cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/decg-e904
title: mes_aps

description: The worker allocation problem in the aircraft final assembly line was solved by several multi-objective evolutionary algorithms. The data set cannot be published to the public due to involving military secrets. However, in order to validate it, you can download the oracle dataset “mes_aps.rar” which contains (6+1)×30=210 independent experiments in table “assembly_algorithm” and all evaluated individuals in table “assembly_result”.
DOI: 10.5517/ccdc.csd.cc25hqw9
title: CCDC 2011121: Experimental Crystal Structure Determination

description: Related Article: Shanshan Qiao, Peng-Cheng Qian, Fan Chen, Jiang Cheng|2020|Org.Biomol.Chem.|18|7086|doi:10.1039/D0OB01438A
DOI: 10.5517/ccdc.csd.cc25hzj6
title: CCDC 2011358: Experimental Crystal Structure Determination

description: Related Article: Xiang Li, Yu-Han Liu, Guang-Zhou Zhu, Feng Gao|2020|New J.Chem.|44|16959|doi:10.1039/D0NJ04033A
DOI: 10.5517/ccdc.csd.cc25hzk7
title: CCDC 2011359: Experimental Crystal Structure Determination

description: Related Article: Xiang Li, Yu-Han Liu, Guang-Zhou Zhu, Feng Gao|2020|New J.Chem.|44|16959|doi:10.1039/D0NJ04033A
DOI: 10.5281/zenodo.4099125
title: Halal Food Product Dataset

description: The turtle of Linked Open Data Halal dataset http://halal.addi.is.its.ac.id/ Funded by Institut Teknologi Sepuluh Nopember number 1168/PKS/ITS/2019
DOI: 10.5281/zenodo.4099124
title: Halal Food Product Dataset

description: The turtle of Linked Open Data Halal dataset http://halal.addi.is.its.ac.id/ Funded by Institut Teknologi Sepuluh Nopember number 1168/PKS/ITS/2019
DOI: 10.6084/m9.figshare.13106852
title: R0309_20191111a_videos

description: Rat 0309, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13106855
title: R0190_20170914a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5517/ccdc.csd.cc25jjs1
title: CCDC 2011893: Experimental Crystal Structure Determination

description: Related Article: Abhisek Banerjee, Shouvik Chattopadhyay|2021|Inorg.Chim.Acta|515|120044|doi:10.1016/j.ica.2020.120044
DOI: 10.5517/ccdc.csd.cc25jnv7
title: CCDC 2012019: Experimental Crystal Structure Determination

description: Related Article: Axel Straube, Peter Coburger, Luis Dütsch, Evamarie Hey-Hawkins|2020|Chemical Science|11|10657|doi:10.1039/D0SC03604H
DOI: 10.5517/ccdc.csd.cc25jrq6
title: CCDC 2012108: Experimental Crystal Structure Determination

description: Related Article: Jonathan A. Kephart, Catherine G. Romero, Chun-Chih Tseng, Kevin J. Anderton, Matthew Yankowitz, Werner Kaminsky, Alexandra Velian|2020|Chemical Science|11|10744|doi:10.1039/D0SC03506H
DOI: 10.5517/ccdc.csd.cc25jrr7
title: CCDC 2012109: Experimental Crystal Structure Determination

description: Related Article: Jonathan A. Kephart, Catherine G. Romero, Chun-Chih Tseng, Kevin J. Anderton, Matthew Yankowitz, Werner Kaminsky, Alexandra Velian|2020|Chemical Science|11|10744|doi:10.1039/D0SC03506H
DOI: 10.5517/ccdc.csd.cc25jrs8
title: CCDC 2012110: Experimental Crystal Structure Determination

description: Related Article: Jonathan A. Kephart, Catherine G. Romero, Chun-Chih Tseng, Kevin J. Anderton, Matthew Yankowitz, Werner Kaminsky, Alexandra Velian|2020|Chemical Science|11|10744|doi:10.1039/D0SC03506H
DOI: 10.5517/ccdc.csd.cc25jrt9
title: CCDC 2012111: Experimental Crystal Structure Determination

description: Related Article: Jonathan A. Kephart, Catherine G. Romero, Chun-Chih Tseng, Kevin J. Anderton, Matthew Yankowitz, Werner Kaminsky, Alexandra Velian|2020|Chemical Science|11|10744|doi:10.1039/D0SC03506H
DOI: 10.5517/ccdc.csd.cc25jrvb
title: CCDC 2012112: Experimental Crystal Structure Determination

