scholarly journals Design Principles of Large Cation Incorporation in Halide Perovskites

Molecules ◽  
2021 ◽  
Vol 26 (20) ◽  
pp. 6184
Author(s):  
Heesoo Park ◽  
Syam Kumar ◽  
Sanjay Chawla ◽  
Fedwa El-Mellouhi
Keyword(s):  
Density Functional ◽  
Perovskite Solar Cells ◽  
Enthalpy Of Mixing ◽  
Design Principles ◽  
Structural Features ◽  
Bayesian Optimization ◽  
Intrinsic Stability ◽  
Halide Perovskites ◽  
Large Cation ◽  
Search Domain

Perovskites have stood out as excellent photoactive materials with high efficiencies and stabilities, achieved via cation mixing techniques. Overcoming challenges to the stabilization of Perovskite solar cells calls for the development of design principles of large cation incorporation in halide perovskite to accelerate the discovery of optimal stable compositions. Large fluorinated organic cations incorporation is an attractive method for enhancing the intrinsic stability of halide perovskites due to their high dipole moment and moisture-resistant nature. However, a fluorinated cation has a larger ionic size than its non-fluorinated counterpart, falling within the upper boundary of the mixed-cation incorporation. Here, we report on the intrinsic stability of mixed Methylammonium (MA) lead halides at different concentrations of large cation incorporation, namely, ehtylammonium (EA; [CH3CH2NH3]+) and 2-fluoroethylammonium (FEA; [CH2FCH2NH3]+). Density functional theory (DFT) calculations of the enthalpy of the mixing and analysis of the perovskite structural features enable us to narrow down the compositional search domain for EA and FEA cations around concentrations that preserve the perovskite structure while pointing towards the maximal stability. This work paves the way to developing design principles of a large cation mixture guided by data analysis of DFT data. Finally, we present the automated search of the minimum enthalpy of mixing by implementing Bayesian optimization over the compositional search domain. We introduce and validate an automated workflow designed to accelerate the compositional search, enabling researchers to cut down the computational expense and bias to search for optimal compositions.

scholarly journals A Physical Data Fusion Approach to Optimize Compositional Stability of Halide Perovskites

2020 ◽  
Author(s):  
Shijing Sun ◽  
Armi Tiihonen ◽  
Felipe Oviedo ◽  
Zhe Liu ◽  
Janak Thapa ◽  
...  
Keyword(s):  
Thin Film ◽  
Data Fusion ◽  
Density Functional ◽  
Grazing Incidence ◽  
Linear Instability ◽  
Bayesian Optimization ◽  
Environmental Stability ◽  
Lead Iodide ◽  
Halide Perovskites ◽  
Compositional Space

<p>Compositional search within multinary perovskites employing brute force synthesis are prohibitively expensive in large chemical spaces. To identify the most stable multi-cation lead iodide perovskites containing Cs, formamidinium (FA) and methylammonium (MA), we fuse results from density functional theory (DFT) calculations and <i>in situ</i> thin-film degradation test within an end-to-end machine learning (ML) algorithm to inform the compositional optimization of Cs<sub>x</sub>MA<sub>y</sub>FA<sub>1-x-y</sub>PbI<sub>3</sub>. We integrate phase thermodynamics modelling as a <i>probabilistic constraint</i> in a Bayesian optimization (BO) loop, which effectively guides the experimental search while considering both structural and environmental stability. After three optimization rounds and only sampling 1.8% of the compositional space, we identify thin-film compositions centred at Cs<sub>0.17</sub>MA<sub>0.03</sub>FA<sub>0.80</sub>PbI<sub>3</sub> that achieve a 3x delay in macroscopic degradation onset under elevated temperature, humidity, and light compared with the more complex state-of-the-art Cs<sub>0.05</sub>(MA<sub>0.17</sub>FA<sub>0.83</sub>)<sub>0.95</sub>Pb(I<sub>0.83</sub>Br<sub>0.17</sub>)<sub>3</sub>. We find up to 8% of MA can be incorporated into the perovskite structure before stability is significantly compromised. Cs is beneficial at low concentrations, however, beyond 17% is found to contribute to reduced stability<b>.</b> Synchrotron-based grazing-incidence wide-angle X-ray scattering (GIWAXS) further validates that the interplay of chemical decomposition and phase separation governs the non-linear instability landscape of this compositional space. We reveal the detrimental role of the ẟ-CsPbI<sub>3</sub> minority phase in accelerating degradation and it can be kinetically suppressed by co-optimising Cs and MA content, providing insights into simplifying perovskite compositions for further environmental stability enhancement. Our approach realizes the effectiveness of ML-enabled data fusion in achieving a holistic, efficient, and physics-informed experimentation for multinary systems, potentially generalisable to materials search in the vast structural and alloyed spaces beyond halide perovskites.</p><br>

scholarly journals A Physical Data Fusion Approach to Optimize Compositional Stability of Halide Perovskites

2020 ◽  
Author(s):  
Shijing Sun ◽  
Armi Tiihonen ◽  
Felipe Oviedo ◽  
Zhe Liu ◽  
Janak Thapa ◽  
...  
Keyword(s):  
Thin Film ◽  
Data Fusion ◽  
Density Functional ◽  
Grazing Incidence ◽  
Linear Instability ◽  
Bayesian Optimization ◽  
Environmental Stability ◽  
Lead Iodide ◽  
Halide Perovskites ◽  
Compositional Space

<p>Compositional search within multinary perovskites employing brute force synthesis are prohibitively expensive in large chemical spaces. To identify the most stable multi-cation lead iodide perovskites containing Cs, formamidinium (FA) and methylammonium (MA), we fuse results from density functional theory (DFT) calculations and <i>in situ</i> thin-film degradation test within an end-to-end machine learning (ML) algorithm to inform the compositional optimization of Cs<sub>x</sub>MA<sub>y</sub>FA<sub>1-x-y</sub>PbI<sub>3</sub>. We integrate phase thermodynamics modelling as a <i>probabilistic constraint</i> in a Bayesian optimization (BO) loop, which effectively guides the experimental search while considering both structural and environmental stability. After three optimization rounds and only sampling 1.8% of the compositional space, we identify thin-film compositions centred at Cs<sub>0.17</sub>MA<sub>0.03</sub>FA<sub>0.80</sub>PbI<sub>3</sub> that achieve a 3x delay in macroscopic degradation onset under elevated temperature, humidity, and light compared with the more complex state-of-the-art Cs<sub>0.05</sub>(MA<sub>0.17</sub>FA<sub>0.83</sub>)<sub>0.95</sub>Pb(I<sub>0.83</sub>Br<sub>0.17</sub>)<sub>3</sub>. We find up to 8% of MA can be incorporated into the perovskite structure before stability is significantly compromised. Cs is beneficial at low concentrations, however, beyond 17% is found to contribute to reduced stability<b>.</b> Synchrotron-based grazing-incidence wide-angle X-ray scattering (GIWAXS) further validates that the interplay of chemical decomposition and phase separation governs the non-linear instability landscape of this compositional space. We reveal the detrimental role of the ẟ-CsPbI<sub>3</sub> minority phase in accelerating degradation and it can be kinetically suppressed by co-optimising Cs and MA content, providing insights into simplifying perovskite compositions for further environmental stability enhancement. Our approach realizes the effectiveness of ML-enabled data fusion in achieving a holistic, efficient, and physics-informed experimentation for multinary systems, potentially generalisable to materials search in the vast structural and alloyed spaces beyond halide perovskites.</p><br>

scholarly journals A Physical Data Fusion Approach to Optimize Compositional Stability of Halide Perovskites

