Deconvolution of concentration depth profiles from angle resolved x‐ray photoelectron spectroscopy data

T. D. Bussing; P. H. Holloway

doi:10.1116/1.572910

Deconvolution of concentration depth profiles from angle resolved x‐ray photoelectron spectroscopy data

Journal of Vacuum Science & Technology A Vacuum Surfaces and Films ◽

10.1116/1.572910 ◽

1985 ◽

Vol 3 (5) ◽

pp. 1973-1981 ◽

Cited By ~ 70

Author(s):

T. D. Bussing ◽

P. H. Holloway

Keyword(s):

Photoelectron Spectroscopy ◽

Spectroscopy Data ◽

X Ray ◽

Depth Profiles ◽

Concentration Depth Profiles

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Molar concentration–depth profiles at the solution surface of a cationic surfactant reconstructed with angle resolved X-ray photoelectron spectroscopy

Applied Surface Science ◽

10.1016/j.apsusc.2010.09.091 ◽

2011 ◽

Vol 257 (6) ◽

pp. 2291-2297 ◽

Cited By ~ 7

Author(s):

Chuangye Wang ◽

Harald Morgner

Keyword(s):

Cationic Surfactant ◽

Photoelectron Spectroscopy ◽

Molar Concentration ◽

X Ray ◽

Depth Profiles ◽

Solution Surface ◽

Concentration Depth Profiles

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Nondestructive Surface Depth Profiles from Angle-Resolved X-ray Photoelectron Spectroscopy Data Using the Maximum Entropy Method. I. A New Protocol

The Journal of Physical Chemistry C ◽

10.1021/jp906326m ◽

2009 ◽

Vol 113 (51) ◽

pp. 21328-21337 ◽

Cited By ~ 17

Author(s):

M. Andrea Scorciapino ◽

Gabriele Navarra ◽

Bernhard Elsener ◽

Antonella Rossi

Keyword(s):

Maximum Entropy ◽

Photoelectron Spectroscopy ◽

Maximum Entropy Method ◽

Entropy Method ◽

Spectroscopy Data ◽

X Ray ◽

Depth Profiles

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Measuring concentration depth profiles at liquid surfaces: Comparing angle resolved X-ray photoelectron spectroscopy and neutral impact collision scattering spectroscopy

Surface Science ◽

10.1016/j.susc.2011.01.035 ◽

2011 ◽

Vol 605 (9-10) ◽

pp. 889-897 ◽

Cited By ~ 15

Author(s):

Chuangye Wang ◽

Gunther G. Andersson

Keyword(s):

Photoelectron Spectroscopy ◽

X Ray ◽

Depth Profiles ◽

Concentration Depth Profiles ◽

Liquid Surfaces

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Surface compositions of 9XC and R6M5 tool steels after laser pulse irradiation according to X-ray photoelectron spectroscopy data

Journal of Surface Investigation X-ray Synchrotron and Neutron Techniques ◽

10.1134/s1027451011050089 ◽

2011 ◽

Vol 5 (3) ◽

pp. 431-439 ◽

Cited By ~ 2

Author(s):

A. T. Kozakov ◽

S. I. Yares’ko ◽

V. I. Kolesnikov ◽

A. V. Sidashov

Keyword(s):

Laser Pulse ◽

Photoelectron Spectroscopy ◽

Spectroscopy Data ◽

Tool Steels ◽

Pulse Irradiation ◽

X Ray

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Chemical bonding and valence state of 3d-metal ions in Ni 1−x Co x Cr 2 O 4 spinels from X-ray diffraction and X-ray photoelectron spectroscopy data

Journal of Electron Spectroscopy and Related Phenomena ◽

10.1016/j.elspec.2014.07.010 ◽

2014 ◽

Vol 195 ◽

pp. 208-219 ◽

Cited By ~ 10

Author(s):

A.G. Kochur ◽

A.T. Kozakov ◽

K.A. Googlev ◽

A.S. Mikheykin ◽

V.I. Torgashev ◽

...

Keyword(s):

Metal Ions ◽

Chemical Bonding ◽

Photoelectron Spectroscopy ◽

Valence State ◽

Spectroscopy Data ◽

X Ray Diffraction ◽

X Ray

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SIMULATION OF THE ELECTRONIC STRUCTURE OF C(C2H)4 AND Ge(C2H)4 BY THE DENSITY FUNCTIONAL THEORY USING X-RAY PHOTOELECTRON SPECTROSCOPY DATA

Journal of Structural Chemistry ◽

10.1134/s0022476621110044 ◽

2021 ◽

Vol 62 (11) ◽

pp. 1684-1693

Author(s):

M. M. Tatevosyan ◽

T. N. Zhukova ◽

V. G. Vlasenko

Keyword(s):

Density Functional Theory ◽

Electronic Structure ◽

Photoelectron Spectroscopy ◽

Density Functional ◽

Spectroscopy Data ◽

Functional Theory ◽

X Ray ◽

The Density Functional Theory

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Deep neural network for x-ray photoelectron spectroscopy data analysis

Machine Learning: Science and Technology ◽

10.1088/2632-2153/ab5da6 ◽

2020 ◽

Vol 1 (1) ◽

pp. 015008 ◽

Cited By ~ 2

Author(s):

G Drera ◽

C M Kropf ◽

L Sangaletti

Keyword(s):

Neural Network ◽

Data Analysis ◽

Photoelectron Spectroscopy ◽

Deep Neural Network ◽

Spectroscopy Data ◽

X Ray

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Study of surface oxidation of polycrystalline rhodium using multivariate analysis based on combined optical microscopy and X-ray photoelectron spectroscopy data

Applied Surface Science ◽

10.1016/j.apsusc.2020.146617 ◽

2020 ◽

Vol 526 ◽

pp. 146617

Author(s):

G. Balcerowska-Czerniak ◽

M. Trzcinski ◽

M. Naparty ◽

A. Bukaluk

Keyword(s):

Multivariate Analysis ◽

Optical Microscopy ◽

Photoelectron Spectroscopy ◽

Surface Oxidation ◽

Spectroscopy Data ◽

X Ray

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Montecarlo Simulation and HAXPES Analysis of Organosilane Segregation in Titania Xerogel Films; Towards a Generic Surface Chemofunctionalization Process

Surfaces ◽

10.3390/surfaces3030026 ◽

2020 ◽

Vol 3 (3) ◽

pp. 352-365

Author(s):

Javier Mateo Moreno ◽

Rodrigo Calvo Membibre ◽

Sergio Pinilla Yanguas ◽

Juan Rubio Zuazo ◽

Miguel Manso Siván

Keyword(s):

Photoelectron Spectroscopy ◽

Surface Segregation ◽

Titanium Isopropoxide ◽

Condensation Process ◽

X Ray ◽

Depth Profiles ◽

Partial Charges ◽

Xerogel Films ◽

Non Destructive

The formation of xerogels implies a sequence of hydrolysis and condensation reactions, which are intricate to analyze in heteromolecular sols. We analyze by probabilistic Montecarlo methods the development of hybrid organosilane–titania xerogels and illustrate how partial charges of the reacting molecules can help estimating relative probabilities for the condensation of the molecules. Since the condensation rate of Ti alkoxides is much higher than the corresponding rate of Si alkoxides (especially if bearing a non-hydrolizable group), by imposing a fast condensation process in agreement with low pH kinetics, the process leads to a surface segregation of the organosilane. The simulation results are compared with results of characterization of thin condensates of two different organosilanes within a titanium–isopropoxide matrix. Non-destructive in-depth profiles were obtained by hard x-ray photoelectron spectroscopy, which can resolve through estimation of Si and specific moieties of the organosilane molecules the progress of the condensation. These results are relevant for the generalization of chemo-functionalization processes by kinetic demixing of organosilanes, which have myriad applications in biomedicine and biotechnology.

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