kMap.py: A Python program for simulation and data analysis in photoemission tomography
Ultra-violet photoemission spectroscopy is a widely-used experimental technique to investigate the valence electronic structure of surfaces and interfaces. When detecting the intensity of the emitted electrons not only as a function of their kinetic energy, but also depending on their emission angle...
Uloženo v:
| Vydáno v: | Computer physics communications Ročník 263; s. 107905 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.06.2021
|
| Témata: | |
| ISSN: | 0010-4655, 1879-2944 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Ultra-violet photoemission spectroscopy is a widely-used experimental technique to investigate the valence electronic structure of surfaces and interfaces. When detecting the intensity of the emitted electrons not only as a function of their kinetic energy, but also depending on their emission angle, as is done in angle-resolved photoemission spectroscopy (ARPES), extremely rich information about the electronic structure of the investigated sample can be extracted. For organic molecules adsorbed as well-oriented ultra-thin films on metallic surfaces, ARPES has evolved into a technique called photoemission tomography (PT). By approximating the final state of the photoemitted electron as a free electron, PT uses the angular dependence of the photocurrent, a so-called momentum map or k-map, and interprets it as the Fourier transform of the initial state’s molecular orbital, thereby gaining insights into the geometric and electronic structure of organic/metal interfaces.
In this contribution, we present kMap.py which is a Python program that enables the user, via a PyQt-based graphical user interface, to simulate photoemission momentum maps of molecular orbitals and to perform a one-to-one comparison between simulation and experiment. Based on the plane wave approximation for the final state, simulated momentum maps are computed numerically from a fast Fourier transform (FFT) of real space molecular orbital distributions, which are used as program input and taken from density functional calculations. The program allows the user to vary a number of simulation parameters, such as the final state kinetic energy, the molecular orientation or the polarization state of the incident light field. Moreover, also experimental photoemission data can be loaded into the program, enabling a direct visual comparison as well as an automatic optimization procedure to determine structural parameters of the molecules or weights of molecular orbitals contributions. With an increasing number of experimental groups employing photoemission tomography to study molecular adsorbate layers, we expect kMap.py to serve as a helpful analysis software to further extend the applicability of PT.
Program Title:kMap.py
CPC Library link to program files:https://doi.org/10.17632/tnrm9jcccc.1
Developer’s respository link:https://github.com/brands-d/kMap/
Code Ocean capsule:https://codeocean.com/capsule/5788845
Licensing provisions: GPLv3
Programming language: Python 3.x
Nature of problem: Photoemission tomography (PT) has evolved as a powerful experimental method to investigate the electronic and geometric structure of organic molecular films [1]. It is based on valence band angle-resolved photoemission spectroscopy and seeks an interpretation of the angular dependence of the photocurrent, a so-called momentum map, from a given initial state in terms of the spatial structure of molecular orbitals. For this purpose, PT heavily relies on a simulation platform which is capable of efficiently predicting momentum maps for a variety of organic molecules, which allows for a convenient way of treating the effect of molecular orientations, and which also accounts for other experimental parameters such as the geometrical setup and nature of the incident photon source. Thereby, PT has been used to determine molecular geometries, gain insight into the nature of the surface chemistry, unambiguously determine the orbital energy ordering in molecular homo- and heterostructures and even reconstruct the orbitals of adsorbed molecules [1–4].
Solution method:kMap.py is a Python program that enables the user, via a PyQt-based graphical user interface, to simulate photoemission momentum maps of molecular orbitals and to perform a one-to-one comparison between simulation and experiment. Based on the plane wave approximation for the final state, simulated momentum maps are computed numerically from a fast Fourier transform (FFT) of real space molecular orbital distributions [2] which are used as program input and which are usually obtained from density functional calculations. The user can vary a number of simulation parameters such as the final state kinetic energy, the molecular orientation or the polarization state of the incident light field. Moreover, also experimental photoemission data can be loaded into the program, enabling a direct visual comparison as well as an automatic optimization procedure to minimize the difference between simulated and measured momentum maps. Thereby, structural parameters of the molecules [2] and the weights of molecular orbitals to experimentally observed emission features can be determined [3].
References
[1] P. Puschnig, M. Ramsey, Photoemission tomography: Valence band photoemission as a quantitative method for investigating molecular films, in: K. Wandelt (Ed.), Encyclopedia of Interfacial Chemistry, Elsevier, Oxford, 2018, pp. 380–391.
[2] P. Puschnig, S. Berkebile, A. J. Fleming, G. Koller, K. Emtsev, T. Seyller, J. D. Riley, C. Ambrosch-Draxl, F. P. Netzer, M. G. Ramsey, Reconstruction of molecular orbital densities from photoemission data, Science 326 (2009) 702–706.
[3] P. Puschnig, E.-M. Reinisch, T. Ules, G. Koller, S. Soubatch, M. Ostler, L. Romaner, F. S. Tautz, C. Ambrosch-Draxl, M. G. Ramsey, Orbital tomography: Deconvoluting photoemission spectra of organic molecules, Phys. Rev. B 84 (2011) 235427.