2020 ◽  
Author(s):  
Shijing Sun ◽  
Armi Tiihonen ◽  
Felipe Oviedo ◽  
Zhe Liu ◽  
Janak Thapa ◽  
...  
Keyword(s):  
Thin Film ◽  
Data Fusion ◽  
Density Functional ◽  
Grazing Incidence ◽  
Linear Instability ◽  
Bayesian Optimization ◽  
Environmental Stability ◽  
Lead Iodide ◽  
Halide Perovskites ◽  
Compositional Space

<p>Compositional search within multinary perovskites employing brute force synthesis are prohibitively expensive in large chemical spaces. To identify the most stable multi-cation lead iodide perovskites containing Cs, formamidinium (FA) and methylammonium (MA), we fuse results from density functional theory (DFT) calculations and <i>in situ</i> thin-film degradation test within an end-to-end machine learning (ML) algorithm to inform the compositional optimization of Cs<sub>x</sub>MA<sub>y</sub>FA<sub>1-x-y</sub>PbI<sub>3</sub>. We integrate phase thermodynamics modelling as a <i>probabilistic constraint</i> in a Bayesian optimization (BO) loop, which effectively guides the experimental search while considering both structural and environmental stability. After three optimization rounds and only sampling 1.8% of the compositional space, we identify thin-film compositions centred at Cs<sub>0.17</sub>MA<sub>0.03</sub>FA<sub>0.80</sub>PbI<sub>3</sub> that achieve a 3x delay in macroscopic degradation onset under elevated temperature, humidity, and light compared with the more complex state-of-the-art Cs<sub>0.05</sub>(MA<sub>0.17</sub>FA<sub>0.83</sub>)<sub>0.95</sub>Pb(I<sub>0.83</sub>Br<sub>0.17</sub>)<sub>3</sub>. We find up to 8% of MA can be incorporated into the perovskite structure before stability is significantly compromised. Cs is beneficial at low concentrations, however, beyond 17% is found to contribute to reduced stability<b>.</b> Synchrotron-based grazing-incidence wide-angle X-ray scattering (GIWAXS) further validates that the interplay of chemical decomposition and phase separation governs the non-linear instability landscape of this compositional space. We reveal the detrimental role of the ẟ-CsPbI<sub>3</sub> minority phase in accelerating degradation and it can be kinetically suppressed by co-optimising Cs and MA content, providing insights into simplifying perovskite compositions for further environmental stability enhancement. Our approach realizes the effectiveness of ML-enabled data fusion in achieving a holistic, efficient, and physics-informed experimentation for multinary systems, potentially generalisable to materials search in the vast structural and alloyed spaces beyond halide perovskites.</p><br>

High-throughput computational material screening of the cycloalkane-based two-dimensional Dion–Jacobson halide perovskites for optoelectronics

2021 ◽  
Author(s):  
Guoqi Zhao ◽  
Jiahao Xie ◽  
Kun Zhou ◽  
Bangyu Xing ◽  
Xinjiang Wang ◽  
...  
Keyword(s):  
High Throughput ◽  
Density Functional ◽  
Perovskite Solar Cells ◽  
Two Dimensional ◽  
Photovoltaic Properties ◽  
Wide Range ◽  
Stability Issue ◽  
Halide Perovskites ◽  
The Stability ◽  
Inorganic Framework

Abstract Two-dimensional (2D) layered perovskites have emerged as potential alternates to traditional 3D analogs to solve the stability issue of perovskite solar cells. In recent years, many efforts have been spent on manipulating the interlayer organic spacing cation to improve the photovoltaic properties of Dion–Jacobson (DJ) perovskites. In this work, a serious of cycloalkane (CA) molecules were selected as the organic spacing cation in 2D DJ perovskites, which can widely manipulate the optoelectronic properties of DJ perovskites. The underlying relationship between the CA interlayer molecules and the crystal structures, thermodynamic stabilities, and electronic properties of 58 DJ perovskites has been investigated by using automatic high-throughput workflow cooperated with density-functional (DFT) calculations. We have found that these CA-based DJ perovskites are all thermodynamic stable. The sizes of the cycloalkane molecules can influence the degree of inorganic framework distortion and further tune the bandgaps with a wide range of 0.9~2.1 eV. These findings indicate the cycloalkane molecules are suitable for spacing cation in 2D DJ perovskites and provide a useful guidance in designing novel 2D DJ perovskites for optoelectronic applications.

