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Francesco Tavani

Publications and source records attributed to Francesco Tavani.

2 recordsLinked to original sources

Local Structure and Dynamics of Three-Dimensional Covalent Organic Frameworks

Resolving and controlling the local dynamical properties of covalent organic frameworks (COFs) remains a central challenge, particularly when assembled from large, flexible building units. Here, we combine synchrotron X-ray pair distribution function (PDF) analyses with machine learning-accelerated molecular dynamics (MD) simulations to resolve the local structure and dynamics of two three-dimensional imine-linked COFs, COF-682 {[(DHP)(TAM)]$_{imine}$}, assembled from 6,13-dihydropentacene (DHP) and tetrakis(4-aminophenyl)methane (TAM), and COF-612 {[(HBC-LA$_{12}$)(HAPT)$_2$]$_{imine}$}, assembled from nanographene dodecabenzaldehyde hexakis{[3,5-bis($p$-formylphenyl)-4,6-dimethoxyphenyl]}hexabenzocoronene (HBC-LA$_{12}$) and 2,3,6,7,14,15-hexa(4-aminophenyl)triptycene (HAPT). Validated against the experimental PDFs through ensemble-averaged calculations, the simulations show that the exposed $\pi$-surface and V-shaped geometry of the DHP linker endow COF-682 with enhanced local flexibility through face-to-face and offset $\pi$-stacking interactions differing in both their average interplanar separation and their ring-plane tilt angle. In contrast, the extended nanographene linker rigidifies COF-612 by maintaining the planarity of its fused cores, while the linker pendant aryl rings equip both COFs with enhanced librational ability. The simulations further provide quantitative measures of the translational and reorientational mobility of the linkers, revealing how local COF dynamics may be tuned by balancing non-covalent interactions and different degrees of aromatic rigidity. The PDF-MD experimental-computational approach holds promise as a general method beyond conventional crystallography to gain insights into the local properties of COFs with the aim of directing their dynamic function.

cond-mat.mtrl-sci

Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion

Materials with negative thermal expansion (NTE) are essential for applications requiring precise control of thermal expansion. Owing to their exceptional chemical tunability, flexible architectures, and low-energy lattice vibrations, metal-organic frameworks (MOFs) represent a rich platform for exploring NTE. However, uncovering the structural motifs that govern NTE across the enormous MOF design space remains experimentally challenging, and large-scale first-principles phonon calculations are computationally prohibitive. Here, we comprehensively evaluate the factors influencing NTE in MOFs by utilizing a high-throughput workflow based on MACE-MP-MOF0, a machine learning interatomic potential fine-tuned for MOFs with near-ab initio accuracy, to construct PhononMOFdb, a database of phonons, inelastic neutron scattering spectra, bulk moduli, and heat capacities for over 12,000 MOFs. High-throughput screening of this database reveals that highly porous cubic topology frameworks with heavier, lower-valent metal nodes favor strong NTE, while linker functionalization provides a practical handle for tuning NTE magnitude and sign without compromising mechanical stability. Experimental validation via high-resolution temperature-dependent synchrotron powder X-ray diffraction on the Ce-UiO-66 MOF and its brominated variants confirms the design recipe and yields volumetric NTE coefficients surpassing current records. This work establishes a data-driven strategy for engineering NTE in MOFs, showing how machine learning-accelerated discovery and targeted experimental validation together unlock predictive materials design.

cond-mat.mtrl-sci