[4] D. Lüftner, T. Ules, E. M. Reinisch, G. Koller, S. Soubatch, F. S. Tautz, M. G. Ramsey, P. Puschnig, Imaging the wave functions of adsorbed molecules, Proc. Nat. Acad. Sci. U. S. A. 111 (2) (2014) 605–610. |
|---|---|
| AbstractList | Ultra-violet photoemission spectroscopy is a widely-used experimental technique to investigate the valence electronic structure of surfaces and interfaces. When detecting the intensity of the emitted electrons not only as a function of their kinetic energy, but also depending on their emission angle, as is done in angle-resolved photoemission spectroscopy (ARPES), extremely rich information about the electronic structure of the investigated sample can be extracted. For organic molecules adsorbed as well-oriented ultra-thin films on metallic surfaces, ARPES has evolved into a technique called photoemission tomography (PT). By approximating the final state of the photoemitted electron as a free electron, PT uses the angular dependence of the photocurrent, a so-called momentum map or k-map, and interprets it as the Fourier transform of the initial state’s molecular orbital, thereby gaining insights into the geometric and electronic structure of organic/metal interfaces.
In this contribution, we present kMap.py which is a Python program that enables the user, via a PyQt-based graphical user interface, to simulate photoemission momentum maps of molecular orbitals and to perform a one-to-one comparison between simulation and experiment. Based on the plane wave approximation for the final state, simulated momentum maps are computed numerically from a fast Fourier transform (FFT) of real space molecular orbital distributions, which are used as program input and taken from density functional calculations. The program allows the user to vary a number of simulation parameters, such as the final state kinetic energy, the molecular orientation or the polarization state of the incident light field. Moreover, also experimental photoemission data can be loaded into the program, enabling a direct visual comparison as well as an automatic optimization procedure to determine structural parameters of the molecules or weights of molecular orbitals contributions. With an increasing number of experimental groups employing photoemission tomography to study molecular adsorbate layers, we expect kMap.py to serve as a helpful analysis software to further extend the applicability of PT.
Program Title:kMap.py
CPC Library link to program files:https://doi.org/10.17632/tnrm9jcccc.1
Developer’s respository link:https://github.com/brands-d/kMap/
Code Ocean capsule:https://codeocean.com/capsule/5788845
Licensing provisions: GPLv3
Programming language: Python 3.x
Nature of problem: Photoemission tomography (PT) has evolved as a powerful experimental method to investigate the electronic and geometric structure of organic molecular films [1]. It is based on valence band angle-resolved photoemission spectroscopy and seeks an interpretation of the angular dependence of the photocurrent, a so-called momentum map, from a given initial state in terms of the spatial structure of molecular orbitals. For this purpose, PT heavily relies on a simulation platform which is capable of efficiently predicting momentum maps for a variety of organic molecules, which allows for a convenient way of treating the effect of molecular orientations, and which also accounts for other experimental parameters such as the geometrical setup and nature of the incident photon source. Thereby, PT has been used to determine molecular geometries, gain insight into the nature of the surface chemistry, unambiguously determine the orbital energy ordering in molecular homo- and heterostructures and even reconstruct the orbitals of adsorbed molecules [1–4].
Solution method:kMap.py is a Python program that enables the user, via a PyQt-based graphical user interface, to simulate photoemission momentum maps of molecular orbitals and to perform a one-to-one comparison between simulation and experiment. Based on the plane wave approximation for the final state, simulated momentum maps are computed numerically from a fast Fourier transform (FFT) of real space molecular orbital distributions [2] which are used as program input and which are usually obtained from density functional calculations. The user can vary a number of simulation parameters such as the final state kinetic energy, the molecular orientation or the polarization state of the incident light field. Moreover, also experimental photoemission data can be loaded into the program, enabling a direct visual comparison as well as an automatic optimization procedure to minimize the difference between simulated and measured momentum maps. Thereby, structural parameters of the molecules [2] and the weights of molecular orbitals to experimentally observed emission features can be determined [3].
References
[1] P. Puschnig, M. Ramsey, Photoemission tomography: Valence band photoemission as a quantitative method for investigating molecular films, in: K. Wandelt (Ed.), Encyclopedia of Interfacial Chemistry, Elsevier, Oxford, 2018, pp. 380–391.
[2] P. Puschnig, S. Berkebile, A. J. Fleming, G. Koller, K. Emtsev, T. Seyller, J. D. Riley, C. Ambrosch-Draxl, F. P. Netzer, M. G. Ramsey, Reconstruction of molecular orbital densities from photoemission data, Science 326 (2009) 702–706.
[3] P. Puschnig, E.-M. Reinisch, T. Ules, G. Koller, S. Soubatch, M. Ostler, L. Romaner, F. S. Tautz, C. Ambrosch-Draxl, M. G. Ramsey, Orbital tomography: Deconvoluting photoemission spectra of organic molecules, Phys. Rev. B 84 (2011) 235427.
