Atomic-Scale Characterization and Control of Metal-Organic Templates and Photosensitizers on Surfaces

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Self-assembled monolayer molecules have been widely employed as interfacial transport materials in inverted perovskite solar cells (PSCs), demonstrating high efficiency and improved device stability. However, self-assembling monolayer (SAM) molecules often ...

This work investigates how irradiance, temperature, and electrolyte properties (pH, concentration, and flow rate), influence the degradation of spray-pyrolyzed BiVO4 photoanodes during water splitting for solar fuel production. A novel four-cell photoelect ...

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Optical manipulation and detection of biological particulates are crucial procedures in biophotonics. Optical sectioning (OS) opens the avenue to three-dimensional (3D) microscopy, but nonoptical approaches, including sample adhesion and mechanical scannin ...

Simulating the coupled electronic and nuclear response of a molecule to light excitation requires the application of nonadiabatic molecular dynamics. However, when faced with a specific photophysical or photochemical problem, selecting the most suitable th ...

The primary performance limitation in inverted perovskite-based solar cells is the interface between the fullerene-based electron transport layers and the perovskite. Atomic layer deposited thin aluminum oxide (AlOX) interlayers that reduce nonradiative re ...

The top surface of the perovskite layer and the interface with the electron transporting layer play a key role in influencing the performance and operational stability of inverted perovskite solar cells (PSCs). A deficient or ineffective surface passivatio ...

Applications in photodetection, photochemistry, and active metamaterials and metasurfaces require fundamental understanding of ultrafast nonthermal and thermal electron processes in metallic nanosystems. Significant progress has been recently achieved in s ...

With perovskite solar cell (PSC) performance already touching the limits of single junction PV devices, the major challenges have now shifted to upscaling and stability. A plethora of materials and processes have been used for making perovskite solar cells ...

Ion migration is an important phenomenon affecting the performance of hybrid perovskite solar cells. It is particularly challenging, however, to disentangle the contribution of H+ diffusion from that of other ions, and the atomic-scale mechanism remains un ...

Over the past decade, computational atomistic modeling, driven by machine learning (ML), has become indispensable to scientific endeavors, improving our understanding and accelerating the search for compounds with enhanced properties. Traditional atomistic ...

The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of density functional theory (DFT). However, running large simulation cells with DFT is computationally demanding, wh ...

This work presents the changing abundance of surface functional groups (SFGs) on polystyrene (PS) upon weathering within one or a few molecular monolayers from a molecular point of view. PS particles were aged by exposing it to a gas flow of typically (5 % ...

Hydrogen hydrates exhibit a rich phase diagram influenced by both pressure and temperature, with the so-called C2 phase emerging prominently above 2.5 GPa. In this phase, hydrogen molecules are densely packed within a cubic icelike lattice and the interact ...

Defect passivation is an efficient strategy for improving the performance of perovskite solar cells (PSCs). In this study, we introduced a benzodithiophene-based 2D spacer with a short alkyl chain (BDT-C2) into a perovskite film for defect passivation. The ...

Metal halide perovskites have thepotential to revolutionizethefield of photovoltaics, though limited stability has impeded commercialexploitation. The soft heterointerface between the perovskite andcharge-transporting layer is one of the major bottlenecks ...

Deep learning methods outperform human capabilities in pattern recognition and data processing problems and now have an increasingly important role in scientific discovery. A key application of machine learning in molecular science is to learn potential en ...

Compound structural identification for non-targeted screening of organic molecules in complex mixtures is commonly carried out using liquid chromatography coupled to tandem mass spectrometry (UHPLC-HRMS/MS and related techniques). Instrumental developments ...

Atomic-Scale Characterization and Control of Metal-Organic Templates and Photosensitizers on Surfaces

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Tailored Lattice-Matched Carbazole Self-Assembled Molecule for Efficient and Stable Perovskite Solar Cells

Hybrid Sequential Process for Perovskite Absorbers Growth by Pulsed Laser Deposition (PLD)

Effect of Operating Conditions on the Degradation of BiVO4 Photoanodes

Boron-emitter development for TOPCon c-Si solar cells based on plasma-deposited boron diffusion source and poly-Si(n) passivating contact

Non-Resonant Magnetic X-ray Scattering as a Probe of Ultrafast Molecular Spin-State Dynamics: An Ab Initio Theory

Optical tweeze-sectioning microscopy for 3D imaging and manipulation of suspended cells

Roadmap for Molecular Benchmarks in Nonadiabatic Dynamics

A Universal Perovskite/C60 Interface Modification via Atomic Layer Deposited Aluminum Oxide for Perovskite Solar Cells and Perovskite-Silicon Tandems

Suppressing surface and interface recombination to afford efficient and stable inverted perovskite solar cells

Ultrafast hot-carrier dynamics in ultrathin monocrystalline gold

Environmental impacts as the key objectives for perovskite solar cells optimization

Hydrogen Diffusion in Hybrid Perovskites from Exchange NMR

Integrating symmetry and physical constraints into atomic-scale machine learning

Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

Natural and simulated weathering of polystyrene: A molecular view of the polymeric interface

Giant Splitting of the Hydrogen Rotational Eigenenergies in the C2 Filled Ice

Benzodithiophene derivative 2D spacer as a defect passivation material in metal halide perovskite solar cells

Mitigating the Heterointerface Driven Instability in Perovskite Photovoltaics

Ab initio quantum chemistry with neural-network wavefunctions

Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry