Results 181 to 190 of about 87,943 (287)
A compact, nonporous, and highly crystalline layered inorganic precursor formed by thermal evaporation inherently restricts its conversion into the halide perovskite phase during vapor‐assisted hybrid two‐step deposition. Introducing localized heterogeneous nucleation sites during vapor deposition enables deliberate modulation of the inorganic layer's ...
Sung‐Eun Kim +10 more
wiley +1 more source
Halide Perovskites for Photo(electro)catalytic Sustainable Energy: Recent Advances and Challenges. [PDF]
Yin R +13 more
europepmc +1 more source
Lattice Coherency‐Driven (111)‐Oriented Wide Bandgap Perovskite Films
Methylammonium lead chloride (MAPbCl3)‐derived seed templates regulate wide‐bandgap perovskite crystallization through coupled thermodynamic and kinetic effects. Lattice‐coherent templating lowers the energy cost for (111) epilayer growth, while growth retardation controls crystallization kinetics, ultimately producing highly crystalline face‐up (111 ...
Yu‐Na Lee +5 more
wiley +1 more source
Ionic gel-mediated synthesis of nanostructured chiral 2D halide perovskites with amplified chiroptical response. [PDF]
Lee DK +11 more
europepmc +1 more source
A wide process window is essential for the commercialization of perovskite photovoltaics. Here, we demonstrate an amorphous π‐conjugated passivator having an asymmetric mono‐iodine substituent on a carbazole moiety imparts a high dipole moment, desirable molecular energy levels, and high thickness tolerance, thereby enabling a wide process window in ...
Hyun Seo Kim +17 more
wiley +1 more source
Thermodynamic Stability and Hydrogen Bonds in Mixed Halide Perovskites. [PDF]
Camayo-Gutierrez L +4 more
europepmc +1 more source
Multiscale perspectives on how excess charges in soft lead halide perovskites induce operational instability in photovoltaic devices are presented. Localized carriers formed under thermodynamic non‐equilibrium states modify atomistic interactions and drive lattice distortions, accelerating device degradation.
Joo‐Hong Lee +6 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
High-Accuracy Machine Learning Projections of Composition-Dependent Thermal Stability in Halide Perovskites. [PDF]
Hering AR +7 more
europepmc +1 more source
Composite cathode engineering and stack pressure co‐optimization enable a high‐performance all‐solid‐state chloride‐ion battery based on a VOCl/CsSn₀.₉In₀.₀₆₇Cl3/In architecture, delivering 169 mAh g−1 with 500‐cycle durability. Electrode‐resolved impedance tracking via distribution of relaxation times revealed progressive interphase and charge ...
Soutam Panja +7 more
wiley +1 more source

