Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene-Derived Metal–Organic Frameworks for Room Temperature NO<sub>2</sub> Detection

This work reports a new method toward creating two-dimensional (2D) conductive metal-organic frameworks (MOFs) for enhanced gas sensing applications. By employing Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene as a metal precursor and 2-aminoterapthalic acid as an organic linker, MXene-derived MOFs with high surface reactivity were synthesized. The Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene sensor, initially selective toward NH<sub>3</sub> gas, was tailored to detect NO<sub>2</sub> gas by integrating it with MXene-derived MOFs, which offer abundant active sites on the surface. The resulting MOF sensor exhibited a notable sensing response of 76.52%, with rapid response and recovery times of 31.5 and 80.2 s, respectively, at room temperature and 35% relative humidity (RH). The sensor's specificity toward acidic NO<sub>2</sub> gas was attributed to the acid-base interaction facilitated by the organic linker, inducing detectable changes in resistance. Additionally, the fabricated MOF sensor demonstrated excellent repeatability and stability under ambient conditions. Remarkably, the sensor exhibited a low detection limit (LOD) of 5 ppb for NO<sub>2</sub> gas. These findings underscore the potential of utilizing 2D MOF sheets derived from MXene precursors for practical gas sensing applications, highlighting their versatility and effectiveness.

Authors

Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-05-15
DOI
https://doi.org/10.1021/acsami.5c05667
Citations
9
Primary Topic
MXene and MAX Phase Materials
Type
article
Field-Weighted Citation Impact
4.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ti3C2Tx MXene-Derived Metal–Organic Frameworks for Room Temperature NO2 Detection

Naveen Kumar Arkoti, Kaushik Pal
9 citations
ACS Applied Materials & Interfaces
MXene and MAX Phase Materials
4.66
article

Ti3C2Tx MXene-Derived Metal–Organic Frameworks for Room Temperature NO2 Detection

Naveen Kumar Arkoti, Kaushik Pal
article en
9 citations

Abstract

This work reports a new method toward creating two-dimensional (2D) conductive metal-organic frameworks (MOFs) for enhanced gas sensing applications. By employing Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene as a metal precursor and 2-aminoterapthalic acid as an organic linker, MXene-derived MOFs with high surface reactivity were synthesized. The Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene sensor, initially selective toward NH<sub>3</sub> gas, was tailored to detect NO<sub>2</sub> gas by integrating it with MXene-derived MOFs, which offer abundant active sites on the surface. The resulting MOF sensor exhibited a notable sensing response of 76.52%, with rapid response and recovery times of 31.5 and 80.2 s, respectively, at room temperature and 35% relative humidity (RH). The sensor's specificity toward acidic NO<sub>2</sub> gas was attributed to the acid-base interaction facilitated by the organic linker, inducing detectable changes in resistance. Additionally, the fabricated MOF sensor demonstrated excellent repeatability and stability under ambient conditions. Remarkably, the sensor exhibited a low detection limit (LOD) of 5 ppb for NO<sub>2</sub> gas. These findings underscore the potential of utilizing 2D MOF sheets derived from MXene precursors for practical gas sensing applications, highlighting their versatility and effectiveness.

ACS Applied Materials & InterfacesVol. 17(21)
Indian Institute of Technology Roorkee (IN)
Openalex Percentile: Top 5%
MXene and MAX Phase Materials
4.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.