scanning Near-field Infrared Microscopy (s-SNIM). The experimental data were in agreement with the simulations, showing how Particle Informatics tools can assist in the design of crystalline materials with tailored surface properties.