Paolo Pio Mazzeo

The coordination co-crystal (4-bromo-2-{[(2-hydroxyethyl)imino]methyl}phenololato-κ ³ O , N , O ′)(thiocyanato-κ N )copper(II)–5-bromo-2-hydroxybenzaldehyde–water (2/1/1), [Cu(C ₉ H ₉ BrNO ₂ )(NCS)]·0.5C ₇ H ₅ BrO ₂ ·0.5H ₂ O or [Cu(H L )(SCN)] ₂ ·C ₇ H ₅ BrO ₂ ·H ₂ O, crystallizes in the monoclinic space group P 2 ₁ / c . The asymmetric unit contains two mononuclear units of the complex, each consisting of one deprotonated ligand, one thiocyanate anion (SCN ⁻ ) coordinated through its nitrogen atom, one free water molecule, and one free 5-bromosalicylaldehyde molecule, forming a co-crystal. The copper atom is four-coordinate, adopting a slightly distorted square-planar geometry defined by the tridentate ligand and the nitrogen atom of the thiocyanate anion. Bond length values show that the thiocyanate ion has a linear S—C[triple-bond]N arrangement, typical of a terminal, N-bound isothiocyanate group. The water molecule plays a key role in linking the two complex units through O—H...O hydrogen bonds. In the crystal, C—H...O and C—H...Br hydrogen bonds allow the free 5-bromosalicylaldehyde molecule to form a bridge between two adjacent layers. Additional O—H...O, C—H...S, O—H...S, and C—H...N interactions further consolidate the overall structure.

Carbazoles are valuable building blocks for emerging pharmaceuticals and bioactive compounds. However, methods to access C1–H-aminated carbazoles remain underdeveloped. Current approaches often require multistep syntheses or the use of toxic metals. Herein, we report the first Pd/NBE-catalyzed C1–H amination of NH-free carbazoles. The method introduces a broad range of cyclic amines onto carbazole scaffold and tolerates several functional groups, including acyl, pivaloyl, and halogen substituents. This approach expands the scope of the Catellani reactions to the direct amination of unprotected carbazoles, offering a concise entry to otherwise challenging C1-aminated scaffolds.

A combined 3DED, plane-wave DFT, and Rietveld refinement workflow uncovers the first example of interlayer-twisting polymorphism in a pillared MOF. While the parent material, PUM198, a Zn-based mixed-ligand MOF, was previously synthesized under solvothermal conditions, mechanochemistry selectively affords a new polymorph, PUM198-m. Although the two phases share identical composition and connectivity, they differ in symmetry, layer arrangement, pore architecture, and topology. Accessible only as a microcrystalline powder, PUM198-m is unsuitable for conventional single-crystal X-ray diffraction, and its flexibility and solvent-filled pores preclude structure solution from the XRPD data. The crystal structure was therefore derived from a multitechnique blueprint in which the starting model was derived from 3DED data and subsequently refined through iterative DFT-assisted Rietveld analysis to describe the as-synthesized, guest-loaded material. This integrated workflow provides a broadly applicable structural elucidation strategy for flexible MOFs that are mechanochemically synthesized, for which conventional crystallographic analysis fails.

The Johnson-Corey-Chaykovsky reaction stands as an elegant approach for the synthesis of cyclopropanes and epoxides. However, most procedures still rely on the original NaH/DMSO conditions, which pose notable safety and handling issues especially in view of industrial applications. Herein, we combine Bayesian Optimization and mechanochemistry to develop a rapid, solvent-free protocol for the Johnson-Corey-Chaykovsky reaction. By prioritizing efficiency and sustainability, Machine Learning quickly identified a new set of reaction conditions for this transformation, also demonstrating that these transformations can proceed efficiently under air-equilibrated, mild conditions using an inexpensive and safe base (KOH). The method is broadly applicable, scalable, and tolerant to diverse functional groups and enabled the preparation of a wide variety of three-membered homo- and heterocycles. Time-Resolved in situ X-ray Powder Diffraction experiments highlighted the crucial role of active milling in promoting this transformation. Overall, this work establishes a foundation for the integration of Machine Learning and mechanochemistry in designing industrially relevant transformations that prioritize safety and sustainability.

Efficient and selective mechanochemical syntheses, post-synthetic modifications and dimensional-growth of 1D-coordination polymers under milling conditions are shown.

Herein, we combine Bayesian Optimization and mechanochemistry to develop a rapid, solvent-free protocol for the Johnson–Corey–Chaykovsky (JCC) cyclopropanation and epoxidation. By prioritizing efficiency and sustainability, Machine Learning quickly identified a new set of reaction conditions for this venerable reaction that diverge from established paradigms (explosive NaH/DMSO system), revealing that these transformations can proceed efficiently under air-equilibrated, mild conditions using an inexpensive and safe base (KOH). The method is broadly applicable, scalable, and tolerant to diverse functional groups and enabled the preparation of a wide variety of three-membered homo- and heterocycles. Overall, this work pioneers the synergy between Machine Learning and mechanochemistry to design industrially relevant transformations that prioritize safety and sustainability.

An original oxidative functionalization of 8-aminoquinolines in the presence of an organic peroxide under batch conditions has been recently reported.

Correction for ‘Collapse or capture? Guest-induced response of two structurally distinct pillared-MOFs upon exposure to pyridines and quinolines’ by Dario Giovanardi et al. , Dalton Trans. , 2025, 54 , 13540–13548, https://doi.org/10.1039/d5dt01321f.