description: Related Article: Jonathan A. Kephart, Catherine G. Romero, Chun-Chih Tseng, Kevin J. Anderton, Matthew Yankowitz, Werner Kaminsky, Alexandra Velian|2020|Chemical Science|11|10744|doi:10.1039/D0SC03506H
DOI: 10.5517/ccdc.csd.cc25jyxl
title: CCDC 2012300: Experimental Crystal Structure Determination

description: Related Article: Chadlia Mchiri, Abdelkader Ouakouak, Soumaya Nasri, Abdesslem Jedidi, Ilona Turowska-Tyrk, Samir Acherar, Céline Frochot, Thierry Roisnel, Habib Nasri|2021|Inorg.Chim.Acta|515|120046|doi:10.1016/j.ica.2020.120046
DOI: 10.17632/sj8vtpvk5j.3
title: Data for: Antiulcerogenic effects of Celosia trigyna plant extracts on ethanol-induced gastric ulcer in adult Wistar rats

description: NMR data for isolated compounds.
DOI: 10.5281/zenodo.4099156
title: U2- and U12-type intron classifications for Physarum polycephalum in BED format

description: A BED file containing intron information for <em>Physarum polycephalum</em> introns classified as U2- or U12-type by intronIC. This data is associated with the following manuscript: https://doi.org/10.1101/2020.10.12.336362; the genome and annotation file used to identify the introns are available here: https://doi.org/10.5281/zenodo.4086119. The file columns are: 1. Genome FASTA record name (scaffold) 2. Intron start coordinate (0-indexed) 3. Intron end coordinate (1-indexed) 4. Intron label from intronIC 5. U12-type probability score (0-100); introns with scores &gt; 95 were considered U12-type in the manuscript 6. Strand
DOI: 10.5281/zenodo.4099155
title: U2- and U12-type intron classifications for Physarum polycephalum in BED format

description: A BED file containing intron information for <em>Physarum polycephalum</em> introns classified as U2- or U12-type by intronIC. This data is associated with the following manuscript: https://doi.org/10.1101/2020.10.12.336362; the genome and annotation file used to identify the introns are available here: https://doi.org/10.5281/zenodo.4086119. The file columns are: 1. Genome FASTA record name (scaffold) 2. Intron start coordinate (0-indexed) 3. Intron end coordinate (1-indexed) 4. Intron label from intronIC 5. U12-type probability score (0-100); introns with scores &gt; 95 were considered U12-type in the manuscript 6. Strand
DOI: 10.5281/zenodo.4039422
title: "Replication package for: Intergenerational mobility in the very long run: Florence 1427-2011"

description: Replication package for the results contained in the paper by Barone, G. and Mocetti, S. titled "Intergenerational mobility in the very long run: Florence 1427-2011"
DOI: 10.5281/zenodo.3950508
title: "Replication package for: Intergenerational mobility in the very long run: Florence 1427-2011"

description: Replication package for the results contained in the paper by Barone, G. and Mocetti, S. titled "Intergenerational mobility in the very long run: Florence 1427-2011"
DOI: 10.17632/fg86r64rrb.1
title: Data for: Chromosomal segments may explain the antibody response cooperation for the canine leishmaniasis pathogenesis

description: Supporting phenotypes and genotypes data
DOI: 10.5281/zenodo.4099136
title: An open dataset of butterflies species of south India

description: An open dataset of butterflies species of south India icluding Scientic Name, English Name & Malayalam Name. This Dataset is growing and prepared for a internal project of Kerala Biodiversity Monitoring Network. This dataset is made available under the Open Data Commons Attribution License v1.0 (ODC-BY 1.0).
DOI: 10.5281/zenodo.4077359
title: An open dataset of butterflies species of south India

description: An open dataset of butterflies species of south India icluding Scientic Name, English Name & Malayalam Name. This Dataset is growing and prepared for a internal project of Kerala Biodiversity Monitoring Network. This dataset is made available under the Open Data Commons Attribution License v1.0 (ODC-BY 1.0).
DOI: 10.6084/m9.figshare.13106852.v1
title: R0309_20191111a_videos

description: Rat 0309, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13106855.v1
title: R0190_20170914a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13107215
title: FOP-ME data

