Deep-eutectic solvent-assisted green synthesis of MAX-phase Cr2AlC and its 2D-MXene derivative Cr2CTxtowards room-temperature detection of ammonia gas

Abstract

This study explores the novel and eco-friendly chemical etching of bulk Cr<inf>2</inf>AlC MAX phases using a deep eutectic solvent (DES) mixture of choline chloride (ChCl) and anhydrous ferric chloride (FeCl<inf>3</inf>) to synthesize chromium carbide (Cr<inf>2</inf>CT<inf>x</inf>) MXene nanolayers. ChCl-FeCl<inf>3</inf>enables a fluoride-free transformation approach to synthesize Cr<inf>2</inf>CT<inf>x</inf>MXene via selective etching of aluminium interlayers, resulting in mixed surface terminations (-O, -OH, -Cl) confirmed from bond vibrations observed in FTIR transmittance spectra. Also, the FESEM micrographs confirm the formation of Cr<inf>2</inf>CT<inf>x</inf>nanolayers with successful cleavage of Cr<inf>2</inf>AlC MAX phase nanolaminates identified from a distinct red shift of D-band with the highest I<inf>D</inf>/I<inf>G</inf>ratio peak intensity ratio, confirming the presence of high defect concentration in Cr<inf>2</inf>CT<inf>x</inf>MXene. The hydrothermally synthesized SnO<inf>2</inf>powders exhibiting a rutile tetragonal phase average particle size of 35.8 ± 0.8 nm were mixed with Cr<inf>2</inf>CT<inf>x</inf>to formulate screen-printable inks for the fabrication of Cr<inf>2</inf>CT<inf>x</inf>, SnO<inf>2</inf>, and their composite Cr<inf>2</inf>CT<inf>x</inf>-SnO<inf>2</inf>gas sensors. The addition of Cr<inf>2</inf>CT<inf>x</inf>demonstrated a detrimental effect on the gas-sensing performance of the SnO<inf>2</inf>sensor, which was further supported from XPS analysis. However, the SnO<inf>2</inf>sensor recorded the highest gas-response of ?452 towards 100 ppm of ammonia gas among all sensors, highlighting the role of oxygen defects confirmed from photoluminescence spectra. This work paves the way for a novel and eco-friendly etching approach of MAX-phases and helps in their research towards the development of ultra-sensitive gas sensors. © 2025 Elsevier Ltd and Techna Group S.r.l. All rights are reserved, including those for text and data mining, AI training, and similar technologies.