cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc294xw8
title: CCDC 2119900: Experimental Crystal Structure Determination

description: Related Article: Bibian Okokhere-Edeghoghon, Samuel E. Neale, Michael S. Hill, Mary F. Mahon, Claire L. McMullin|2022|Dalton Trans.|51|136|doi:10.1039/D1DT03775G
DOI: 10.5517/ccdc.csd.cc294xx9
title: CCDC 2119901: Experimental Crystal Structure Determination

description: Related Article: Bibian Okokhere-Edeghoghon, Samuel E. Neale, Michael S. Hill, Mary F. Mahon, Claire L. McMullin|2022|Dalton Trans.|51|136|doi:10.1039/D1DT03775G
DOI: 10.5517/ccdc.csd.cc294xyb
title: CCDC 2119902: Experimental Crystal Structure Determination

description: Related Article: Bibian Okokhere-Edeghoghon, Samuel E. Neale, Michael S. Hill, Mary F. Mahon, Claire L. McMullin|2022|Dalton Trans.|51|136|doi:10.1039/D1DT03775G
DOI: 10.5517/ccdc.csd.cc295tq1
title: CCDC 2120763: Experimental Crystal Structure Determination

description: Related Article: Po-Han Chen, Ching-Pei Hsu, Hsi-Ching Tseng, Yi-Hung Liu, Ching-Wen Chiu|2021|Chem.Commun.|57|13732|doi:10.1039/D1CC06319G
DOI: 10.5517/ccdc.csd.cc295tr2
title: CCDC 2120764: Experimental Crystal Structure Determination

description: Related Article: Po-Han Chen, Ching-Pei Hsu, Hsi-Ching Tseng, Yi-Hung Liu, Ching-Wen Chiu|2021|Chem.Commun.|57|13732|doi:10.1039/D1CC06319G
DOI: 10.5517/ccdc.csd.cc295ts3
title: CCDC 2120765: Experimental Crystal Structure Determination

description: Related Article: Po-Han Chen, Ching-Pei Hsu, Hsi-Ching Tseng, Yi-Hung Liu, Ching-Wen Chiu|2021|Chem.Commun.|57|13732|doi:10.1039/D1CC06319G
DOI: 10.5517/ccdc.csd.cc28z3m0
title: CCDC 2114312: Experimental Crystal Structure Determination

description: Related Article: Hassan A. Baalbaki, Kudzanai Nyamayaro, Julia Shu, Chatura Goonesinghe, Hyuk-Joon Jung, Parisa Mehrkhodavandi|2021|Inorg.Chem.|60|19304|doi:10.1021/acs.inorgchem.1c03123
DOI: 10.5517/ccdc.csd.cc28z3p2
title: CCDC 2114314: Experimental Crystal Structure Determination

description: Related Article: Hassan A. Baalbaki, Kudzanai Nyamayaro, Julia Shu, Chatura Goonesinghe, Hyuk-Joon Jung, Parisa Mehrkhodavandi|2021|Inorg.Chem.|60|19304|doi:10.1021/acs.inorgchem.1c03123
DOI: 10.5517/ccdc.csd.cc2925k4
title: CCDC 2117255: Experimental Crystal Structure Determination

description: Related Article: Yi Deng, Xiao Liang, Kun Wei, Yu-Rong Yang|2021|J.Am.Chem.Soc.|143|20622|doi:10.1021/jacs.1c11265
DOI: 10.5517/ccdc.csd.cc29bs1h
title: CCDC 2125516: Experimental Crystal Structure Determination

description: Related Article: Bibian Okokhere-Edeghoghon, Samuel E. Neale, Michael S. Hill, Mary F. Mahon, Claire L. McMullin|2022|Dalton Trans.|51|136|doi:10.1039/D1DT03775G
DOI: 10.5517/ccdc.csd.cc29bs2j
title: CCDC 2125517: Experimental Crystal Structure Determination

description: Related Article: Bibian Okokhere-Edeghoghon, Samuel E. Neale, Michael S. Hill, Mary F. Mahon, Claire L. McMullin|2022|Dalton Trans.|51|136|doi:10.1039/D1DT03775G
DOI: 10.6084/m9.figshare.17410325
title: Cross_section_profile_data

description: The raw data used to plot the lateral average of the shear-wave velocity anomaly as a function of depth for 33 cross-sections from 17 S-wave models. The "0" in the naming format of "*_0_dat" means the average for all shear-wave velocity anomaly; while the "1" in the naming format of "*_1_dat" refers the average of only the negative shear-wave velocity anomaly.
DOI: 10.15468/ydt3nn
title: Neolepetopsid true limpets (Gastropoda: Patellogastropoda) from Indian Ocean hot vents shed light on relationships among genera