description: Data and code
DOI: 10.6084/m9.figshare.13107215.v1
title: FOP-ME data

description: Data and code
DOI: 10.25345/c5k787
title: MassIVE MSV000086318 - GNPS_Synthettic cannabinoids DDA
title: Untargeted approach data dependent analysis synthetic cannabinoids
DOI: 10.21227/t8fm-jr51
title: iSignDB: A biometric signature database created using smartphone

description: iSignDB: A biometric signature database created using smartphoneSuraiya Jabin, Sumaiya Ahmad, Sarthak Mishra, and Farhana Javed ZareenDepartment of Computer Science, Jamia Millia Islamia, New Delhi-110025, IndiaIt's a database of biometric signatures recorded using sensors present in a smartphone. ​The dataset iSignDB is created to implement a novel anti-spoof biometric signature authentication for smartphone users.We named it iSignDB as we collected it using a licensed MathWorks cloud account and withtwodevicesiPhone 7 Plus and Redmi Note 7 for capturing dynamic signatures.A total of 48 subjects volunteered for data collection out of which we identified 32 users as genuine signature contributors and 16 users as fake signature contributors with skilled forgery.Data was collected in 3 different sessions separated by at least 20 days in order to capture the emotional intelligence of users.During each session, one pair of subjects, out of which one subject contributed 10 original signatures and the other contributed 5 fake signatures.For obtaining a fake signature, a subject was allowed to practice copying not only the signature image of a genuine user but also the behaviourism (e.g. number of touchpoints, style of finger movement while signing, etc.) while genuine signer signs on the touch screen of a smartphone.A total of 30 genuine and 15 fake samples were collected for each of 32 users.One sign of a user contains a sensor log captured using sensors present in the smartphone: Accelerometer, Gyroscope, Magnetometer, and GPS, etc along with images of signature as obtained by performing a sign on the touch screen of the device.Currently, we put biometric sign database of one user only in this repository, but as soon as this work is published, we will make the full database of 32 users available with terms and conditions.We successfully trained 32 BiLSTM models on dynamic signature dataset created with EER of 3.35% which is a significant improvement over all such models in existing literature (HMOG, and eBioSignDS 2).We provide Matlab code (compatible with MATLAB 2020a licensed version) for training, testing, and calculating EER in this repository (https://github.com/suraiyajabin/iSignDB2020).iSignDB will be made available to other researchers only after signing its "Term of use" agreement.Nomenclature for files in the dataset iSignDB: (each sign with 5 sensor logs corresponding to Acceleration, Angular Velocity, Magnetic Field, Orientation, and Position, and image of signature u01_s3_r010_AngVel.txt : means a signature of user 1, on session 3, real signature, 10th sample’s Angular velocity sensor log u01_s1_f02_MagField.txt : means a signature of user 1, on session 1, fake signature, 2nd sample’s magnetic field sensor log u01_s1_r01_im.png : image of the genuine signature of user 1, captured on session 1, sample 1
DOI: 10.21227/me58-g702
title: iSignDB: A biometric signature database created using smartphone