[4] D. Lüftner, T. Ules, E. M. Reinisch, G. Koller, S. Soubatch, F. S. Tautz, M. G. Ramsey, P. Puschnig, Imaging the wave functions of adsorbed molecules, Proc. Nat. Acad. Sci. U. S. A. 111 (2) (2014) 605–610. |
| ArticleNumber | 107905 |
| Author | Lüftner, Daniel Yang, Xiaosheng Tautz, F. Stefan Puschnig, Peter Brandstetter, Dominik |
| Author_xml | – sequence: 1 givenname: Dominik orcidid: 0000-0002-0434-1289 surname: Brandstetter fullname: Brandstetter, Dominik organization: Karl-Franzens-Universität Graz, Institut für Physik, NAWI Graz, 8010 Graz, Austria – sequence: 2 givenname: Xiaosheng orcidid: 0000-0002-7632-0401 surname: Yang fullname: Yang, Xiaosheng organization: Karl-Franzens-Universität Graz, Institut für Physik, NAWI Graz, 8010 Graz, Austria – sequence: 3 givenname: Daniel surname: Lüftner fullname: Lüftner, Daniel organization: Karl-Franzens-Universität Graz, Institut für Physik, NAWI Graz, 8010 Graz, Austria – sequence: 4 givenname: F. Stefan orcidid: 0000-0003-3583-2379 surname: Tautz fullname: Tautz, F. Stefan organization: Peter Grünberg Institut (PGI-3), Forschungszentrum Jülich, 52425 Jülich, Germany – sequence: 5 givenname: Peter orcidid: 0000-0002-8057-7795 surname: Puschnig fullname: Puschnig, Peter email: peter.puschnig@uni-graz.at organization: Karl-Franzens-Universität Graz, Institut für Physik, NAWI Graz, 8010 Graz, Austria |
| BookMark | eNp9kE1OwzAQhS1UJNrCAdj5Agl26tg1rKqKP6kIFsDWmjoOdUniyDZIuT0OZcWiq5l5et9o5s3QpHOdQeiSkpwSyq_2ue51XpCCpllIUp6gKV0KmRWSsQmaEkJJxnhZnqFZCHtCiBByMUXvn0_Q5_1wjVf4ZYg71-Heuw8PLa6dx8G2Xw1Em2ToKlxBhNRAMwQbsE3enYvOtDaE0RJdO6L9bjhHpzU0wVz81Tl6u7t9XT9km-f7x_Vqk2lGeMxgK7e82rIShAZhNAMBFGohOCWyThoHUzBpiOaLEmq-LIQoDQNgqUApF3MkDnu1dyF4Uytt4--90YNtFCVqjEftVYpHjfGoQzyJpP_I3tsW_HCUuTkwJr30bY1XQVvTaVNZb3RUlbNH6B8FT4EL |
| CitedBy_id | crossref_primary_10_1016_j_carbon_2023_118215 crossref_primary_10_1088_1367_2630_ad3e22 crossref_primary_10_1002_smll_202304803 crossref_primary_10_1002_adfm_202208507 crossref_primary_10_1039_D5NR00700C crossref_primary_10_1103_2k7h_h8jm crossref_primary_10_1016_j_ica_2023_121705 crossref_primary_10_1103_PhysRevB_111_165402 |
| Cites_doi | 10.1016/j.cpc.2010.04.018 10.1088/1367-2630/17/1/013033 10.1103/PhysRevLett.107.193002 10.1103/PhysRevB.51.13614 10.1038/s41586-020-2649-2 10.1016/j.tsf.2008.06.053 10.1088/1367-2630/16/10/103005 10.1016/j.elspec.2016.11.007 10.1073/pnas.1315716110 10.1103/PhysRevB.86.045417 10.1016/j.elspec.2014.06.003 10.1038/s41467-017-00402-0 10.1063/5.0018597 10.1088/1367-2630/ab0781 10.1038/s41535-019-0194-8 10.1140/epjb/e2019-100015-x 10.1103/PhysRevB.94.205144 10.1126/science.1176105 10.1103/PhysRevLett.117.183001 10.1039/C4CP04595E 10.1088/1367-2630/ab8aae 10.1038/s41467-019-13254-7 10.1016/j.susc.2013.10.020 10.1103/PhysRevB.98.085426 10.1002/ange.201904609 10.1088/1367-2630/18/9/093041 10.1103/PhysRevB.96.125402 10.1021/acs.analchem.6b00986 10.1103/PhysRevB.10.4932 10.1021/acsnano.7b02449 10.1016/j.chemphys.2005.10.023 10.1038/ncomms9287 10.1103/PhysRev.140.A1133 10.1016/0038-1098(78)90838-4 10.1016/j.elspec.2005.01.022 10.1103/PhysRevB.84.235427 10.1103/PhysRevB.10.5030 10.1002/sia.740010103 |
| ContentType | Journal Article |
| Copyright | 2021 The Author(s) |
| Copyright_xml | – notice: 2021 The Author(s) |
| DBID | 6I. AAFTH AAYXX CITATION |
| DOI | 10.1016/j.cpc.2021.107905 |
| DatabaseName | ScienceDirect Open Access Titles Elsevier:ScienceDirect:Open Access CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Physics |
| EISSN | 1879-2944 |
| ExternalDocumentID | 10_1016_j_cpc_2021_107905 S0010465521000461 |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 1B1 1RT 1~. 1~5 29F 4.4 457 4G. 5GY 5VS 6I. 7-5 71M 8P~ 9JN AACTN AAEDT AAEDW AAFTH AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARLI AAXUO AAYFN ABBOA ABFNM ABMAC ABNEU ABQEM ABQYD ABXDB ABYKQ ACDAQ ACFVG ACGFS ACLVX ACNNM ACRLP ACSBN ACZNC ADBBV ADECG ADEZE ADJOM ADMUD AEBSH AEKER AENEX AFKWA AFTJW AFZHZ AGHFR AGUBO AGYEJ AHHHB AHZHX AI. AIALX AIEXJ AIKHN AITUG AIVDX AJBFU AJOXV AJSZI ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG ATOGT AVWKF AXJTR AZFZN BBWZM BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FLBIZ FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HLZ HME HMV HVGLF HZ~ IHE IMUCA J1W KOM LG9 LZ4 M38 M41 MO0 N9A NDZJH O-L O9- OAUVE OGIMB OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SCB SDF SDG SES SEW SHN SPC SPCBC SPD SPG SSE SSK SSQ SSV SSZ T5K TN5 UPT VH1 WUQ ZMT ~02 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c406t-ab9b6db45a7ca7ec4a7a1af776109f7ca6ae249e0c635af682775e4aa475ea593 |