description: This dataset contains the digitized treatments in Plazi based on the original journal article Chen, Chong, Zhou, Yadong, Watanabe, Hiromi Kayama, Zhang, Ruiyan, Wang, Chunsheng (2022): Neolepetopsid true limpets (Gastropoda: Patellogastropoda) from Indian Ocean hot vents shed light on relationships among genera. Zoological Journal of the Linnean Society 194: 276-296, DOI: 10.1093/zoolinnean/zlab081
DOI: 10.6084/m9.figshare.17418890
title: Effectiveness and common side effects of Dolutegravir Compared to Efavirenz-Based Regimens of Combined Antiretroviral Therapy in Kitwe, Zambia.xlsx

description: An unpaired t-test was performed to compare viral load suppression and CD4 count between clients on EFV based regimen and DTG based regimen at 24 weeks, 48 weeks and 96 weeks. This test was also performed when comparing viral load and CD4 count of clients switched from EFV based regimen to DTG based regimen. In addition, to compare viral and CD4 count within treatment groups on the two regimens at different periods, the Friedman’s test was used; followed by a Pairwise comparison using the Dunn Post Hoc Test with the Bonferroni correction. To assess if clients with viral suppression remain virally suppressed after switching from EFV-based regimens to DTG based regimens VL and CD4+ were analysed 24 weeks after the switch to DTG based regimens and then at 48 weeks. Records of clients’ results before the switch to DTG based regimens were compared to records after switching to DTG based regimens and reported as percentages and proportions. To assess adherence and compliance to treatment, dates of the review were noted. Common side effects of naïve clients on both regimens’ data were collected from records of clients on both regimens and were described in proportions and assessed with the chi-square test; Side effects of experienced clients before and after the switch to DTG-based regimens, data was described using proportions and assessed with the chi-square test.Data were analysed using Microsoft Excel spreadsheets and Graph Pad Prism 7 statistical package. For statistical significance, a p-value less than 0.05 was accepted.
DOI: 10.6084/m9.figshare.17418890.v1
title: Effectiveness and common side effects of Dolutegravir Compared to Efavirenz-Based Regimens of Combined Antiretroviral Therapy in Kitwe, Zambia.xlsx

description: An unpaired t-test was performed to compare viral load suppression and CD4 count between clients on EFV based regimen and DTG based regimen at 24 weeks, 48 weeks and 96 weeks. This test was also performed when comparing viral load and CD4 count of clients switched from EFV based regimen to DTG based regimen. In addition, to compare viral and CD4 count within treatment groups on the two regimens at different periods, the Friedman’s test was used; followed by a Pairwise comparison using the Dunn Post Hoc Test with the Bonferroni correction. To assess if clients with viral suppression remain virally suppressed after switching from EFV-based regimens to DTG based regimens VL and CD4+ were analysed 24 weeks after the switch to DTG based regimens and then at 48 weeks. Records of clients’ results before the switch to DTG based regimens were compared to records after switching to DTG based regimens and reported as percentages and proportions. To assess adherence and compliance to treatment, dates of the review were noted. Common side effects of naïve clients on both regimens’ data were collected from records of clients on both regimens and were described in proportions and assessed with the chi-square test; Side effects of experienced clients before and after the switch to DTG-based regimens, data was described using proportions and assessed with the chi-square test.Data were analysed using Microsoft Excel spreadsheets and Graph Pad Prism 7 statistical package. For statistical significance, a p-value less than 0.05 was accepted.
DOI: 10.48511/hgec-0c46
title:  Columbia Lake Water Quality (EKISC) 

description: The East Kootenay Invasive Species Council (EKISC) conducts invasive mussel monitoring on various waterbodies across the region. A water sample is taken at each lake using a plankton tow net to test for invasive Zebra and Quagga mussel larva. Ancillary data including temperature, pH, and Secchi depth are taken at each water body and are shared in this dataset. Higher priority lakes (i.e., lakes that receive more transient use) are sampled twice per month, while lower priority lakes are sampled once per month from the beginning of June until the end of September. This dataset contains ancillary data collected from Columbia Lake.
DOI: 10.5281/zenodo.5800012
title: Erythroxylum williamsii decontaminated FSCR

description: .
DOI: 10.5281/zenodo.5800011
title: Erythroxylum williamsii decontaminated FSCR

description: .
DOI: 10.25919/pfkr-s130
title: Comparative proteomics study of the conglutin proteins across 46 narrow-leafed lupin accessions

