Perovskites are a class of materials with a unique crystal structure that have gained significant attention in recent years for their potential applications in solar cells, light-emitting diodes, and other optoelectronic devices.
These materials are characterized by their ABX3 formula, where A and B are cations and X is an anion, often a halide.
Perovskites offer a range of tunable properties, such as high light absorption coefficient, long carrier diffusion lengths, and low-cost fabrication.
Reaserch in this field has been rapidly expanding, with ongoing efforts to optimize perovskite compositions, device architectures, and manufacturing processes to enhance efficiency, stability, and reproducibility.
The versatility and promising performance of perovskites have made them a key area of focus in the development of next-generation photovoltaic and optoelectronic technologies.
One molar solution containing PbX2 and MAX was prepared in DMF or GBL for X=Br−, I−, respectively. The bromide solution was prepared at room temperature, whereas the iodide solution was heated up to 60 °C. The solutions were filtered using PTFE filter with 0.2-μm pore size. Two millilitres of the filtrate were placed in a vial and the vial was kept in an oil bath undisturbed at 80 and 110 °C for Br- and I-based perovskites, respectively. All procedures were carried out under ambient conditions and humidity of 55–57%. The crystals used for measurements were grown for 3 h. The reaction yield for MAPbBr3 and MAPbI3 was calculated to be 35 and 11 wt %, respectively.
Saidaminov M.I., Abdelhady A.L., Murali B., Alarousu E., Burlakov V.M., Peng W., Dursun I., Wang L., He Y., Maculan G., Goriely A., Wu T., Mohammed O.F, & Bakr O.M. (2015). High-quality bulk hybrid perovskite single crystals within minutes by inverse temperature crystallization. Nature Communications, 6, 7586.
The perovskite sensitizer (CH3NH3)PbI3 was prepared according to the reported procedure17 (link). A hydroiodic acid (30 mL, 0.227 mol, 57 wt.% in water, Aldrich) and methylamine (27.8 mL, 0.273 mol, 40% in methanol, TCI) were stirred in the ice bath for 2 h. After stirring at 0oC for 2 h, the resulting solution was evaporated at 50oC for 1 h and produced synthesized chemicals (CH3NH3I). The precipitate was washed three times with diethyl ether and dried under vacuum and used without further purification. To prepare (CH3NH3)PbI3, readily synthesized CH3NH3I (0.395 g) and PbI2 (1.157 g, 99% Aldrich) were mixed in γ-butyrolactone (2 mL, >99% Aldrich) at 60oC for overnight with stirring. Anatase TiO2 nanoparticles were synthesized by acetic acid catalyzed hydrolysis of titanium isopropoxide (97%, Aldrich), followed by autoclaving at 230oC for 12 h. Aqueous solvent in the autoclaved TiO2 colloid solution was replaced by ethanol for preparation of non-aqueous TiO2 paste. Ethyl cellulose (Aldrich), lauric acid (Fluka), and terpineol (Aldrich) were added into the ethanol solution of the TiO2 particles, and then ethanol was removed from the solution using a rotary evaporator to obtain viscous pastes. For homogeneous mixing, the paste was further treated with a three-roll mill. The nominal composition of TiO2/terpineol/ethylcellulose/lauric acid was 1/6/0.3/0.1.
Kim H.S., Lee C.R., Im J.H., Lee K.B., Moehl T., Marchioro A., Moon S.J., Humphry-Baker R., Yum J.H., Moser J.E., Grätzel M, & Park N.G. (2012). Lead Iodide Perovskite Sensitized All-Solid-State Submicron Thin Film Mesoscopic Solar Cell with Efficiency Exceeding 9%. Scientific Reports, 2, 591.