| ISICitedReferencesCount | 16 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000642455800003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0010-4655 |
| IngestDate | Tue Nov 18 21:58:09 EST 2025 Sat Nov 29 07:32:09 EST 2025 Fri Feb 23 02:41:29 EST 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Python-based simulation tool Angle-resolved photoemission spectroscopy Photoemission tomography |
| Language | English |
| License | This is an open access article under the CC BY license. |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c406t-ab9b6db45a7ca7ec4a7a1af776109f7ca6ae249e0c635af682775e4aa475ea593 |
| ORCID | 0000-0002-0434-1289 0000-0002-7632-0401 0000-0002-8057-7795 0000-0003-3583-2379 |
| OpenAccessLink | https://dx.doi.org/10.1016/j.cpc.2021.107905 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_cpc_2021_107905 crossref_primary_10_1016_j_cpc_2021_107905 elsevier_sciencedirect_doi_10_1016_j_cpc_2021_107905 |
| PublicationCentury | 2000 |
| PublicationDate | June 2021 2021-06-00 |
| PublicationDateYYYYMMDD | 2021-06-01 |
| PublicationDate_xml | – month: 06 year: 2021 text: June 2021 |
| PublicationDecade | 2020 |
| PublicationTitle | Computer physics communications |
| PublicationYear | 2021 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Puschnig, Reinisch, Ules, Koller, Soubatch, Ostler, Romaner, Tautz, Ambrosch-Draxl, Ramsey (b11) 2011; 84 Moser (b17) 2017; 214 Harris, Millman, van der Walt, Gommers, Virtanen, Cournapeau, Wieser, Taylor, Berg, Smith, Kern, Picus, Hoyer, van Kerkwijk, Brett, Haldane, del Rio, Wiebe, Peterson, Gerard-Marchant, Sheppard, Reddy, Weckesser, Abbasi, Gohlke, Oliphant (b33) 2020; 585 Jones, Oliphant, Peterson (b34) 2001 M. Newville, R. Otten, T. Stensitzki, A.R.J. Nelson, A. Ingargiola, D.B. Allen, M. Rawlik, Lmfit - non-linear least-squares minimization and curve-fitting for python, copyright 2020, URL Zamborlini, Lüftner, Feng, Kollmann, Puschnig, Dri, Panighel, Santo, Goldoni, Comelli, Jugovac, Feyer, Schneider (b9) 2017; 8 (b31) 2003 Hollerer, Lüftner, Hurdax, Ules, Soubatch, Tautz, Koller, Puschnig, Sterrer, Ramsey (b45) 2017; 11 Puschnig, Berkebile, Fleming, Koller, Emtsev, Seyller, Riley, Ambrosch-Draxl, Netzer, Ramsey (b4) 2009; 326 Feibelman, Eastman (b23) 1974; 10 Park, Kwon (b14) 2016; 88 Kliuiev, Latychevskaia, Osterwalder, Hengsberger, Castiglioni (b46) 2016; 18 . Graus, Metzger, Grimm, Nigge, Feyer, Schöll, Reinert (b26) 2019; 92 Egger, Kollmann, Hurdax, Lüftner, Yang, Weiß, Gottwald, Richter, Koller, Soubatch, Tautz, Puschnig, Ramsey (b6) 2019; 21 Krylov (b21) 2020; 153 Broekman, Tadich, Huwald, Riley, Leckey, Seyller, Emtsev, Ley (b35) 2005; 144–147 Kohn, Sham (b30) 1965; 140 Valiev, Bylaska, Govind, Kowalski, Straatsma, Dam, Wang, Nieplocha, Apra, Windus, de Jong (b41) 2010; 181 Dauth, Körzdörfer, Kümmel, Ziroff, Wiessner, Schöll, Reinert, Arita, Shimada (b12) 2011; 107 Sholl, Steckel (b32) 2009 Gadzuk (b3) 1974; 10 Seah, Dench (b38) 1979; 1 Koini, Haber, Werzer, Berkebile, Koller, Oehzelt, Ramsey, Resel (b44) 2008; 517 Puschnig (b43) 2020 Liu, Ikeda, Nagamatsu, Nishi, Ueno, Kera (b8) 2014; 195 Kliuiev, Zamborlini, Jugovac, Gurdal, von Arx, Waltar, Schnidrig, Alberto, Iannuzzi, Feyer, Hengsberger, Castiglioni (b10) 2019; 10 Wießner, Hauschild, Schöll, Reinert, Feyer, Winkler, Krömker (b7) 2012; 86 Wallauer, Raths, Stallberg, Münster, Brandstetter, Yang, Güdde, Puschnig, Soubatch, Kumpf, Bocquet, Tautz, Höfer (b16) 2021 Woodruff (b1) 2016 Puschnig, Ramsey (b2) 2018 Feidt, Mathias, Aeschlimann (b18) 2019; 3 Shirley, Terminello, Santoni, Himpsel (b28) 