description: The most abundant proteins in lupin seeds are the conglutin proteins which are classified into four major families: α, β, γ and δ. These seed storage proteins, play a major role in supplying nitrogen, carbon, and sulphur to the growing seedling during germination and contribute to specific pharmaceutical and nutritional attributes. For instance, the beta conglutin proteins with desirable techno-functional characteristics are known as the main allergenic proteins in lupin seed, whilst the gamma conglutin proteins have been reported to possess strong anti-diabetic properties. Herein, a combination of discovery and targeted quantitative proteomics approaches were used for evaluating the diversity of the conglutin profiles across 46 genetically diverse narrow-leafed lupin (NLL, Lupinus angustifolius) accessions. This collection includes the following data: 1- The information-dependent acquisition mass spectrometry (IDA-MS) data 2- ProteinPilot Reports for the IDA data which includes information about the data quality and protein and peptide identifications 3-Multiple reaction monitoring-mass spectrometry (LC-MRM-MS) data
DOI: 10.5281/zenodo.5719520
title: Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: discovery cohort meta data and parsed TCR repertoire data

description: Meta data corresponding the the discovery cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: (1) a file mapping the SNP data subject IDs to the TCR repertoire data subject IDs (gwas_id_mapping.tsv)<br> (2) a file including the PCAir PCs, self-reported ancestry, and genomic ancestry for each subject (all_pc_air.txt)<br> (3) a file including the PCAir variance explained by each PC (all_pc_air_variance.txt)<br> (3) a file including the SNP ID, chromosome, hg19 position, allele, rsid, and quality control metrics for each SNP in the SNP array (emerson_snp_rs_data.tsv)<br> (4) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (5) a file including predicted TRBD2 allele genotypes for each subject (emerson_trbd2_alleles.tsv)<br> (6) Parsed TCRB repertoire data. These raw data were first published in Emerson et. al, <em>Nature Genetics </em>2017. (emerson_parsed_tcrb.tgz) <strong>Corresponding discovery cohort raw TCR repertoire data is available here: </strong>https: //doi.org/10.21417/B7001Z (ImmuneACCESS database)<br> <strong>Corresponding discovery cohort SNP data is available here:</strong> https: //www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001918.v1.p1 (The database of Genotypes and Phenotypes, accession number: phs001918)<br> <br> <strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas
description: {"references": ["Emerson, Ryan O., William S. DeWitt, Marissa Vignali, Jenna Gravley, Joyce K. Hu, Edward J. Osborne, Cindy Desmarais, et al. 2017. \"Immunosequencing Identifies Signatures of Cytomegalovirus Exposure History and HLA-Mediated Effects on the T Cell Repertoire.\" Nature Genetics 49 (5): 659\u201365.", "Martin, Paul J., David M. Levine, Barry E. Storer, Sarah C. Nelson, Xinyuan Dong, and John A. Hansen. 2020. \"Recipient and Donor Genetic Variants Associated with Mortality after Allogeneic Hematopoietic Cell Transplantation.\" Blood Advances 4 (14): 3224\u201333."]}
DOI: 10.5281/zenodo.5719519
title: Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: discovery cohort meta data and parsed TCR repertoire data

description: Meta data corresponding the the discovery cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: (1) a file mapping the SNP data subject IDs to the TCR repertoire data subject IDs (gwas_id_mapping.tsv)<br> (2) a file including the PCAir PCs, self-reported ancestry, and genomic ancestry for each subject (all_pc_air.txt)<br> (3) a file including the PCAir variance explained by each PC (all_pc_air_variance.txt)<br> (3) a file including the SNP ID, chromosome, hg19 position, allele, rsid, and quality control metrics for each SNP in the SNP array (emerson_snp_rs_data.tsv)<br> (4) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (5) a file including predicted TRBD2 allele genotypes for each subject (emerson_trbd2_alleles.tsv)<br> (6) Parsed TCRB repertoire data. These raw data were first published in Emerson et. al, <em>Nature Genetics </em>2017. (emerson_parsed_tcrb.tgz) <strong>Corresponding discovery cohort raw TCR repertoire data is available here: </strong>https: //doi.org/10.21417/B7001Z (ImmuneACCESS database)<br> <strong>Corresponding discovery cohort SNP data is available here:</strong> https: //www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001918.v1.p1 (The database of Genotypes and Phenotypes, accession number: phs001918)<br> <br> <strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas
description: {"references": ["Emerson, Ryan O., William S. DeWitt, Marissa Vignali, Jenna Gravley, Joyce K. Hu, Edward J. Osborne, Cindy Desmarais, et al. 2017. \"Immunosequencing Identifies Signatures of Cytomegalovirus Exposure History and HLA-Mediated Effects on the T Cell Repertoire.\" Nature Genetics 49 (5): 659\u201365.", "Martin, Paul J., David M. Levine, Barry E. Storer, Sarah C. Nelson, Xinyuan Dong, and John A. Hansen. 2020. \"Recipient and Donor Genetic Variants Associated with Mortality after Allogeneic Hematopoietic Cell Transplantation.\" Blood Advances 4 (14): 3224\u201333."]}
DOI: 10.5281/zenodo.5719516
title: Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: validation cohort meta data and parsed TCR repertoire data

