Integrating Bayesian Inference with Scanning Probe Experiments for Robust Identification of Surface Adsorbate Configurations

Abstract Controlling the properties of organic/inorganic materials requires detailed knowledge of their molecular adsorption geometries. This is often unattainable, even with current state-of-the-art tools. Visualizing the structure of complex non-planar adsorbates with atomic force microscopy (AFM) is challenging, and identifying it computationally is intractable with conventional structure search. In a fresh approach, we propose to integrate cross-disciplinary tools for a robust and automated identification of 3D adsorbate configurations. We employ Bayesian optimization with first-principles simulations for accurate and unbiased structure inference of multiple adsorbates. The corresponding AFM simulations then allow us to fingerprint adsorbate structures appearing in AFM experimental images. In the instance of bulky (1S)-camphor adsorbed on the Cu(111) surface, we found three matching AFM image contrasts, which allowed us to correlate experimental image features to distinct cases of molecular adsorption.

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Characterization of individual molecular adsorption geometries by atomic force microscopy: Cu-TCPP on rutile TiO2 (110)

The Journal of Chemical Physics ◽

10.1063/1.4929608 ◽

2015 ◽

Vol 143 (9) ◽

pp. 094202 ◽

Cited By ~ 20

Author(s):

Res Jöhr ◽

Antoine Hinaut ◽

Rémy Pawlak ◽

Ali Sadeghi ◽

Santanu Saha ◽

...

Keyword(s):

Atomic Force Microscopy ◽

Molecular Adsorption ◽

Rutile Tio2 ◽

Force Microscopy ◽

Atomic Force

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Adjusting the descriptor for a crystal structure search using Bayesian optimization

Physical Review Materials ◽

10.1103/physrevmaterials.4.033801 ◽

2020 ◽

Vol 4 (3) ◽

Author(s):

Nobuya Sato ◽

Tomoki Yamashita ◽

Tamio Oguchi ◽

Koji Hukushima ◽

Takashi Miyake

Keyword(s):

Crystal Structure ◽

Bayesian Optimization ◽

Structure Search

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A study of molecular adsorption of a cationic surfactant on complex surfaces with atomic force microscopy

The Analyst ◽

10.1039/c5an01941a ◽

2016 ◽

Vol 141 (3) ◽

pp. 1017-1026 ◽

Cited By ~ 6

Author(s):

I. Sokolov ◽

G. Zorn ◽

J. M. Nichols

Keyword(s):

Atomic Force Microscopy ◽

Cationic Surfactant ◽

Solid Surfaces ◽

Molecular Adsorption ◽

Complex Surfaces ◽

Force Microscopy ◽

Atomic Force ◽

Broad Interest

The study of molecular adsorption on solid surfaces is of broad interest.

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Measurement Method of Adhesion Strength between Inorganic Materials and Polymer by Using Atomic Force Microscopy

Journal of the Ceramic Society of Japan ◽

10.2109/jcersj.102.1102 ◽

1994 ◽

Vol 102 (1192) ◽

pp. 1102-1104 ◽

Cited By ~ 2

Author(s):

Akira KAWAI ◽

Hitoshi NAGATA ◽

Masasuke TAKATA

Keyword(s):

Atomic Force Microscopy ◽

Adhesion Strength ◽

Measurement Method ◽

Inorganic Materials ◽

Force Microscopy ◽

Atomic Force

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A Robust Identification of the Protein Standard Bands in Two-Dimensional Electrophoresis Gel Images

Electrical Control and Communication Engineering ◽

10.1515/ecce-2017-0009 ◽

2017 ◽

Vol 13 (1) ◽

pp. 63-68

Author(s):

Artūras Serackis ◽

Dalius Matuzevičius ◽

Dalius Navakauskas ◽

Eldar Šabanovič ◽

Andrius Katkevičius ◽

...

