Towards photoferroic materials by design: recent progress and perspectives

Castelli, Ivano E.; Olsen, Thomas; Chen, Yunzhong

doi:10.1088/2515-7655/ab428c

Cited by 16 publications

(15 citation statements)

References 116 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, calculations of the mechanical and dynamic stability could be useful to confirm whether the candidate material could be synthesized or not. The light-harvesting efficiency is often estimated by the size of the band gap or full absorption spectrum and the photocatalytic properties with the position of the band edges [ 4 , 10 , 28 , 33 ].…”

Section: Autonomous Workflow and Computational Methodsmentioning

confidence: 99%

“…(2) Ferroelectric semiconductors (photoferroics) have two properties that make them very interesting for a new generation of solar energy conversion materials [ 9 ]. On one side, they can generate photovoltages larger than the band gap, and from the other side, they show an intrinsic polarization, which spontaneously separates the electrons and holes without the need of a

junction or co-catalysts, in PV and PEC devices, respectively [ 10 , 11 ]. By generating photovoltages larger than the band gap, photoferroic materials would be able to easily provide the driving force (reaction overpotentials) necessary to run the hydrogen and, especially, oxygen evolution reactions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Autonomous Design of Photoferroic Ruddlesden-Popper Perovskites for Water Splitting Devices

2022

Self Cite

View full text Add to dashboard Cite

The use of ferroelectric materials for light-harvesting applications is a possible solution for increasing the efficiency of solar cells and photoelectrocatalytic devices. In this work, we establish a fully autonomous computational workflow to identify light-harvesting materials for water splitting devices based on properties such as stability, size of the band gap, position of the band edges, and ferroelectricity. We have applied this workflow to investigate the Ruddlesden-Popper perovskite class and have identified four new compositions, which show a theoretical efficiency above 5%.

show abstract

Section: Autonomous Workflow and Computational Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Autonomous Design of Photoferroic Ruddlesden-Popper Perovskites for Water Splitting Devices

2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Bismuth ferrite with the chemical formula BiFeO3 has been known since the 1950s [1]. However, its potential applications as a semiconductor multifunctional material in piezoelectric devices, spintronics, sensors, photosensitizers, and photocatalyisis have recently gained significant interest [2][3][4][5]. The narrow energy band gap characterizing this material allows the maximum and efficient utilization of the visible light from solar radiation energy as compared to the widely used TiO2 photocatalyst that absorbs in the UV range as a result of its wide band gap [6].…”

Section: Introductionmentioning

confidence: 99%

Energy Band Gap Modeling of Doped Bismuth Ferrite Multifunctional Material Using Gravitational Search Algorithm Optimized Support Vector Regression

Owolabi

Rahman

2021

Crystals

View full text Add to dashboard Cite

Bismuth ferrite (BiFeO3) is a promising multiferroic and multifunctional inorganic chemical compound with many fascinating application potentials in sensors, photo-catalysis, optical devices, spintronics, and information storage, among others. This class of material has special advantages in the photocatalytic field due to its narrow energy band gap as well as the possibility of the internal polarization suppression of the electron-hole recombination rate. However, the narrow light absorption range, which results in a low degradation efficiency, limits the practical application of the compound. Experimental chemical doping through which the energy band gap of bismuth ferrite compound is tailored to the desired value suitable for a particular application is frequently accompanied by the lattice distortion of the rhombohedral crystal structure. The energy band gap of doped bismuth ferrite is modeled in this contribution through the fusion of a support vector regression (SVR) algorithm with a gravitational search algorithm (GSA) using crystal lattice distortion as a predictor. The proposed hybrid gravitational search based support vector regression HGS-SVR model was evaluated by its mean squared error (MSE), correlation coefficient (CC), and root mean square error (RMSE). The proposed HGS-SVR has an estimation capacity with an up to 98.06% accuracy, as obtained from the correlation coefficient on the testing dataset. The proposed hybrid model has a low MSE and RMSE of 0.0092 ev and 0.0958 ev, respectively. The hybridized algorithm further models the impact of several doping materials on the energy band gap of bismuth ferrite, and the predicted energy gaps are in excellent agreement with the measured values. The precision and robustness exhibited by the developed model substantiate its significance in predicting the energy band gap of doped bismuth ferrite at a relatively low cost while the experimental stress is circumvented.

show abstract

“…In addition, the complexity of the calculations and their simulation cost increases at each step. Examples of funnel schemes and workflows for, e. g., visible solar light ferroelectric devices can be found in the literature . In these cases, materials are selected for their stability, light harvesting properties, and interfaces.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Discovery of Materials for Intercalation Electrodes

Bölle

Mathiesen

Nielsen

et al. 2020

Batteries & Supercaps

Self Cite

View full text Add to dashboard Cite

The development of automated computational tools is required to accelerate the discovery of novel battery materials. In this work, we design and implement a workflow, in the framework of Density Functional Theory, which autonomously identifies materials to be used as intercalation electrodes in batteries, based on descriptors like adsorption energies and diffusion barriers. A substantial acceleration for the calculations of the kinetic properties is obtained due to a recent implementation of the Nudged Elastic Bands (NEB) method, which takes into consideration the symmetries of the system to reduce the number of images to calculate. We have applied this workflow to discover new cathode materials for Mg batteries, where two of these materials display a threefold increase in the potential of the Chevrel phase, the state‐of‐the‐art cathode in commercial prototype Mg batteries.

show abstract

Towards photoferroic materials by design: recent progress and perspectives

Cited by 16 publications

References 116 publications

Autonomous Design of Photoferroic Ruddlesden-Popper Perovskites for Water Splitting Devices

Autonomous Design of Photoferroic Ruddlesden-Popper Perovskites for Water Splitting Devices

Energy Band Gap Modeling of Doped Bismuth Ferrite Multifunctional Material Using Gravitational Search Algorithm Optimized Support Vector Regression

Autonomous Discovery of Materials for Intercalation Electrodes

Contact Info

Product

Resources

About