1995; 51 Dauth, Wiessner, Feyer, Schöll, Puschnig, Reinert, Kümmel (b22) 2014; 16 Dauth, Graus, Schelter, Wießner, Schöll, Reinert, Kümmel (b36) 2016; 117 Willenbockel, Lüftner, Stadtmüller, Koller, Kumpf, Puschnig, Soubatch, Ramsey, Tautz (b39) 2015; 17 Lüftner, Hurdax, Koller, Puschnig, Ramsey, Weiß, Yang, Soubatch, Tautz, Feyer, Gottwald (b37) 2017; 96 Truhlar, Hiberty, Shaik, Gordon, Danovich (b20) 2019; 131 Lüftner, Ules, Reinisch, Koller, Soubatch, Tautz, Ramsey, Puschnig (b24) 2014; 111 Feyer, Graus, Nigge, Wießner, Acres, Wiemann, Schneider, Schöll, Reinert (b13) 2014; 621 Day, Zwartsenberg, Elfimov, Damascelli (b19) 2019; 4 Larsen, Mortensen, Blomqvist, Castelli, Christensen, Dulak, Friis, Groves, Hammer, Hargus, Hermes, Jennings, Jensen, Kermode, Kitchin, Kolsbjerg, Kubal, Kaasbjerg, Lysgaard, Maronsson, Maxson, Olsen, Pastewka, Peterson, Rostgaard, Schiotz, Schütt, Strange, Thygesen, Vegge, Vilhelmsen, Walter, Zeng, Jacobsen (b42) 2017; 29 Schönauer, Weiss, Feyer, Lüftner, Stadtmüller, Schwarz, Sueyoshi, Kumpf, Puschnig, Ramsey, Tautz, Soubatch (b15) 2016; 94 Kera, Tanaka, Yamane, Yoshimura, Okudaira, Seki, Ueno (b29) 2006; 325 Kliuiev, Latychevskaia, Zamborlini, Jugovac, Metzger, Grimm, Schöll, Osterwalder, Hengsberger, Castiglioni (b47) 2018; 98 Goldberg, Fadley, Kono (b27) 1978; 28 Weiß, Lüftner, Ules, Reinisch, Kaser, Gottwald, Richter, Soubatch, Koller, Ramsey, Tautz, Puschnig (b25) 2015; 6 Bradshaw, Woodruff (b5) 2015; 17 Jansen, Keunecke, Düvel, Möller, Schmitt, Bennecke, Kappert, Steil, Luke, Steil (b48) 2020; 22 Sholl (10.1016/j.cpc.2021.107905_b32) 2009 Park (10.1016/j.cpc.2021.107905_b14) 2016; 88 Shirley (10.1016/j.cpc.2021.107905_b28) 1995; 51 Puschnig (10.1016/j.cpc.2021.107905_b2) 2018 Weiß (10.1016/j.cpc.2021.107905_b25) 2015; 6 Broekman (10.1016/j.cpc.2021.107905_b35) 2005; 144–147 10.1016/j.cpc.2021.107905_b40 Dauth (10.1016/j.cpc.2021.107905_b12) 2011; 107 (10.1016/j.cpc.2021.107905_b31) 2003 Hollerer (10.1016/j.cpc.2021.107905_b45) 2017; 11 Puschnig (10.1016/j.cpc.2021.107905_b11) 2011; 84 Schönauer (10.1016/j.cpc.2021.107905_b15) 2016; 94 Egger (10.1016/j.cpc.2021.107905_b6) 2019; 21 Puschnig (10.1016/j.cpc.2021.107905_b4) 2009; 326 Harris (10.1016/j.cpc.2021.107905_b33) 2020; 585 Day (10.1016/j.cpc.2021.107905_b19) 2019; 4 Wießner (10.1016/j.cpc.2021.107905_b7) 2012; 86 Feyer (10.1016/j.cpc.2021.107905_b13) 2014; 621 Goldberg (10.1016/j.cpc.2021.107905_b27) 1978; 28 Dauth (10.1016/j.cpc.2021.107905_b36) 2016; 117 Graus (10.1016/j.cpc.2021.107905_b26) 2019; 92 Kera (10.1016/j.cpc.2021.107905_b29) 2006; 325 Jones (10.1016/j.cpc.2021.107905_b34) 2001 Krylov (10.1016/j.cpc.2021.107905_b21) 2020; 153 Dauth (10.1016/j.cpc.2021.107905_b22) 2014; 16 Kohn (10.1016/j.cpc.2021.107905_b30) 1965; 140 Wallauer (10.1016/j.cpc.2021.107905_b16) 2021 Liu (10.1016/j.cpc.2021.107905_b8) 2014; 195 Feibelman (10.1016/j.cpc.2021.107905_b23) 1974; 10 Woodruff (10.1016/j.cpc.2021.107905_b1) 2016 Truhlar (10.1016/j.cpc.2021.107905_b20) 2019; 131 Kliuiev (10.1016/j.cpc.2021.107905_b10) 2019; 10 Larsen (10.1016/j.cpc.2021.107905_b42) 2017; 29 Valiev (10.1016/j.cpc.2021.107905_b41) 2010; 181 Zamborlini (10.1016/j.cpc.2021.107905_b9) 2017; 8 Moser (10.1016/j.cpc.2021.107905_b17) 2017; 214 Lüftner (10.1016/j.cpc.2021.107905_b24) 2014; 111 Puschnig (10.1016/j.cpc.2021.107905_b43) 2020 Kliuiev (10.1016/j.cpc.2021.107905_b47) 2018; 98 Bradshaw (10.1016/j.cpc.2021.107905_b5) 2015; 17 Koini (10.1016/j.cpc.2021.107905_b44) 2008; 517 Willenbockel (10.1016/j.cpc.2021.107905_b39) 2015; 17 Kliuiev (10.1016/j.cpc.2021.107905_b46) 2016; 18 Jansen (10.1016/j.cpc.2021.107905_b48) 2020; 22 Lüftner (10.1016/j.cpc.2021.107905_b37) 2017; 96 Feidt (10.1016/j.cpc.2021.107905_b18) 2019; 3 Seah (10.1016/j.cpc.2021.107905_b38) 1979; 1 Gadzuk (10.1016/j.cpc.2021.107905_b3) 1974; 10 |
