Fluorescent boron and phosphorus Co-doped graphene quantum dots for bovine serum albumin sensing in cow's milk with smartphone-enabled real-time readout.

Accurate and rapid detection of milk proteins is important for ensuring dairy quality and assessing nutritional value. However, many conventional analytical techniques involve high operational costs, complicated sample pretreatment, and insufficient sensitivity, especially when applied to complex milk matrices. Among milk proteins, bovine serum albumin (BSA) is widely regarded as a key quality indicator, as its concentration can reflect the physiological condition of dairy animals and may also signal adulteration in milk products. In the present study, we developed a sensitive fluorescence-based nanosensor using boron- and phosphorus-co-doped graphene quantum dots (BP-GQDs) for the quantitative detection of BSA directly in milk samples. The BP-GQDs were synthesized through a simple hydrothermal method, producing uniformly distributed nanodots with strong blue fluorescence emission. Their structural, morphological, and optical properties were systematically examined using UV-vis spectroscopy, high-resolution transmission electron microscopy (HR-TEM), powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), energy-dispersive X-ray spectroscopy (EDS), steady-state fluorescence spectroscopy, and time-correlated single-photon counting (TCSPC). Co-doping with boron and phosphorus led to a noticeable enhancement in fluorescence efficiency and quantum yield while maintaining good biocompatibility. The sensing performance was governed by a photoinduced electron transfer (PET) - based fluorescence quenching mechanism arising from the interaction between BP-GQDs and BSA, resulting in high selectivity and excellent sensitivity, with a detection limit of 7.861 nM. Also, integration of this sensor with a smartphone-assisted platform enabled rapid, on-site quantification of BSA in milk, demonstrating its potential for field-level dairy quality monitoring and improved protein analysis compared with conventional colorimetric and immunological methods.