scholarly journals Electronic and optical properties of vacancy ordered double perovskites A2BX6 (A = Rb, Cs; B = Sn, Pd, Pt; and X = Cl, Br, I): a first principles study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muhammad Faizan ◽  
K. C. Bhamu ◽  
Ghulam Murtaza ◽  
Xin He ◽  
Neeraj Kulhari ◽  
...  
Keyword(s):  
Optical Properties ◽  
Band Gap ◽  
First Principles ◽  
Density Functional ◽  
Perovskite Solar Cells ◽  
Dielectric Constants ◽  
Maximum Efficiency ◽  
Exchange Potential ◽  
Double Perovskites ◽  
Electronic And Optical Properties

AbstractThe highly successful PBE functional and the modified Becke–Johnson exchange potential were used to calculate the structural, electronic, and optical properties of the vacancy-ordered double perovskites A2BX6 (A = Rb, Cs; B = Sn, Pd, Pt; X = Cl, Br, and I) using the density functional theory, a first principles approach. The convex hull approach was used to check the thermodynamic stability of the compounds. The calculated parameters (lattice constants, band gap, and bond lengths) are in tune with the available experimental and theoretical results. The compounds, Rb2PdBr6 and Cs2PtI6, exhibit band gaps within the optimal range of 0.9–1.6 eV, required for the single-junction photovoltaic applications. The photovoltaic efficiency of the studied materials was assessed using the spectroscopic-limited-maximum-efficiency (SLME) metric as well as the optical properties. The ideal band gap, high dielectric constants, and optimum light absorption of these perovskites make them suitable for high performance single and multi-junction perovskite solar cells.

A Review on Stability of Inorganic Metal Halide Perovskites: Challenge and Opportunity for Stable Solar Cells

2021 ◽  
Author(s):  
Wanchun Xiang ◽  
Shengzhong Liu ◽  
Wolfgang Tress
Keyword(s):  
Solar Cells ◽  
High Temperature ◽  
Metal Halide ◽  
Inorganic Perovskite ◽  
The Past ◽  
Intrinsic Stability ◽  
Halide Perovskites

Inorganic perovskite based solar cells (PSCs) have been receiving unprecedented attention worldwide in the past several years due to their higher intrinsic stability towards high temperature and high theoretical power...

scholarly journals Structural, Electronic, and Optical Properties of Group 6 Doped Anatase TiO2: A Theoretical Approach

2021 ◽  
Vol 11 (4) ◽  
pp. 1657
Author(s):  
Petros-Panagis Filippatos ◽  
Nikolaos Kelaidis ◽  
Maria Vasilopoulou ◽  
Dimitris Davazoglou ◽  
Alexander Chroneos
Keyword(s):  
Optical Properties ◽  
Solar Cells ◽  
Electron Transport ◽  
Density Functional ◽  
Perovskite Solar Cells ◽  
Solar Spectrum ◽  
Type Conductivity ◽  
Electronic And Optical Properties ◽  
Group 6 ◽  
Visible Wavelengths