This program is implemented in the Python (3.x) programming language, and both the source code and instructions on how to install it is available at http://atomap.org. It relies heavily on the fitting and modelling routines implemented in HyperSpy [39 ]. Currently, the program is optimized for analysing STEM-images of perovskite oxide materials projected along a direction. However, it is trivial to adapt it for any structure as discussed below in "Adapting for other structures and projections". Extending the code should be easy, and requests for both new features and assistance in adapting for other structures are welcome on the issue tracker (linked from http://atomap.org/) or by e-mail to the corresponding author. The software and source code are distributed under the free and open source GNU General Public License v3.0. The program is sorted into several classes: atom_position, atom_plane, sublattice, and atom_lattice. atom_position is the position of a single atomic column, and contains variables like position, , , and other information about the shape of the atomic column. atom_plane contains all the atom_positions which belong to the same atomic plane. sublattice contains all the atom_positions and atom_planes belonging to the same sublattice, like the A-cations in Fig. 1. atom_lattice contains all the sublattices, so in Fig. 1, this would include the A-cations, B-cations, and oxygen sublattices. The atom_lattice class can be saved and loaded, saving all the atom_position parameters. One current limitation is that the whole image given to the program must have a similar crystal structure. For example, a perovskite heterostructure shown in Figs. 4, 5, and 6 works fine, due to the structures being sufficiently similar. A perovskite oxide film grown on Si would, however, not work. Similarly, if there are any amorphous parts in the image, local bright features could be identified as atomic positions by the peak finding function. One simple solution is to crop the images, so only the same crystal structure is within the image given to the program. This could probably be automated, which would allow for automatic determination of regions with different structures. For example, in an aluminum alloy, one would be able to automatically figure out which regions are aluminum matrix and which are precipitates. When fitting a single sublattice, the fitting is done on individual atomic column using a single 2D Gaussian. One obvious improvement would be to make a model containing all the atomic columns, and fitting them all simultaneously. While this is more computationally demanding, it could reduce the effects from neighboring atomic columns and, therefore, increase the accuracy of the fitting. The amount of improvement would be related to the degree of overlap between the atomic columns. With a very large separation between the atomic columns, this improvement would be zero or very small. With a very small separation, this improvement would be substantial. Quantifying the limits of fitting a single atomic column vs. including the neighboring atomic columns is interesting, but outside the scope of this work as the separation between the atomic columns was sufficiently large. Atomap implements a version of this by removing the most intense sublattice before fitting the less intense sublattices. This is equivalent to having a model where the most intense atomic columns are fitted first, then locked, and afterwards fitting the second most intense atomic columns. Fitting 2D Gaussians to all atomic columns in a data set simultaneously will be experimented with in Atomap in the near future, using the aforementioned process to find reasonable initial values first.
Nord M., Vullum P.E., MacLaren I., Tybell T, & Holmestad R. (2017). Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting. Advanced Structural and Chemical Imaging, 3(1), 9.
Radiant-heat stimuli were generated by an infrared neodymium yttrium aluminum perovskite (Nd:YAP) laser with a wavelength of 1.34 μm (Electronical Engineering). At this wavelength, laser pulses activate directly nociceptive terminals in the most superficial skin layers (15 (link), 16 (link)). Laser pulses were directed on a square area (5 × 5 cm2) centered on the dorsum of the left hand and defined before the beginning of the experimental session. An He-Ne laser pointed to the area to be stimulated. The laser beam was transmitted via an optic fiber, and its diameter was set at ∼7 mm (∼38 mm2) by focusing lenses. The pulse duration was 4 ms, and four stimulus energies were used (E1, 2.5 J; E2, 3 J; E3, 3.5 J; E4, 4 J). After each stimulus, the target of the laser beam was shifted by ∼1 cm in a random direction, to avoid nociceptor fatigue or sensitization.
Hu L, & Iannetti G.D. (2019). Neural indicators of perceptual variability of pain across species. Proceedings of the National Academy of Sciences of the United States of America, 116(5), 1782-1791.
The focus of this work is the analysis of atomic resolution STEM-images of perovskite oxides. As mentioned earlier, these materials are in the form of ABO . The A-site is a larger cation like strontium or lanthanum, the smaller B-site is typically a transition metal like manganese or titanium, and the O is oxygen. A-site cations are usually the heaviest element in the structure, the B-site cations the second heaviest, and oxygen the lightest. The heterostructures studied were La Sr MnO (LSMO) on LaFeO (LFO) on (111)-oriented Nb-doped STO and LSMO on (111)-oriented Nb-doped STO. TEM samples were prepared as thin sections perpendicular to the [1 0]-direction of the STO. Deposition [35 (link), 36 (link)] of the films and the preparation of the TEM specimens [37 (link)] are described in more detail elsewhere.
