Colloidal Synthesis of Ag2MnSnS4 Quantum Dots for Bioimaging Applications

Abstract

Ag₂MnSnS₄ (AMTS), a member of the multinary I₂–II–IV–VI₄ compound family, exhibits a high absorption coefficient and intrinsic magnetic properties. While bulk AMTS crystals were synthesized via high-temperature solid-state methods, reports of AMTS quantum dots (QDs) remained scarce. Here, we report the first colloidal synthesis of AMTS QDs by optimizing reaction temperature and precursor composition. AMTS QDs obtained at 250 °C were spherical or polygonal with an average size of 5.4 nm or less. Decreasing the Ag fraction in precursors produced Ag-deficient, Mn-rich QDs, exhibiting high tolerance to nonstoichiometry. Their absorption spectra were blue-shifted, and the energy gap increased from 1.95 to 2.36 eV with a decrease in the Ag⁺/metal cation ratio in the precursors from 0.50 to 0.05. Although no photoluminescence (PL) was observed at room temperature, a broad PL peak appeared at 77 K around 740–760 nm. ZnS coating on AMTS QDs enhanced the PL, giving a broad emission at 690 nm. The magnetic properties originated from unpaired 3d electrons of Mn²⁺. For bioimaging applications, ZnS-coated AMTS (AMTS@ZnS) QDs were further modified with 3-mercaptopropionic acid, enabling stable dispersion in water without compromising the optical and magnetic properties. The hydrophilic AMTS@ZnS QDs exhibited high longitudinal relaxivity (r₁), 19 mmol (Mn²⁺)⁻¹ dm³ s^–1, surpassing commercial Mn-based complexes (r₁ < 10 mmol^–1 dm³ s^–1). Although the T₁-weighted MRI intensity was similar at a fixed Mn²⁺ concentration, the QDs prepared with Ag/metal = 0.17 showed 1.7-fold higher relaxivity per QD than those with 0.44. In vivo MRI confirmed a clear signal enhancement at injection sites. The QDs internalized by cells were detectable by MRI in living animals. Given their negligible cytotoxicity compared to Cd-based QDs, AMTS QDs represent a promising next-generation MRI contrast agent, with additional potential for dual-mode bioimaging upon further PL optimization.