Keyword(s):

Image Features ◽

Self Organizing Map ◽

Two Dimensional ◽

Robust Identification ◽

Two Dimensional Electrophoresis ◽

Unknown Protein ◽

Analysis Workflow ◽

Dimensional Electrophoresis ◽

New Algorithms

Abstract The aim of the investigation presented in this paper was to develop a software-based assistant for the protein analysis workflow. The prior characterization of the unknown protein in two-dimensional electrophoresis gel images is performed according to the molecular weight and isoelectric point of each protein spot estimated from the gel image before further sequence analysis by mass spectrometry. The paper presents a method for automatic and robust identification of the protein standard band in a two-dimensional gel image. In addition, the method introduces the identification of the positions of the markers, prepared by using pre-selected proteins with known molecular mass. The robustness of the method was achieved by using special validation rules in the proposed original algorithms. In addition, a self-organizing map-based decision support algorithm is proposed, which takes Gabor coefficients as image features and searches for the differences in preselected vertical image bars. The experimental investigation proved the good performance of the new algorithms included into the proposed method. The detection of the protein standard markers works without modification of algorithm parameters on two-dimensional gel images obtained by using different staining and destaining procedures, which results in different average levels of intensity in the images.

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Assembly of thin Film Dielectrics by Sequential Adsorption Reactions of Unilamellar Inorganic Colloids

MRS Proceedings ◽

10.1557/proc-446-377 ◽

1996 ◽

Vol 446 ◽

Cited By ~ 1

Author(s):

Mingming Fang ◽

Chy Hyung Kim ◽

Anthony C. Sutorik ◽

David M. Kaschak ◽

Thomas E. Mallouk

Keyword(s):

Thin Film ◽

Inorganic Materials ◽

Silicon Surfaces ◽

X Ray Diffraction ◽

Alkali Cations ◽

Force Microscopy ◽

Atomic Force ◽

Sequential Adsorption ◽

Thin Film Dielectrics ◽

Layered Perovskites

AbstractSeveral layered inorganic materials (e.g. KCa2Nb3O10, KTiNbO5, and CsPb2Nb3O10) were prepared and their alkali cations exchanged by in aqueous acid. A fraction of the interlayer protons of HCa2Nb3O10 and HTiNbO5 can be replaced by tetra-n-butylammonium (TBA+), by reaction with TBA+OH. Intercalation of a sufficient amount of TBA+ causes complete exfoliation, and single, nanometer-thick sheets of these materials are thus obtained. By sequential adsorption of these two-dimensional colloidal polyanions and polymeric cations, monolayer sheets of layered perovskites can be stacked on silicon surfaces to give thin films of any desired thickness. The layered materials, the exfoliated colloids, and the thin film multilayers on silicon were studied by X-ray diffraction, transmission electronic microscopy (TEM), ellipsometry, and atomic force microscopy (AFM). The dielectric properties of the related bulk materials were measured, and are also discussed.

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Accurate Electromechanical Characterization of Soft Molecular Monolayers using Piezo Force Microscopy

10.26434/chemrxiv.8199263 ◽

2019 ◽

Author(s):

Nathaniel Miller ◽

Haley Grimm ◽

Seth Horne ◽

Geoffrey Hutchison

Keyword(s):