description: iSignDB: A biometric signature database created using smartphoneSuraiya Jabin, Sumaiya Ahmad, Sarthak Mishra, and Farhana Javed ZareenDepartment of Computer Science, Jamia Millia Islamia, New Delhi-110025, IndiaIt's a database of biometric signatures recorded using sensors present in a smartphone. ​The dataset iSignDB is created to implement a novel anti-spoof biometric signature authentication for smartphone users.We named it iSignDB as we collected it using a licensed MathWorks cloud account and withtwodevicesiPhone 7 Plus and Redmi Note 7 for capturing dynamic signatures.A total of 48 subjects volunteered for data collection out of which we identified 32 users as genuine signature contributors and 16 users as fake signature contributors with skilled forgery.Data was collected in 3 different sessions separated by at least 20 days in order to capture the emotional intelligence of users.During each session, one pair of subjects, out of which one subject contributed 10 original signatures and the other contributed 5 fake signatures.For obtaining a fake signature, a subject was allowed to practice copying not only the signature image of a genuine user but also the behaviourism (e.g. number of touchpoints, style of finger movement while signing, etc.) while genuine signer signs on the touch screen of a smartphone.A total of 30 genuine and 15 fake samples were collected for each of 32 users.One sign of a user contains a sensor log captured using sensors present in the smartphone: Accelerometer, Gyroscope, Magnetometer, and GPS, etc along with images of signature as obtained by performing a sign on the touch screen of the device.Currently, we put biometric sign database of one user only in this repository, but as soon as this work is published, we will make the full database of 32 users available with terms and conditions.We successfully trained 32 BiLSTM models on dynamic signature dataset created with EER of 3.35% which is a significant improvement over all such models in existing literature (HMOG, and eBioSignDS 2).We provide Matlab code (compatible with MATLAB 2020a licensed version) for training, testing, and calculating EER in this repository (https://github.com/suraiyajabin/iSignDB2020).iSignDB will be made available to other researchers only after signing its "Term of use" agreement.Nomenclature for files in the dataset iSignDB: (each sign with 5 sensor logs corresponding to Acceleration, Angular Velocity, Magnetic Field, Orientation, and Position, and image of signature u01_s3_r010_AngVel.txt : means a signature of user 1, on session 3, real signature, 10th sample’s Angular velocity sensor log u01_s1_f02_MagField.txt : means a signature of user 1, on session 1, fake signature, 2nd sample’s magnetic field sensor log u01_s1_r01_im.png : image of the genuine signature of user 1, captured on session 1, sample 1
DOI: 10.34740/kaggle/dsv/1567531
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.4099564
title: Nikas_et_al_2020_ORIJ_DATASET

description: This dataset contains the underlying data for the following publication: <strong>Nikas, A., Fountoulakis, A., Forouli, A., & Doukas, H. (2020). A robust augmented ε-constraint method (AUGMECON-R) for finding exact solutions of multi-objective linear programming problems. Operational Research, in press, 10.1007/s12351-020-00574-6.</strong> Full details of methods used to create the dataset and provided within this publication.
DOI: 10.5281/zenodo.4099563
title: Nikas_et_al_2020_ORIJ_DATASET

description: This dataset contains the underlying data for the following publication: <strong>Nikas, A., Fountoulakis, A., Forouli, A., & Doukas, H. (2020). A robust augmented ε-constraint method (AUGMECON-R) for finding exact solutions of multi-objective linear programming problems. Operational Research, in press, 10.1007/s12351-020-00574-6.</strong> Full details of methods used to create the dataset and provided within this publication.
DOI: 10.34740/kaggle/dsv/1230802
title: COVID-19 Chest X-Rays for Lung Severity Scoring
DOI: 10.17632/r6vkrdvjdh.1
title: Data for: Universal Branch Model for the Solution of Optimal Power Flows in Hybrid AC/DC Grids
DOI: 10.5281/zenodo.4099682
title: van_vliet_et_al_2020_EIST_DATASET

description: This dataset contains the underlying data for the following publication: <strong>van Vliet, O., Hanger, S., Nikas, A., Spijker, E., Carlsen, H., Doukas, H., & Lieu, J. (2020). The importance of stakeholders in scoping risk assessments—Lessons from low-carbon transitions. Environmental Innovation and Societal Transitions 35, 400-413. https://doi.org/10.1016/j.eist.2020.04.001.</strong> Full details of methods used to create the dataset and provided within this publication.
DOI: 10.5281/zenodo.4099681
title: van_vliet_et_al_2020_EIST_DATASET

description: This dataset contains the underlying data for the following publication: <strong>van Vliet, O., Hanger, S., Nikas, A., Spijker, E., Carlsen, H., Doukas, H., & Lieu, J. (2020). The importance of stakeholders in scoping risk assessments—Lessons from low-carbon transitions. Environmental Innovation and Societal Transitions 35, 400-413. https://doi.org/10.1016/j.eist.2020.04.001.</strong> Full details of methods used to create the dataset and provided within this publication.
DOI: 10.25919/5f8b267be7537
title: Parkes observations for project P737 semester 2020APRS_11

description: The aim of this proposal is to carry out tests of the new backend instruments which cannot be carried out during standard maintenance periods. The scheduled time is used to measure beam shapes, determine polarisation calibration solutions and commission the National Facility observing modes for the new wide-band receiver.
DOI: 10.5281/zenodo.4099717
title: Tabular summary of shampoo sales

description: This is the tabular summary of shampoo sales data.
DOI: 10.5281/zenodo.4099716
title: Tabular summary of shampoo sales

description: This is the tabular summary of shampoo sales data.
DOI: 10.5281/zenodo.4099722
title: Van de Ven et al._2019_ERL_DATASET

