Direct Experimental Evidence for Substrate Adatom Incorporation into a Molecular Overlayer.
Philip J MousleyLuke A RochfordPaul T P RyanPhilip BloweyJames LawrenceDavid A DuncanHadeel HussainBillal SohailTien-Lin LeeGavin R BellGiovanni CostantiniReinhard J MaurerChristopher NicklinDavid Phillip WoodruffPublished in: The journal of physical chemistry. C, Nanomaterials and interfaces (2022)
While the phenomenon of metal substrate adatom incorporation into molecular overlayers is generally believed to occur in several systems, the experimental evidence for this relies on the interpretation of scanning tunneling microscopy (STM) images, which can be ambiguous and provides no quantitative structural information. We show that surface X-ray diffraction (SXRD) uniquely provides unambiguous identification of these metal adatoms. We present the results of a detailed structural study of the Au(111)-F 4 TCNQ system, combining surface characterization by STM, low-energy electron diffraction, and soft X-ray photoelectron spectroscopy with quantitative experimental structural information from normal incidence X-ray standing wave (NIXSW) and SXRD, together with dispersion-corrected density functional theory (DFT) calculations. Excellent agreement is found between the NIXSW data and the DFT calculations regarding the height and conformation of the adsorbed molecule, which has a twisted geometry rather than the previously supposed inverted bowl shape. SXRD measurements provide unequivocal evidence for the presence and location of Au adatoms, while the DFT calculations show this reconstruction to be strongly energetically favored.
Keyphrases
- density functional theory
- high resolution
- electron microscopy
- molecular dynamics
- single molecule
- dual energy
- body mass index
- mass spectrometry
- sensitive detection
- crystal structure
- optical coherence tomography
- computed tomography
- magnetic resonance
- high speed
- reduced graphene oxide
- health information
- magnetic resonance imaging
- healthcare
- risk factors
- gold nanoparticles
- deep learning
- electronic health record
- big data
- physical activity
- amino acid
- bioinformatics analysis
- solar cells
- data analysis
- monte carlo
- label free
- contrast enhanced