Lead Zirconate Titanate ◽

Mechanical Response ◽

Differential Capacitance ◽

Inorganic Materials ◽

Organic Monolayers ◽

Force Microscopy ◽

Electrostatic Component ◽

Piezo Force Microscopy ◽

Electromechanical Characterization

We report a new methodology for the electromechanical characterization of organic monolayers based on the implementation of dual AC resonance tracking piezo force microscopy (DART-PFM) combined with a sweep of an applied DC field under a fixed AC field. This experimental design allows calibration of the electrostatic component of the tip response and enables the use of low spring constant levers in the measurement. Moreover, the technique is shown to determine both positive and negative piezo response. The successful decoupling of the electrostatic component from the mechanical response will enable more quantitative electromechanical characterization of molecular and biomaterials and should generate new design principles for soft bio-compatible piezoactive materials. To highlight the applicability, our new methodology was used to successfully characterize the piezoelectric coefficient (d<sub>33</sub>) of a variety of piezoactive materials, including self-assembled monolayers made of small molecules (dodecane thiol, mercaptoundecanoic acid) or macromolecules (peptides, peptoids), as well as a variety of inorganic materials, including lead zirconate titanate [PZT], quartz, and periodically poled lithium niobate [PPLN]. Due to high differential capacitance, the soft organic monolayers demonstrated exceedingly large electromechanical response (as high as 250 pm/V) but smaller d<sub>33</sub>piezocoefficients. Finally, we find that the capacitive electrostatic response of the organic monolayers studied are significantly larger than conventional inorganic piezoelectric materials (e.g., PZT, PPLN, quartz), suggesting organic electromechanical materials applications can successfully draw from both piezo and electrostatic responses.

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USING DATA SCIENCE TO EVALUATE NANO-REINFORCED EPOXY SURFACES

10.12783/asc36/35815 ◽

2021 ◽

Author(s):

JONATHAN THEIM ◽

DANIEL P. COLE ◽

UTKARSH DUBEY ◽

ASHUTOSH SRIVASTAVA ◽

CHOWDHURY ASHRAF ◽

...

Keyword(s):

Data Science ◽

Mechanical Performance ◽

Narrow Range ◽

Bayesian Optimization ◽

Training Set ◽

Full Field ◽

Force Microscopy ◽

Particle Position ◽

Full Field Measurement ◽

Using Data

Toughened composites reinforced with nanofillers show improved mechanical performance such as increased abrasion resistance, fracture toughness, and fracture energy. The degree of these improvements is influenced by the degree of dispersion of the nanofillers which can be analyzed using force microscopy (AFM), a technique that allows for mapping the local height and elastic modulus of a surface. However, current AFM apparatuses can only measure a narrow range of moduli according to the type of tip, which complicates the full-field measurement of moduli in nanocomposites with nanosilica (~72 GPa) embedded in epoxy (0.1 – 5 GPa). Moreover, height mapping can only visualize filler particles exposed at the surface. These limitations make it challenging to determine the 3D location of nanoparticles near the surface of a composite. To overcome these limitations of conventional AFM, we used a combination of data science, micromechanics, and experimental data from AFM to locate the centroidal position of nanosilica (NS) particles relative to the surrounding epoxy surface. Using finite element simulations, a theoretical dataset of modulus values as a function of particle position relative to the epoxy surface was created as a training set. Bayesian optimization determines the “best” particle position that results in minimum error between simulated and experimental modulus contours. The algorithm returns the 3D position of the fully or partially embedded NS particle relative to the epoxy surface. The algorithm has shown the ability to partially produce simulated modulus contours that resemble the experimental modulus contours.

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Nanoelectromechanics of Inorganic and Biological Systems: From Structural Imaging to Local Functionalities

Microscopy Today ◽

10.1017/s1551929500054304 ◽

2008 ◽

Vol 16 (1) ◽

pp. 28-33

Author(s):

Brian J. Rodriguez ◽

Sergei V. Kalinin ◽

Stephen Jesse ◽

G. Thompson ◽

A. Vertegel ◽

...

Keyword(s):

Scanning Probe Microscopy ◽

Electromechanical Coupling ◽

Biological Systems ◽

Cardiac Activity ◽

Piezoresponse Force Microscopy ◽

Inorganic Materials ◽

Connective Tissues ◽

Paper Briefly ◽

Force Microscopy ◽

Complex Biosystems

Coupling between electrical and mechanical phenomena is extremely common in inorganic materials, and nearly ubiquitous in biological systems, underpinning phenomena and devices ranging from SONAR to cardiac activity and hearing. This paper briefly summarizes the Scanning Probe Microscopy (SPM) approach, referred to as Piezoresponse Force Microscopy (PFM), for probing electromechanical coupling on the nanometer scales, and delineates some existing and emerging applications to probe local structure and functionality in inorganic ferroelectrics, calcified and connective tissues, and complex biosystems based on electromechanical detection.

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