description: This dataset contains the underlying data for the following publication: <strong>Van de Ven, D. J., Sampedro, J., Johnson, F. X., Bailis, R., Forouli, A., Nikas, A., ... & Doukas, H. (2019). Integrated policy assessment and optimisation over multiple sustainable development goals in Eastern Africa. <em>Environmental Research Letters, 14</em>(9), 094001, </strong><strong>https://doi.org/10.1088/1748-9326/ab375d</strong>. Full details of methods used to create the dataset are provided within this publication.
DOI: 10.5281/zenodo.4099721
title: Van de Ven et al._2019_ERL_DATASET

description: This dataset contains the underlying data for the following publication: <strong>Van de Ven, D. J., Sampedro, J., Johnson, F. X., Bailis, R., Forouli, A., Nikas, A., ... & Doukas, H. (2019). Integrated policy assessment and optimisation over multiple sustainable development goals in Eastern Africa. <em>Environmental Research Letters, 14</em>(9), 094001, </strong><strong>https://doi.org/10.1088/1748-9326/ab375d</strong>. Full details of methods used to create the dataset are provided within this publication.
DOI: 10.25345/c5ff4j
title: MassIVE MSV000086319 - Acapulco Bay Aspergillus sp ACA9 GNPS_3
title: This GNPS project pretend to be the final version of our study. We include new extracts and pure compounds obtained from the same strain but at different culture conditions.
DOI: 10.5517/cc95vhs
title: CCDC 273745: Experimental Crystal Structure Determination

description: Related Article: Xiu-E Lin, Rong Cao, Yan-Qin Wang, Xiao-Ju Li, Wen-Hua Bi, Da-Qiang Yuan|2005|Jiegou Huaxue|24|711|
DOI: 10.5517/ccdc.csd.cc23vdcr
title: CCDC 1961784: Experimental Crystal Structure Determination

description: Related Article: Atanu Banerjee, Subhashree P. Dash, Monalisa Mohanty, Gurunath Sahu, Giuseppe Sciortino, Eugenio Garribba, M. Fernanda N. N. Carvalho, Fernanda Marques, João Costa Pessoa, Werner Kaminsky, Krzysztof Brzezinski, Rupam Dinda|2020|Inorg.Chem.|59|14042|doi:10.1021/acs.inorgchem.0c01837
DOI: 10.5517/ccdc.csd.cc24bg43
title: CCDC 1976254: Experimental Crystal Structure Determination

description: Related Article: Atanu Banerjee, Subhashree P. Dash, Monalisa Mohanty, Gurunath Sahu, Giuseppe Sciortino, Eugenio Garribba, M. Fernanda N. N. Carvalho, Fernanda Marques, João Costa Pessoa, Werner Kaminsky, Krzysztof Brzezinski, Rupam Dinda|2020|Inorg.Chem.|59|14042|doi:10.1021/acs.inorgchem.0c01837
DOI: 10.5517/ccdc.csd.cc24bg54
title: CCDC 1976255: Experimental Crystal Structure Determination

description: Related Article: Atanu Banerjee, Subhashree P. Dash, Monalisa Mohanty, Gurunath Sahu, Giuseppe Sciortino, Eugenio Garribba, M. Fernanda N. N. Carvalho, Fernanda Marques, João Costa Pessoa, Werner Kaminsky, Krzysztof Brzezinski, Rupam Dinda|2020|Inorg.Chem.|59|14042|doi:10.1021/acs.inorgchem.0c01837
DOI: 10.5517/ccdc.csd.cc24x61b
title: CCDC 1993301: Experimental Crystal Structure Determination

description: Related Article: Srijan Narayan Chowdhury, Sachidulal Biswas, Purak Das, Satadal Paul, Achintesh N. Biswas|2020|Inorg.Chem.|59|14012|doi:10.1021/acs.inorgchem.0c01776
DOI: 10.5517/ccdc.csd.cc23jyqb
title: CCDC 1952712: Experimental Crystal Structure Determination