Processing steps for locating and fitting 2-D Gaussians to every atomic column in a perovskite oxide using STEM-ADF and STEM-ABF data acquired with the electron beam parallel to the [1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{1}$$\end{document}1¯0] direction
An example of a typical STEM image is shown in Fig. 1 (top left). The first aim of the method is to extract the position and shape for all the different atomic columns in these kinds of images. Second, we want to find the relations between the different atomic columns. In essence, the process of fitting one sublattice can be summed up in three steps: (i) Find the positions of all the atomic columns you want to examine. (ii) Refine the positions using center of mass until they are close enough for the 2-D Gaussian fitting to work robustly. (iii) Fit the atomic columns using a 2-D elliptical Gaussian function . This is defined by the following: where is the background, A the amplitude, the center positions, the standard deviations, and the rotation. The background is set to the minimum intensity value of the region around the atomic column. This way of setting the background value is easy and robust. However, it has some drawbacks in that a single pixel with low value due to some kind of artefact can lead to the background varying greatly between the different atomic columns. One way of improving this is by having the background as a parameter while fitting the 2-D Gaussians; however, this reduces the robustness as the chance of poor fitting increases. Therefore, in this work, the simpler minimum value method was used, as it worked well in practice. More advanced forms of background subtraction will be implemented in Atomap in the future. Additional sublattices are found by having a priori crystallographic knowledge on where they are located in relation to the first sublattice, as explained below.
Nord M., Vullum P.E., MacLaren I., Tybell T, & Holmestad R. (2017). Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting. Advanced Structural and Chemical Imaging, 3(1), 9.
The perovskite precursor solution was prepared by dissolving FAPbI3 powder (1.8 M) and MACl (0.63 M, Dyenamo) into mixed solvent of DMF and DMSO (DMF:DMSO = 4:1 v/v, Acros). The perovskite solution was spin coated at 6,000 r.p.m. for 50 s with pouring diethyl ether (1 ml, Acros) as an anti-solvent at 15 s of spin-coat process. Then the substrates were annealed at 150 °C for 10 min in dry air. The DMPESI was dissolved in chloroform (Acros) with different concentration and the solution was spin coated at 4,000 r.p.m. for 20 s on the as-prepared perovskite films and dried on a hot plate at 100 °C for 10 min.
Suo J., Yang B., Mosconi E., Bogachuk D., Doherty T.A., Frohna K., Kubicki D.J., Fu F., Kim Y., Er-Raji O., Zhang T., Baldinelli L., Wagner L., Tiwari A.N., Gao F., Hinsch A., Stranks S.D., De Angelis F, & Hagfeldt A. (2024). Multifunctional sulfonium-based treatment for perovskite solar cells with less than 1% efficiency loss over 4,500-h operational stability tests. Nature Energy, 9(2), 172-183.
1.5 m Cs0.03(FA0.90MA0.10)0.97Pb(IxBr1‐x)3 (x = 0.0–0.4) perovskite precursor was obtained by dissolving FAI, MAI, CsI, PbBr2, PbI2 and 5% mmol RbCl in a mixed solvent of DMF:DMSO = 4:1, and adopted a one‐step spin‐coating process with a two‐step spin‐coating procedure (2000 rpm for 10 s followed by 6000 rpm for 20 s.). For (111)/(001)‐perovskite, IPA/IPA+additive was dropped onto the spinning substrate during the second spin‐coating step at the 12 s. The additive in IPA for NBG is 3 mg mL−1 MACl and for WBG is 1 mg mL−1 PEACl. For randomly oriented perovskite, CB was dropped onto the spinning substrate during the second spin‐coating step at 12 s. The substrate was then immediately transferred on a hotplate and annealed, 120 °C annealed for 20 min for NBG perovskite film and 140 °C annealed for 20 min for WBG perovskite film.
Li D., Sun X., Zhang Y., Guan Z., Yue Y., Wang Q., Zhao L., Liu F., Wei J, & Li H. (2024). Uniaxial‐Oriented Perovskite Films with Controllable Orientation. Advanced Science, 11(19), 2401184.
The two different perovskite solution systems were investigated in great detail in this report. Methylammonium lead iodide, MaPbI3, (MAPI) dissolved in N,N.Dimethylformamide (DMF) with the molality 1 mmol mL−1 (1 m), due to the simplicity of the solution system, and double cation perovskite, Cs0.17FA0.83Pb(I0.91Br0.09)3, dissolved in a 4:1 (v:v) mixture of DMF and Dimethylsulfoxide (DMSO) with the molality 1 mmol mL−1 (1 m) and the addition of 500 µL γ ‐Butylactone (GBL) per mL to the above solution. The solutions had thus a different molality of 1m (i) and ≈0.6m (ii). This difference in molality was chosen to compensate for differences in the deposited thin film thickness caused by different rheological properties of the solutions. The final, dry perovskite thin‐film thicknesses were still different by ≈0.3 µm (as measured by simple profilometry, see Note S8, Supporting Information).
Ternes S., Laufer F, & Paetzold U.W. (2024). Modeling and Fundamental Dynamics of Vacuum, Gas, and Antisolvent Quenching for Scalable Perovskite Processes. Advanced Science, 11(14), 2308901.
Charge transfer from the polariton states was investigated by placing few-layer graphene (FLG) on the perovskite, which had already been exfoliated on the Au substrate. The dry transfer of the FLG onto the perovskite was performed at room temperature inside a nitrogen-filled glovebox to suppress perovskite degradation. Additionally, encapsulation of the perovskites was investigated by spin coating the polystyrene solution at different rpm. Nevertheless, the reflectance and photoluminescence were recorded in a vacuum using the Horiba HR Evolution.
Anantharaman S.B., Lynch J., Stevens C.E., Munley C., Li C., Hou J., Zhang H., Torma A., Darlington T., Coen F., Li K., Majumdar A., Schuck P.J., Mohite A., Harutyunyan H., Hendrickson J.R, & Jariwala D. (2024). Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites. Light, Science & Applications, 13, 1.
ITO-patterned glass substrates (10 Ω sq−1, Huananxiangcheng Ltd.) and ITO-patterned PEN flexible substrates (<15 Ω sq−1, Peccell) were cleaned with deionized water, acetone, and isopropyl alcohol respectively. Then ITO-patterned glass substrates were treated with an oxygen plasma process (Emitech K1050X, 230 V, 100 W) for 5 min before fabrication. The rest fabrication processes of ITO-based and SWCNT-based perovskite solar cells were the same. Cu:NiOx NPs solution was spin-coated on ITO-based and SWCNT-based substrates at 2000 rpm for 20 s, followed by a post-heating process at 120 °C for 10 min. Then, these Cu:NiOx-coated substrates were moved to a UV-ozone cleaning device to receive 5 min of UV-Ozone treatment. Then the KI layer was prepared on top of the Cu:NiOx via spin-coating, the spin-coating condition of the KI layer is 2000 rpm, 30 s with a solution concentration of 2 mg/ml (in water), and heated at 100 °C for 10 min. Here, the composition of the perovskite layer is Cs0.05FA0.80MA0.15Pb(IxBr1-x)3, the perovskite precursor solution was prepared by dissolving 470.23 mg PbI2, 66.06 mg PbBr2, 15.59 mg CsI, 166.64 mg formamidinium iodide, and 19.15 mg methylammonium bromide in a 1 ml solution of 4:1 V/V DMF/DMSO. Following this, the solution was stirred overnight at room temperature. Then the perovskite layer was formed by spin-coating according to a two-step protocol, 1000 rpm for 10 s and 4000 rpm for 35 s, 80 µl CB was dropped 5 s before the end of the second step. Then the film was heated at 100 °C for 60 min on a hotplate. A passivation layer, choline chloride was then fabricated on top of the perovskite layer at 4000 rpm, 30 s with a solution concentration of 1 mg/mL (in IPA), and heated at 100 °C for 30 min. The SnO2 layer was prepared with the SnO2 butanol solution, which was diluted with 1-butanol until the concentration reached 1.25 wt%. Subsequently, SnO2 thin film was spin-coated on top of the perovskite with the diluted solution at 6000 rpm (2000 rpm/s) for 30 s and heated at 100 °C for 40 min. PCBM was employed as the electron transport material, PC61BM (20 mg/ml in CB) was spin-coated at 2000 rpm for 20 s, and dried at 100 °C for 5 min. As for the back SWCNT electrode, the transfer process is the same as the front SWCNT transfer process. For control cells, BCP solution (0.5 mg/mL in IPA) was spin-coated on top of PC61BM. Finally, a 100 nm thick Ag electrode was deposited in a thermal evaporator (>3 × 10−6 Torr, Moorefield thermal evaporator) to complete the fabrication process.
Zhang J., Hu X.G., Ji K., Zhao S., Liu D., Li B., Hou P.X., Liu C., Liu L., Stranks S.D., Cheng H.M., Silva S.R, & Zhang W. (2024). High-performance bifacial perovskite solar cells enabled by single-walled carbon nanotubes. Nature Communications, 15, 2245.
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DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
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N,N-dimethylformamide is a clear, colorless liquid organic compound with the chemical formula (CH3)2NC(O)H. It is a common laboratory solvent used in various chemical reactions and processes.