| References_xml | – year: 2021 ident: b16 publication-title: Science – reference: M. Newville, R. Otten, T. Stensitzki, A.R.J. Nelson, A. Ingargiola, D.B. Allen, M. Rawlik, Lmfit - non-linear least-squares minimization and curve-fitting for python, copyright 2020, URL – volume: 111 start-page: 605 year: 2014 end-page: 610 ident: b24 publication-title: Proc. Natl. Acad. Sci. USA – volume: 181 start-page: 1477 year: 2010 end-page: 1489 ident: b41 publication-title: Comput. Phys. Comm. – volume: 140 start-page: A1133 year: 1965 end-page: A1138 ident: b30 publication-title: Phys. Rev. – volume: 131 start-page: 12460 year: 2019 end-page: 12466 ident: b20 publication-title: Angew. Chem. – year: 2001 ident: b34 article-title: SciPy: Open source scientific tools for Python – volume: 51 start-page: 13614 year: 1995 ident: b28 publication-title: Phys. Rev. B – start-page: 380 year: 2018 end-page: 391 ident: b2 publication-title: Encyclopedia of Interfacial Chemistry – volume: 10 start-page: 5255 year: 2019 ident: b10 publication-title: Nature Commun. – volume: 94 year: 2016 ident: b15 publication-title: Phys. Rev. B – volume: 585 start-page: 357 year: 2020 end-page: 362 ident: b33 publication-title: Nature – volume: 1 start-page: 2 year: 1979 end-page: 11 ident: b38 publication-title: Surf. Interface Anal. – volume: 4 start-page: 54 year: 2019 ident: b19 publication-title: npj Quantum Mater. – volume: 88 start-page: 4565 year: 2016 end-page: 4570 ident: b14 publication-title: Anal. Chem. – year: 2003 ident: b31 publication-title: A Primer in Density Functional Theory – volume: 6 start-page: 8287 year: 2015 ident: b25 publication-title: Nature Commun. – volume: 10 start-page: 4932 year: 1974 ident: b23 publication-title: Phys. Rev. B – volume: 214 start-page: 29 year: 2017 end-page: 52 ident: b17 publication-title: J. Electron Spectrosc. Relat. Phenom. – volume: 11 start-page: 6252 year: 2017 end-page: 6260 ident: b45 publication-title: ACS Nano – volume: 107 year: 2011 ident: b12 publication-title: Phys. Rev. Lett. – volume: 92 start-page: 80 year: 2019 ident: b26 publication-title: Eur. Phys. J. B – volume: 21 year: 2019 ident: b6 publication-title: New J. Phys. – year: 2009 ident: b32 article-title: Density Functional Theory: A Practical Introduction – volume: 3 year: 2019 ident: b18 publication-title: Phys. Rev. Mater. – volume: 517 start-page: 483 year: 2008 end-page: 487 ident: b44 publication-title: Thin Solid Films – volume: 621 start-page: 64 year: 2014 end-page: 68 ident: b13 publication-title: Surf. Sci. – volume: 86 year: 2012 ident: b7 publication-title: Phys. Rev. B – volume: 144–147 start-page: 1001 year: 2005 end-page: 1004 ident: b35 publication-title: J. Electron. Spectrosc. Relat. Phenom. – volume: 17 year: 2015 ident: b5 publication-title: New J. Phys. – volume: 117 year: 2016 ident: b36 publication-title: Phys. Rev. Lett. – volume: 98 year: 2018 ident: b47 publication-title: Phys. Rev. B – volume: 153 year: 2020 ident: b21 publication-title: J. Chem. Phys. – volume: 16 year: 2014 ident: b22 publication-title: New J. Phys. – volume: 325 start-page: 113 year: 2006 end-page: 120 ident: b29 publication-title: Chem. Phys. – volume: 8 start-page: 335 year: 2017 ident: b9 publication-title: Nature Commun. – volume: 326 start-page: 702 year: 2009 end-page: 706 ident: b4 publication-title: Science – volume: 84 year: 2011 ident: b11 publication-title: Phys. Rev. B – year: 2020 ident: b43 article-title: Organic Molecule Database: a database for molecular orbitals of – volume: 17 start-page: 1530 year: 2015 end-page: 1548 ident: b39 publication-title: Phys. Chem. Chem. Phys. – year: 2016 ident: b1 article-title: Modern Techniques of Surface Science – volume: 29 year: 2017 ident: b42 publication-title: J. Phys.: Condens. Matter – reference: . – volume: 28 start-page: 459 year: 1978 end-page: 463 ident: b27 publication-title: Solid State Commun. – volume: 96 year: 2017 ident: b37 publication-title: Phys. Rev. B – volume: 195 start-page: 287 year: 2014 end-page: 292 ident: b8 publication-title: J. Electron Spectrosc. Relat. Phenom. – volume: 18 year: 2016 ident: b46 publication-title: New J. Phys. – volume: 10 start-page: 5030 year: 1974 end-page: 5044 ident: b3 publication-title: Phys. Rev. B – volume: 22 year: 2020 ident: b48 publication-title: New J. Phys. – year: 2009 ident: 