Prediction of ambient-pressure high-temperature superconductivity in electronically modified transition-metal hydrides

Abstract The search for conventional superconductors with high transition temperatures ( $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> ) has largely focused on intrinsically metallic compounds. In this work, we explore the potential of intrinsically non-metallic compounds to exhibit high- $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> superconductivity under ambient pressure through carrier doping. We identify MgAlFeH 6 , a representative of carrier-doped transition-metal hydrides like Mg 2 FeH 6 , as a promising example with a predicted $${T}_{c}\approx 130\,{\rm{K}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> <mml:mo>≈</mml:mo> <mml:mn>130</mml:mn> <mml:mspace/> <mml:mi>K</mml:mi> </mml:mrow> </mml:math> . We propose that the average projected electron density of states (DOS), defined as the geometric mean of the total and hydrogen-projected DOS at the Fermi level, serves as a simple and computationally inexpensive indicator of high- $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> behavior. Notably, the correlation between $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> and the average projected DOS is stronger than that between $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> and either total DOS or hydrogen-projected DOS. We also highlight the tradeoff between high- $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> and dynamic stability, both of which depend on the electron DOS at the Fermi level. Our findings thus expand the pool of potential superconducting materials and offer a practical route for accelerating the discovery of superconductors suitable for real-world applications.

Authors

Publication Details

Journal
npj Computational Materials
Published
2026-03-28
DOI
https://doi.org/10.1038/s41524-026-02040-x
Primary Topic
Inorganic Chemistry and Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prediction of ambient-pressure high-temperature superconductivity in electronically modified transition-metal hydrides

Olivia D. Schneble, Haowei Xu, Marek Polański, Rafael Jaramillo et al.
npj Computational Materials
Inorganic Chemistry and Materials
article

Prediction of ambient-pressure high-temperature superconductivity in electronically modified transition-metal hydrides

Olivia D. Schneble, Haowei Xu, Marek Polański, Rafael Jaramillo, Ju Li
article en

Abstract

Abstract The search for conventional superconductors with high transition temperatures ( $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> ) has largely focused on intrinsically metallic compounds. In this work, we explore the potential of intrinsically non-metallic compounds to exhibit high- $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> superconductivity under ambient pressure through carrier doping. We identify MgAlFeH 6 , a representative of carrier-doped transition-metal hydrides like Mg 2 FeH 6 , as a promising example with a predicted $${T}_{c}\approx 130\,{\rm{K}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> <mml:mo>≈</mml:mo> <mml:mn>130</mml:mn> <mml:mspace/> <mml:mi>K</mml:mi> </mml:mrow> </mml:math> . We propose that the average projected electron density of states (DOS), defined as the geometric mean of the total and hydrogen-projected DOS at the Fermi level, serves as a simple and computationally inexpensive indicator of high- $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> behavior. Notably, the correlation between $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> and the average projected DOS is stronger than that between $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> and either total DOS or hydrogen-projected DOS. We also highlight the tradeoff between high- $${T}_{c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> </mml:msub> </mml:math> and dynamic stability, both of which depend on the electron DOS at the Fermi level. Our findings thus expand the pool of potential superconducting materials and offer a practical route for accelerating the discovery of superconductors suitable for real-world applications.

npj Computational Materials
Openalex Percentile: Top 5%
Inorganic Chemistry and Materials
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.