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Chlorobenzene is a colorless, volatile liquid used as an intermediate in the production of various chemicals. It serves as a precursor for the synthesis of other organic compounds.
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The D8 Advance is a versatile X-ray diffractometer (XRD) designed for phase identification, quantitative analysis, and structural characterization of a wide range of materials. It features advanced optics and a high-performance detector to provide accurate and reliable results.
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Oleic acid is a long-chain monounsaturated fatty acid commonly used in various laboratory applications. It is a colorless to light-yellow liquid with a characteristic odor. Oleic acid is widely utilized as a component in various laboratory reagents and formulations, often serving as a surfactant or emulsifier.
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Oleylamine is a chemical compound used as a surfactant, emulsifier, and lubricant in various industrial applications. It is a long-chain aliphatic amine with a hydrocarbon backbone and an amino group at one end. Oleylamine is commonly used in the formulation of lubricants, coatings, and personal care products.
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Toluene is a colorless, flammable liquid with a distinctive aromatic odor. It is a common organic solvent used in various industrial and laboratory applications. Toluene has a chemical formula of C6H5CH3 and is derived from the distillation of petroleum.
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Acetonitrile is a colorless, volatile, flammable liquid. It is a commonly used solvent in various analytical and chemical applications, including liquid chromatography, gas chromatography, and other laboratory procedures. Acetonitrile is known for its high polarity and ability to dissolve a wide range of organic compounds.
4-tert-butylpyridine is a chemical compound used as a laboratory reagent. It is a pyridine derivative with a tert-butyl group substituted at the 4-position. This compound is commonly utilized in various chemical synthesis and analysis applications within research and development settings.
Lead bromide is an inorganic compound with the chemical formula PbBr2. It is a dense, crystalline solid that is commonly used in various scientific and industrial applications.
Perovskites are a unique class of materials with an ABX3 formula, where A and B are cations and X is an anion, often a halide. They are characterized by their high light absorption coefficient, long carrier diffusion lengths, and low-cost fabrication. These properties make perovskites highly versatile and promising for applications in solar cells, light-emitting diodes, and other optoelectronic devices.
Perovskites can be tuned by varying the A, B, and X components in the ABX3 formula. This allows for the creation of a wide range of perovskite compositions, each with its own unique properties. Common variations include lead-based, tin-based, and mixed-cation perovskites, which offer different performance characteristics and applications.
Perovskites have garnered significant attention for their potential in solar cell technologies, where they have demonstrated high efficiencies and low-cost manufacturing. Additionally, perovskites are being explored for use in light-emitting diodes (LEDs), photodetectors, and other optoelectronic devices due to their strong light-absorbing and emitting properties.
PubCompare.ai is an AI-driven platform that can optimize your perovskite research by helping you screen protocol literature more efficiently and leveraging AI to pinpoint critical insights. The platform's AI-driven analysis can highlight key differences in protocol effectiveness, enabling you to choose the best option for reproducibility and accury in your perovskite studies.
More about "Perovskite"
Perovskites are a remarkable class of materials with a distinctive crystal structure that have gained significant attention in recent years for their potential applications in solar cells, light-emitting diodes (LEDs), and other optoelectronic devices.
These materials are characterized by their ABX3 formula, where A and B are cations, and X is often a halide anion.
Perovskites offer a range of tunable properties, such as high light absorption coefficient, long carrier diffusion lengths, and low-cost fabrication, making them a key focus in the development of next-generation photovoltaic and optoelectronic technologies.
Researchers have been rapidly expanding their exploration of perovskites, with ongoing efforts to optimize perovskite compositions, device architectures, and manufacturing processes to enhance efficiency, stability, and reproducibility.
This includes the use of various solvents and additives, such as DMSO, N,N-dimethylformamide (DMF), chlorobenzene, and toluene, as well as the incorporation of materials like oleic acid, oleylamine, and 4-tert-butylpyridine, to improve the performance and stability of perovskite-based devices.
Advanced characterization techniques, such as the D8 Advance X-ray diffractometer, have been employed to better understand the structural and compositional properties of perovskites, aiding in the optimization of their performance.
The versatility and promising performance of perovskites have made them a key area of focus in the ongoing quest for more efficient and cost-effective optoelectronic technologies.
With the help of AI-driven platforms like PubCompare.ai, researchers can now easily locate relevant protocols from literature, preprints, and patents, and use AI-driven comparisons to identify the best protocols and products, enhancing reproducibity and accuracy in their perovskite studies.