10.1016/j.cpc.2021.107905_b32 – volume: 181 start-page: 1477 issue: 9 year: 2010 ident: 10.1016/j.cpc.2021.107905_b41 publication-title: Comput. Phys. Comm. doi: 10.1016/j.cpc.2010.04.018 – volume: 17 year: 2015 ident: 10.1016/j.cpc.2021.107905_b5 publication-title: New J. Phys. doi: 10.1088/1367-2630/17/1/013033 – volume: 107 year: 2011 ident: 10.1016/j.cpc.2021.107905_b12 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.107.193002 – volume: 51 start-page: 13614 year: 1995 ident: 10.1016/j.cpc.2021.107905_b28 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.51.13614 – volume: 585 start-page: 357 issue: 7825 year: 2020 ident: 10.1016/j.cpc.2021.107905_b33 publication-title: Nature doi: 10.1038/s41586-020-2649-2 – volume: 3 year: 2019 ident: 10.1016/j.cpc.2021.107905_b18 publication-title: Phys. Rev. Mater. – volume: 517 start-page: 483 year: 2008 ident: 10.1016/j.cpc.2021.107905_b44 publication-title: Thin Solid Films doi: 10.1016/j.tsf.2008.06.053 – volume: 16 year: 2014 ident: 10.1016/j.cpc.2021.107905_b22 publication-title: New J. Phys. doi: 10.1088/1367-2630/16/10/103005 – volume: 214 start-page: 29 year: 2017 ident: 10.1016/j.cpc.2021.107905_b17 publication-title: J. Electron Spectrosc. Relat. Phenom. doi: 10.1016/j.elspec.2016.11.007 – volume: 111 start-page: 605 issue: 2 year: 2014 ident: 10.1016/j.cpc.2021.107905_b24 publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.1315716110 – ident: 10.1016/j.cpc.2021.107905_b40 – volume: 86 year: 2012 ident: 10.1016/j.cpc.2021.107905_b7 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.86.045417 – volume: 195 start-page: 287 year: 2014 ident: 10.1016/j.cpc.2021.107905_b8 publication-title: J. Electron Spectrosc. Relat. Phenom. doi: 10.1016/j.elspec.2014.06.003 – volume: 8 start-page: 335 year: 2017 ident: 10.1016/j.cpc.2021.107905_b9 publication-title: Nature Commun. doi: 10.1038/s41467-017-00402-0 – volume: 153 year: 2020 ident: 10.1016/j.cpc.2021.107905_b21 publication-title: J. Chem. Phys. doi: 10.1063/5.0018597 – year: 2003 ident: 10.1016/j.cpc.2021.107905_b31 – volume: 21 year: 2019 ident: 10.1016/j.cpc.2021.107905_b6 publication-title: New J. Phys. doi: 10.1088/1367-2630/ab0781 – year: 2021 ident: 10.1016/j.cpc.2021.107905_b16 publication-title: Science – volume: 29 issue: 27 year: 2017 ident: 10.1016/j.cpc.2021.107905_b42 publication-title: J. Phys.: Condens. Matter – volume: 4 start-page: 54 year: 2019 ident: 10.1016/j.cpc.2021.107905_b19 publication-title: npj Quantum Mater. doi: 10.1038/s41535-019-0194-8 – volume: 92 start-page: 80 year: 2019 ident: 10.1016/j.cpc.2021.107905_b26 publication-title: Eur. Phys. J. B doi: 10.1140/epjb/e2019-100015-x – year: 2001 ident: 10.1016/j.cpc.2021.107905_b34 – volume: 94 year: 2016 ident: 10.1016/j.cpc.2021.107905_b15 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.94.205144 – volume: 326 start-page: 702 year: 2009 ident: 10.1016/j.cpc.2021.107905_b4 publication-title: Science doi: 10.1126/science.1176105 – volume: 117 year: 2016 ident: 10.1016/j.cpc.2021.107905_b36 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.117.183001 – volume: 17 start-page: 1530 year: 2015 ident: 10.1016/j.cpc.2021.107905_b39 publication-title: Phys. Chem. Chem. Phys. doi: 10.1039/C4CP04595E – volume: 22 year: 2020 ident: 10.1016/j.cpc.2021.107905_b48 publication-title: New J. Phys. doi: 10.1088/1367-2630/ab8aae – volume: 10 start-page: 5255 year: 2019 ident: 10.1016/j.cpc.2021.107905_b10 publication-title: Nature Commun. doi: 10.1038/s41467-019-13254-7 – volume: 621 start-page: 64 issue: 0 year: 2014 ident: 10.1016/j.cpc.2021.107905_b13 publication-title: Surf. Sci. doi: 10.1016/j.susc.2013.10.020 – volume: 98 year: 2018 ident: 10.1016/j.cpc.2021.107905_b47 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.98.085426 – volume: 131 start-page: 12460 issue: 36 year: 2019 ident: 10.1016/j.cpc.2021.107905_b20 publication-title: Angew. Chem. doi: 10.1002/ange.201904609 – volume: 18 year: 2016 ident: 10.1016/j.cpc.2021.107905_b46 publication-title: New J. Phys. doi: 10.1088/1367-2630/18/9/093041 – volume: 96 year: 2017 ident: 