Dirac-cone induced metallic conductivity in Cu3(HHTP)2: high-quality MOF thin films fabricated via ML-driven robotic synthesis

Metal–organic frameworks have garnered interest for over 25 years in energy and electronics, yet their adoption in devices has been hindered by low electrical conductivity, largely attributed to activated transport. Our study demonstrates a significant shift, revealing metallic conductivity in Cu3(HHTP)2 thin films—240 S m−1 at room temperature and 300 S m−1 at 100 K, a departure from its presumed semiconductive nature. Achieved through robotic, AI-based layer-by-layer assembly in a self-driving laboratory, this method produces SURMOFs with minimal defects, optimized via rapid surrogate characterization techniques. Our research, supported by both electronic structure calculations and experimental verification, identifies a persistent Dirac cone in the hexagonal D6h symmetry of 2D sheets as crucial for the observed metallic behavior. Notably, even with ABAB stacking in the bulk, this Dirac cone feature maintains metallic conductivity, enhancing at lower temperatures. This breakthrough not only clarifies the conduction mechanism in Cu3(HHTP)2 but also highlights the SDL's potential in developing high-quality MOF thin films for future applications. Our findings indicate that tailoring the Dirac cone's energy could lead to a new class of highly conductive, metallic MOFs.

Publication Details

Journal
Refubium (Universitätsbibliothek der Freien Universität Berlin)
Published
2025-01-01
DOI
https://doi.org/10.17169/refubium-48407
Primary Topic
Metal-Organic Frameworks: Synthesis and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dirac-cone induced metallic conductivity in Cu3(HHTP)2: high-quality MOF thin films fabricated via ML-driven robotic synthesis

Refubium (Universitätsbibliothek der Freien Universität Berlin)
Metal-Organic Frameworks: Synthesis and Applications
article

Dirac-cone induced metallic conductivity in Cu3(HHTP)2: high-quality MOF thin films fabricated via ML-driven robotic synthesis

article en

Abstract

Metal–organic frameworks have garnered interest for over 25 years in energy and electronics, yet their adoption in devices has been hindered by low electrical conductivity, largely attributed to activated transport. Our study demonstrates a significant shift, revealing metallic conductivity in Cu3(HHTP)2 thin films—240 S m−1 at room temperature and 300 S m−1 at 100 K, a departure from its presumed semiconductive nature. Achieved through robotic, AI-based layer-by-layer assembly in a self-driving laboratory, this method produces SURMOFs with minimal defects, optimized via rapid surrogate characterization techniques. Our research, supported by both electronic structure calculations and experimental verification, identifies a persistent Dirac cone in the hexagonal D6h symmetry of 2D sheets as crucial for the observed metallic behavior. Notably, even with ABAB stacking in the bulk, this Dirac cone feature maintains metallic conductivity, enhancing at lower temperatures. This breakthrough not only clarifies the conduction mechanism in Cu3(HHTP)2 but also highlights the SDL's potential in developing high-quality MOF thin films for future applications. Our findings indicate that tailoring the Dirac cone's energy could lead to a new class of highly conductive, metallic MOFs.

Refubium (Universitätsbibliothek der Freien Universität Berlin)
Deutsche Forschungsgemeinschaft, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Affordable and clean energy
Openalex Percentile: Top 61%
Metal-Organic Frameworks: Synthesis and Applications
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.