Titania (TiO2) is a key material used as an electron transport in dye-sensitized and halide perovskite solar cells due to its intrinsic n-type conductivity, visible transparency, low-toxicity, and abundance. Moreover, it exhibits pronounced photocatalytic properties in the ultra-violet part of the solar spectrum. However, its wide bandgap (around 3.2 eV) reduces its photocatalytic activity in the visible wavelengths’ region and electron transport ability. One of the most efficient strategies to simultaneously decrease its bandgap value and increase its n-type conductivity is doping with appropriate elements. Here, we have investigated using the density functional theory (DFT), as well as the influence of chromium (Cr), molybdenum (Mo), and tungsten (W) doping on the structural, electronic, and optical properties of TiO2. We find that doping with group 6 elements positively impacts the above-mentioned properties and should be considered an appropriate method for photocatalystic applications. In addition to the pronounced reduction in the bandgap values, we also predict the formation of energy states inside the forbidden gap, in all the cases. These states are highly desirable for photocatalytic applications as they induce low energy transitions, thus increasing the oxide’s absorption within the visible. Still, they can be detrimental to solar cells’ performance, as they constitute trap sites for photogenerated charge carriers.

Cluster, Surface and Bulk Properties of ZnCd Binary Alloys: Molecular-Dynamics Simulations

2005 ◽  
Vol 502 ◽  
pp. 51-56 ◽  
Author(s):  
Sakir Erkoc
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Density Functional ◽  
Structural Features ◽  
Bulk Materials ◽  
Bulk Properties ◽  
Atom Clusters ◽  
Dynamics Simulations ◽  
Mixed Clusters ◽  
Stable Structures

The structural and electronic properties of isolated neutral ZnmCdn clusters for m+n £ 3 have been investigated by performing density functional theory calculations at B3LYP level. The optimum geometries, vibrational frequencies, electronic structures, and the possible dissosiation channels of the clusters considered have been obtained. An empirical many-body potential energy function (PEF), which comprices two- and three-body atomic interactions, has been developed to investigate the structural features and energetics of ZnmCdn (m+n=3,4) microclusters. The most stable structures were found to be triangular for the three-atom clusters and tetrahedral for the four-atom clusters. On the other hand, the structural features and energetics of Znn-mCdm (n=7,8) microclusters, and Zn50, Cd50, Zn25Cd25, Zn12Cd38, and Zn38Cd12 nanoparticles have been investigated by performing molecular-dynamics computer simulations using the developed PEF. The most stable structures were found to be compact and three-dimensional for all elemental and mixed clusters. An interesting structural feature of the mixed clusters is that Zn and Cd atoms do not mix in mixed clusters, they come together almost without mixing. Surface and bulk properties of Zn, Cd, and ZnCd systems have been investigated too by performing molecular-dynamics simulations using the developed PEF. Surface reconstruction and multilayer relaxation on clean surfaces, adatom on surface, substitutional atom on surface and bulk materials, and vacancy on surface and bulk materials have been studied extensively.

Iron Chelation by thiocytosine: Investigating electronic and structural features for describing tautomerism and metal chelation processes

2021 ◽  
pp. 1-8
Author(s):  
Azadeh Jafari Rad ◽  
Maryam Abbasi ◽  
Bahareh Zohrevand
Keyword(s):  
Density Functional Theory ◽  
Dft Calculations ◽  
Molecular Orbital ◽  
Density Functional ◽  
Biological Systems ◽  
Iron Chelation ◽  
Structural Features ◽  
Metal Chelation ◽  
Functional Theory

This work was performed regarding the importance of iron (Fe) chelation for biological systems. This goal was investigated by assistance of a model of thiocytosine (TC) for participating in Fe-chelation processes. First, formations of tautomeric conformations were investigated to explore existence of possible structures of TC. Next, Fe-chelation processes were examined for all four obtained tautomers of TC. The results indicated that thiol tautomers could be seen at higher stability than thio tautomers, in which one of such thiol tautomers yielded the strongest Fe-chelation process to build FeTC3 model. As a consequence, parallel to the results of original TC tautomers, Fe-chelated models were found to be achievable for meaningful chelation processes or sensing the existence of Fe in media. Examining molecular orbital features could help for sensing purposes. The results of this work were obtained by performing density functional theory (DFT) calculations proposing TC compounds suitable for Fe-chelation purposes.

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