10.1016/j.cpc.2021.107905_b37 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.96.125402 – volume: 88 start-page: 4565 issue: 0 year: 2016 ident: 10.1016/j.cpc.2021.107905_b14 publication-title: Anal. Chem. doi: 10.1021/acs.analchem.6b00986 – year: 2016 ident: 10.1016/j.cpc.2021.107905_b1 – volume: 10 start-page: 4932 year: 1974 ident: 10.1016/j.cpc.2021.107905_b23 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.10.4932 – year: 2020 ident: 10.1016/j.cpc.2021.107905_b43 – volume: 11 start-page: 6252 year: 2017 ident: 10.1016/j.cpc.2021.107905_b45 publication-title: ACS Nano doi: 10.1021/acsnano.7b02449 – start-page: 380 year: 2018 ident: 10.1016/j.cpc.2021.107905_b2 – volume: 325 start-page: 113 year: 2006 ident: 10.1016/j.cpc.2021.107905_b29 publication-title: Chem. Phys. doi: 10.1016/j.chemphys.2005.10.023 – volume: 6 start-page: 8287 year: 2015 ident: 10.1016/j.cpc.2021.107905_b25 publication-title: Nature Commun. doi: 10.1038/ncomms9287 – volume: 140 start-page: A1133 issue: 4A year: 1965 ident: 10.1016/j.cpc.2021.107905_b30 publication-title: Phys. Rev. doi: 10.1103/PhysRev.140.A1133 – volume: 28 start-page: 459 year: 1978 ident: 10.1016/j.cpc.2021.107905_b27 publication-title: Solid State Commun. doi: 10.1016/0038-1098(78)90838-4 – volume: 144–147 start-page: 1001 year: 2005 ident: 10.1016/j.cpc.2021.107905_b35 publication-title: J. Electron. Spectrosc. Relat. Phenom. doi: 10.1016/j.elspec.2005.01.022 – volume: 84 year: 2011 ident: 10.1016/j.cpc.2021.107905_b11 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.84.235427 – volume: 10 start-page: 5030 year: 1974 ident: 10.1016/j.cpc.2021.107905_b3 publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.10.5030 – volume: 1 start-page: 2 year: 1979 ident: 10.1016/j.cpc.2021.107905_b38 publication-title: Surf. Interface Anal. doi: 10.1002/sia.740010103 |
| SSID | ssj0007793 |
| Score | 2.4577916 |
| Snippet | Ultra-violet photoemission spectroscopy is a widely-used experimental technique to investigate the valence electronic structure of surfaces and interfaces.... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 107905 |
| SubjectTerms | Angle-resolved photoemission spectroscopy Photoemission tomography Python-based simulation tool |
| Title | kMap.py: A Python program for simulation and data analysis in photoemission tomography |
| URI | https://dx.doi.org/10.1016/j.cpc.2021.107905 |
| Volume | 263 |
| WOSCitedRecordID | wos000642455800003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-2944 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0007793 issn: 0010-4655 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELaWFiQuiKcoL_nACZRVNi_H3JaqFSBR7aGg5RQ5Xlvd0maj3bRqfwT_mZl4nIRCET1wSSLLcaLMl_F4PPMNY69zrWKtkygA6UYBIGQRlKFeBGGqdKKsMtKGbbEJcXCQz-dyNhr98Lkw5yeiqvKLC1n_V1FDGwgbU2dvIO5uUGiAaxA6HEHscPwnwX__rOpxfelSzmeXyA3go7DamMLN8pRKdrUbBxgiChdETYIx5UerZoVV4NCPBqbp6ZDU2nMaUC0IcoxsMDK9zzPpPe9rTCRu2owhZ60jk0mXG_SNfNXzpVptjgzNoRgdhNv373dtQ9k4Lg--dzKctUVo3-6PMUjNEr7JdRENQqy8OoZJAAnchuo4IoXnFCqsTmWbl_27rnduh-OxrpGKMpqM-76_8mpfme-6KEQf4HZcwBAFDlG4IW6x7UikEpTk9vTj3vxTN7ULQSzO9N5-m7wNGLzyHn82dAbGy-F9do9WHXzq0PKAjUz1kN2ZOeE9Yl8JM-_4lDvEcEIMB8TwHjEc5MkRMdwjhi-h7xAxvEfMY_Zlf-9w90NABTcCDXZdE6hSltmiTFIltBIGflahJsoKgZz8FtoyZWC5bkINZqqyWR4JkZpEqQROKpXxE7ZVrSrzlPFYmRgWF5mMJiaxmSoneVlKJAOyuozzcIeF_usUmtjosSjKSXGtVHbYm-6W2lGx_K1z4j95QbaksxELgM_1tz27yTOes7s9ql-wrWZ9Zl6y2_q8WW7Wrwg7PwF59ZZh |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=kMap.py%3A+A+Python+program+for+simulation+and+data+analysis+in+photoemission+tomography&rft.jtitle=Computer+physics+communications&rft.au=Brandstetter%2C+Dominik&rft.au=Yang%2C+Xiaosheng&rft.au=L%C3%BCftner%2C+Daniel&rft.au=Tautz%2C+F.+Stefan&rft.date=2021-06-01&rft.issn=0010-4655&rft.volume=263&rft.spage=107905&rft_id=info:doi/10.1016%2Fj.cpc.2021.107905&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_cpc_2021_107905 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0010-4655&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0010-4655&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0010-4655&client=summon |