description: Related Article: Martyna Szymańska, Małgorzata Insińska-Rak, Grzegorz Dutkiewicz, Giovanni N. Roviello, Marta A. Fik-Jaskółka, Violetta Patroniak|2020|J.Mol.Liq.|319|114182|doi:10.1016/j.molliq.2020.114182
DOI: 10.5517/ccdc.csd.cc25bkbf
title: CCDC 2006144: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Anamaria Ardelean, Peter Lönnecke, Ghenadie Novitchi, Evamarie Hey-Hawkins, Marius Andruh, Otilia Costisor|2020|Polyhedron|190|114766|doi:10.1016/j.poly.2020.114766
DOI: 10.5517/ccdc.csd.cc25bkcg
title: CCDC 2006145: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Anamaria Ardelean, Peter Lönnecke, Ghenadie Novitchi, Evamarie Hey-Hawkins, Marius Andruh, Otilia Costisor|2020|Polyhedron|190|114766|doi:10.1016/j.poly.2020.114766
DOI: 10.5517/ccdc.csd.cc25bkdh
title: CCDC 2006146: Experimental Crystal Structure Determination

description: Related Article: Ildiko Buta, Anamaria Ardelean, Peter Lönnecke, Ghenadie Novitchi, Evamarie Hey-Hawkins, Marius Andruh, Otilia Costisor|2020|Polyhedron|190|114766|doi:10.1016/j.poly.2020.114766
DOI: 10.5517/ccdc.csd.cc25fw3m
title: CCDC 2009330: Experimental Crystal Structure Determination

description: Related Article: Eranga H. Gamage, Joshua T. Greenfield, Colin Unger, Saeed Kamali, Judith K. Clark, Colin P. Harmer, Liang Luo, Jigang Wang, Michael Shatruk, Kirill Kovnir|2020|Inorg.Chem.|59|13353|doi:10.1021/acs.inorgchem.0c01727
DOI: 10.5517/ccdc.csd.cc25fw5p
title: CCDC 2009332: Experimental Crystal Structure Determination

description: Related Article: Eranga H. Gamage, Joshua T. Greenfield, Colin Unger, Saeed Kamali, Judith K. Clark, Colin P. Harmer, Liang Luo, Jigang Wang, Michael Shatruk, Kirill Kovnir|2020|Inorg.Chem.|59|13353|doi:10.1021/acs.inorgchem.0c01727
DOI: 10.5517/ccdc.csd.cc25g13t
title: CCDC 2009485: Experimental Crystal Structure Determination

description: Related Article: Jonas Bresien, Yannic Pilopp, Axel Schulz, Lilian Sophie Szych, Alexander Villinger, Ronald Wustrack|2020|Inorg.Chem.|59|13561|doi:10.1021/acs.inorgchem.0c01934
DOI: 10.5517/ccdc.csd.cc25g14v
title: CCDC 2009486: Experimental Crystal Structure Determination

description: Related Article: Jonas Bresien, Yannic Pilopp, Axel Schulz, Lilian Sophie Szych, Alexander Villinger, Ronald Wustrack|2020|Inorg.Chem.|59|13561|doi:10.1021/acs.inorgchem.0c01934
DOI: 10.5517/ccdc.csd.cc25g15w
title: CCDC 2009487: Experimental Crystal Structure Determination

description: Related Article: Jonas Bresien, Yannic Pilopp, Axel Schulz, Lilian Sophie Szych, Alexander Villinger, Ronald Wustrack|2020|Inorg.Chem.|59|13561|doi:10.1021/acs.inorgchem.0c01934
DOI: 10.5517/ccdc.csd.cc25g16x
title: CCDC 2009488: Experimental Crystal Structure Determination

description: Related Article: Jonas Bresien, Yannic Pilopp, Axel Schulz, Lilian Sophie Szych, Alexander Villinger, Ronald Wustrack|2020|Inorg.Chem.|59|13561|doi:10.1021/acs.inorgchem.0c01934
DOI: 10.5517/ccdc.csd.cc25g17y
title: CCDC 2009489: Experimental Crystal Structure Determination

description: Related Article: Jonas Bresien, Yannic Pilopp, Axel Schulz, Lilian Sophie Szych, Alexander Villinger, Ronald Wustrack|2020|Inorg.Chem.|59|13561|doi:10.1021/acs.inorgchem.0c01934
DOI: 10.5517/ccdc.csd.cc25jjt2
title: CCDC 2011894: Experimental Crystal Structure Determination

description: Related Article: Abhisek Banerjee, Shouvik Chattopadhyay|2021|Inorg.Chim.Acta|515|120044|doi:10.1016/j.ica.2020.120044