Recent advance on machine learning of MXenes for energy storage and conversion

Abstract

Transition metal carbide/nitride (MXene) is an emerging two-dimensional (2D) material in the field of energy storage and conversion due to the unique 2D structure and high ionic conductivity property, which has been extensively focused. However, the MXenes family possesses tremendous species variety and element composition with more than 90% of unknown family members.The traditional experimental methods always focused on single species, which is time-consuming and not systematic enough. Currently, machine learning, as an emerging computer technology, provided an advanced technique to boost the application of the MXene family comprehensively. In this review, we comprehensively summarize and comment on the latest application progress of machine learning in the development of MXene materials, focusing on the internal mechanism between machine learning and material development. Applications of MXene in the field of battery, supercapacitor, biological, and catalysis were fully reviewed. It can open up a new road map for the development of MXene materials in the new era.

Dimensional engineering of anode materials for high performance potassium ion hybrid capacitor—A review

“…(d) We found that many scholars used DFT or molecular dynamics simulation to fully explore materials when analyzing new PIHC anode materials, and obtained satisfactory results. With the increase of artificial intelligence hashrate, theoretical simulation combined with experiment has become a new way to reduce the cost of scientific researches and accelerate the cycle of scientific researches 142 . (e) In previous reports, the charge storage mechanism of PIHC has been explained differently, so verifying the mechanism based on different in‐situ characterization techniques is of great necessity.…”

“…With the increase of artificial intelligence hashrate, theoretical simulation combined with experiment has become a new way to reduce the cost of scientific researches and accelerate the cycle of scientific researches. 142 (e) In previous reports, the charge storage mechanism of PIHC has been explained differently, so verifying the mechanism based on different in-situ characterization techniques is of great necessity. In addition, the PIHC reports are at an ideal stage, and their performance can only be replicated under laboratory conditions.…”

Graph representation of multi-dimensional materials

“…An atom-centric representation proposed by Hu and Parker [145] defines connections using a cut-off distance, which is computed based on the number density of atoms and nth nearest neighbour peaks. Beyond graphene, other 2D materials, such as transition metal carbides (MXene) [146], transition metal chalcogenides [147], and monolayer phosphorene [148], have been applied for various applications, from electronics to catalysts.…”

Advance of Prussian Blue‐Derived Nanohybrids in Energy Storage: Current Status and Perspective

“…[1][2][3] Among them, lithiumion battery (LIB) technology has improved dramatically in the past three decades. [4][5][6][7][8] Energy storage has become a global imperative, [9][10][11][12][13] which is why advanced energy storage materials are gaining traction in the scientific community.…”