In this paper, researchers explore the modulation of metal nanoclusters’ optical properties through inter-cluster conversion using external stimuli. They prepare blue-emitting copper nanoclusters (CuNCs) using phenylalanine (Phe) as a template under acidic conditions. The CuNCs exhibit sequential tuning of photophysical properties as pH changes from ~4 to ~12. Blue-emitting CuNCs shift to cyan-emitting CuNCs with a large 80 nm redshift in emission maximum. The study also highlights the pH-induced intercluster conversion by analyzing core composition and oxidation states. Additionally, the CuNCs show potential applications: efficient CO2 probing and peroxidase-mimicking enzymatic activity.
- 💡 Researchers prepared blue-emitting CuNCs using phenylalanine template.
- 🔄 pH variation (pH ~4 to pH ~12) shifts emission from blue to cyan.
- 🔬 XPS studies confirm core composition change and oxidation state variation.
- 🌍 CuNCs act as a sensitive probe for CO2 with low detection limit.
- ⚗️ CuNCs exhibit peroxidase-mimicking enzymatic activity.
- 🧪 Mechanistic investigation reveals hydroxyl radical generation.
- 🌟 Study sheds light on pH-switchable properties of CuNCs and their applications.
The researchers’ work demonstrates the tunable optical properties of copper nanoclusters through pH variations and their potential for CO2 sensing and enzyme-like activities. The findings contribute to the growing interest in using metal nanoclusters for diverse applications.
- 📝 The study focuses on preparing copper nanoclusters (CuNCs) using phenylalanine as a template under acidic conditions. These CuNCs exhibit interesting pH-dependent optical properties, shifting their emission from blue to cyan as the pH increases. The core composition and oxidation states of the CuNCs were found to change with pH, demonstrating their pH-induced intercluster conversion. The unique properties of these CuNCs make them suitable for various applications.
- 📝 In the context of environmental sensing, the CuNCs were shown to be effective probes for detecting dissolved CO2, with a remarkably low limit of detection. Additionally, the CuNCs demonstrated peroxidase-like activity under physiological conditions, involving the generation of hydroxyl radicals. This enzymatic activity could have significant implications in various biochemical processes.
- 📝 The findings of this study shed light on the multifunctional potential of copper nanoclusters and their applications in both sensing and catalytic activities. The pH-dependent switchability of their optical properties and the ability to act as both CO2 sensors and peroxidase mimics make them promising candidates for further exploration in various fields.
- 🌌 Copper nanoclusters (CuNCs) with blue emission are prepared using phenylalanine (Phe) as a template at pH ~4.
- 🌈 The CuNCs exhibit sequential tuning of optical properties from blue to cyan emission as pH increases to ~12.
- 🔬 Characterization reveals changes in core composition and oxidation states due to pH-induced intercluster conversion.
- 🔄 CuNCs show pH-sensitive behavior and act as a sensitive probe for detecting CO2 and as an artificial enzyme.
- 🧪 Blue-emitting CuNCs transform into cyan-emitting CuNCs with increasing pH.
- 💡 CuNCs can act as a sensitive probe for detecting dissolved CO2.
- ⚛️ X-ray photoelectron spectroscopy (XPS) reveals different oxidation states in CuNCs.
- 🦠 CuNCs exhibit peroxidase mimicking enzymatic activity.
- 🌌 The study focuses on creating copper nanoclusters with tunable emission properties by adjusting pH.
- 🧪 Phenylalanine is used as a template to prepare CuNCs with blue emission, which can be switched to cyan emission by changing pH.
- 🔬 Characterization techniques like XPS confirm the pH-induced changes in core composition and oxidation states of CuNCs.
- 🔄 The pH sensitivity of CuNCs makes them suitable for detecting dissolved CO2 and catalyzing reactions like a peroxidase enzyme.
- Saptarshi Mukherjee, Shashi Shekhar, Raibat Sarker, Paritosh Mahato and Sameeksha Agrawal
- Copper nanoclusters
- pH-dependent emission
- CO2 sensing
- Peroxidase mimicking
- Multifunctional nanomaterials
