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Advances in halide perovskite and computational science

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Why can the perovskite material perform so well despite countless defects?


The emergence and development of perovskite

Here are two high-performance materials. Material A is cheap and easy to make, but it has poorstability. Material B is difficult to make and has a higher production cost than A but has excellent stability. Will we choose material A and increase its stability? Will we choose material B and increase its productivity? I think that people would generally choose A. The reason is simple. When it is easy to make and the cost is low, the opportunity for more people to participate in research increases, and the possibility of breaking through material limits with collective intelligence increases.

What I want to talk about now is the organic-inorganic hybrid perovskite (later perovskite), which is an example of a material with A’s characteristics. In 2009, Japan’s Miyasaka Group announced the first perovskite solar cell using methylammonium lead triiodide (MAPbI3), an organic-inorganic hybrid material, as a dye substitute for dye-sensitized solar cells. Since then, perovskites have attract tremendous interests from the solar cell community for nearly a decade, and its certified efficiency has recently come close to the highest efficiency of a single crystal silicon solar cell. Of course, we must keep in mind that material A has a problem with stability.

Figure 1: Various applications of halide perovskite and the crystal structure of MAPbI3

Figure 1: Various applications of halide perovskite and the crystal structure of MAPbI3


Why did it have to be perovskite?

The low barrier of entry is one of the biggest reasons for the rapid growth of perovskite materials in a short time. Various high-efficiency semiconductor devices, including solar cells, can only be fabricated by a solution process without expensive vacuum deposition equipment, so many researchers have been able to enter the perovskite material research field over the past decade. Recently, solar cells, photoelectric devices, such as LED, X-ray imaging, and photosensors, and electronic devices, such as memristors and thin-film transistors, have been included as research subjects.

Even if the process is simple and economically feasible, if the performance were not good, the interest in perovskite would not have been as great as it is now. The question of why it performs well even in processes with relatively many defects and difficult impurity control compared to other thin-film materials using vacuum deposition processes has been one of the main concerns of researchers from the beginning. When I first heard about the perovskite solar cell in the winter of 2013, the first question that came to me was, “Why can the perovskite material perform so well despite countless defects?”

Figure 2: Conceptual diagram and research results of halide perovskite’s unique properties

Figure 2: Conceptual diagram and research results of halide perovskite’s unique properties


Computational study on perovskites

Computational methods may be the first choice when a fundamental question about material properties arises. There were several theoretical investigations on the intrinsic defect characteristics of perovskites by computational scientists interested in robustness against defects in 2014. All of those reports revealed that intrinsic defects seldom make the deep level defects within the bandgap, which explains why perovskites can exhibit excellent performance despite numerous defects. According to the findings of subsequent studies, Rashba spin-orbit coupling, polaronic charge transport, and low electron-phonon interaction combined contribute to perovskite’s excellent photoelectric properties.

As the development of perovskite materials is accelerated and numerous research results are pouring out, the application fields for computational material science research are also diversified and faced with the need to perform analysis of more complex systems. Inevitably, systems are becoming more complex, and the methodologies for performing calculations are becoming more sophisticated. The perovskite material itself must deal with five atomic systems (H, C, N, I, Pb), but in the case of surface treatment or alloying, seven to nine atomic systems analysis is required. Organic molecules move dynamically inside the lattice and maintain a lattice structure with high crystallinity, but in density functional theory calculation, the lattice structure is placed in a fixed position and analyzed, so the lattice structure collapses, or convergence problems frequently occur. (In fact, it is the reason why many computational material researchers were hesitant to start their calculation of perovskites in the early days.) In addition, spin-orbit coupling, which takes a lot of computation time because of Pb’s presence, must be considered.

A significant loss occurs in the “research speed” part, which has been claimed to be computational research’s biggest advantage. Meanwhile, because of the ease of the process, the material synthesis rate is unprecedentedly quick in the semiconducting thin-film manufacturing field. A specific composition came up during a discussion with a research team I collaborate with, and a scene where the experimental team’s researcher went to the laboratory to make a sample and bring it back in less than an hour is one of the unforgettable episodes.

Figure 3: Perovskite’s dimension control and bandgap modulation by alloying

Figure 3: Perovskite’s dimension control and bandgap modulation by alloying


For computational materials researchers, perovskite is

Although manufacturing is easy, computational methodology application to perovskite materials is difficult because its internal structure and physical phenomena are complicated. The fact that the material’s stability is so low that it is difficult to analyze with an electron microscope is also a challenge for computational materials researchers.

Nevertheless, I would like to say that computational research on perovskite still has many attractive aspects. First, it can be said that the most cutting-edge technologies are utilized in the computational materials science field. Because perovskite’s main application is optoelectronic devices, it is necessary to analyze the correlation between excited electrons and phonons. For this purpose, the ground state calculation alone is insufficient. To this end, various methodologies to calculate carrier lifetime and attempts to apply the time-dependent density functional theory are underway.

Second, considering that synthesis is relatively easy, it can be said to be advantageous for experimentally verifying candidates derived through computational screening or artificial intelligence (AI) calculations. Because of AI development and the explosive increase in computational resources, attempts to develop new eco-friendly perovskite materials through calculation are continuously reported. Beyond the previously known three-dimensional structure with an ABX3 configuration, two-dimensional, one-dimensional, and multidimensional hybrid structures have been reported one after another, so there will be countless systems that require calculations in the future.

Finally, I would like to highlight the hybrid characteristics of perovskite materials. Although perovskite has mixed physical properties, the distinction between organic/inorganic terms that distinguish existing materials is unclear, and some say it has “crystal-liquid duality.” In the past, research methodologies and concepts were established for each organic/inorganic field. Now, the unified theory of the two distinct fields is required and perovskites can become a leading material for this synergetic research fields.



As “Borderless” has become a hot topic in all fields of society these days, materials at the material world’s boundary are considered organic-inorganic hybrid perovskite materials. With the development of AI and big data‒related technologies, all computational materials fields face a period of rapid change. I would like to say that there are computational materials researchers studying hybrid perovskite at the point where the boundaries meet.



3) Kim, Y. C. et al. Printable organometallic perovskite enables large-area, low-dose X-ray imaging. Nature 550, 87–91 (2017).
4) Hwang, B. et al. Effect of halide-mixing on the switching behaviors of organic-inorganic hybrid perovskite memory. Sci.Rep. 7, 43794 (2017).
5) Xie, C., et al. Perovskite‐Based Phototransistors and Hybrid Photodetectors. Adv. Func. Mater. 30, 1903907 (2020).
6) Zheng, F. et al. Rashba Spin–Orbit Coupling Enhanced Carrier Lifetime in CH3NH3PbI3. Nano Lett 15, 7794–7800 (2015).
7) Zhu, H. et al. Screening in crystalline liquids protects energetic carriers in hybrid perovskites. Science 353, 1409–1413 (2016).
8) Saidaminov, M. I. Mohammed, O. F. & Bakr, O. M. Low-Dimensional-Networked Metal Halide Perovskites: The Next Big Thing. ACS Energy Lett. 2, 889–896 (2017).
9) Protesescu, L. et al. Nanocrystals of Cesium Lead Halide Perovskites (CsPbX3, X = Cl, Br, and I): Novel Optoelectronic Materials Showing Bright Emission with Wide Color Gamut. Nano Lett 15, 3692–3696 (2015).

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 Ki-Ha Hong, Department of Materials Science and Engineering, Hanbat National University 


 Ki-Ha Hong | Department of Materials Science and Engineering, Hanbat National University