description: Meta data corresponding the the validation cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: (1) SNP genotypes for the two SNPs which overlap with the discovery cohort<br> - (nicaragua_snp_genotypes_ints.tsv) -- SNP genotypes as integers<br> - (nicaragua_snp_genotypes_strings.tsv) -- SNP genotypes as allele strings <br> (2) the ancestry PCs for each individual in the validation cohort (nicaragua_snp_ancestry_PCA.tsv)<br> (3) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (4) a file including IMGT genes used for parsing TCRA repertoire data (human_vj_alleles_alpha.tsv)<br> (5) Parsed TCRA repertoire data (nicaragua_parsed_TCRA.tgz)<br> (6) Parsed TCRB repertoire data (nicaragua_parsed_TCRB.tgz) <strong>Corresponding raw validation cohort TCR repertoire data is available here:</strong> https://www. ncbi.nlm.nih.gov/bioproject/PRJNA762269 (The BioProject database, accession number: PRJNA762269) <strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas
DOI: 10.5281/zenodo.5719515
title: Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities: validation cohort meta data and parsed TCR repertoire data

description: Meta data corresponding the the validation cohort for the paper, "Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities" by Magdalena L Russell, Aisha Souquette, David M Levine, Stefan A Schattgen, E Kaitlynn Allen, Guillermina Kuan, Noah Simon, Angel Balmaseda, Aubree Gordon, Paul G Thomas, Frederick A Matsen IV, and Philip Bradley. These meta data include: (1) SNP genotypes for the two SNPs which overlap with the discovery cohort<br> - (nicaragua_snp_genotypes_ints.tsv) -- SNP genotypes as integers<br> - (nicaragua_snp_genotypes_strings.tsv) -- SNP genotypes as allele strings <br> (2) the ancestry PCs for each individual in the validation cohort (nicaragua_snp_ancestry_PCA.tsv)<br> (3) a file including IMGT genes and sequences used for parsing TCRB repertoire data (human_vj_allele_cdr3_nucseqs.tsv)<br> (4) a file including IMGT genes used for parsing TCRA repertoire data (human_vj_alleles_alpha.tsv)<br> (5) Parsed TCRA repertoire data (nicaragua_parsed_TCRA.tgz)<br> (6) Parsed TCRB repertoire data (nicaragua_parsed_TCRB.tgz) <strong>Corresponding raw validation cohort TCR repertoire data is available here:</strong> https://www. ncbi.nlm.nih.gov/bioproject/PRJNA762269 (The BioProject database, accession number: PRJNA762269) <strong>Software tools designed to work with these data are available here:</strong> https://github.com/phbradley/tcr-gwas
DOI: 10.48511/9zmw-hc96
title:  Columbia River at Columbia Wetlands 

description: The Columbia Shuswap Invasive Species Society (CSISS) collects plankton samples for several waterbodies in the Northern Columbia Basin which are tested for the presence of larval stages of invasive mussels and clams. Along with the plankton samples, ancillary data including surface pH, surface temperature and Secchi depth are measured. Data is collected from July to September, either every 2 weeks or every month (depending on the waterbody’s risk of infestation).
DOI: 10.34740/kaggle/dsv/2958895
title: Covid patient datasets
DOI: 10.48511/26m1-qb37
title:  Columbia River at Donald Bridge 

description: The Columbia Shuswap Invasive Species Society (CSISS) collects plankton samples for several waterbodies in the Northern Columbia Basin which are tested for the presence of larval stages of invasive mussels and clams. Along with the plankton samples, ancillary data including surface pH, surface temperature and Secchi depth are measured. Data is collected from July to September, either every 2 weeks or every month (depending on the waterbody’s risk of infestation).
DOI: 10.6084/m9.figshare.3761562.v2081
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.48511/5252-6z48
title:  Columbia River at Golden Airport 

description: The Columbia Shuswap Invasive Species Society (CSISS) collects plankton samples for several waterbodies in the Northern Columbia Basin which are tested for the presence of larval stages of invasive mussels and clams. Along with the plankton samples, ancillary data including surface pH, surface temperature and Secchi depth are measured. Data is collected from July to September, either every 2 weeks or every month (depending on the waterbody’s risk of infestation).
DOI: 10.48511/h168-gv18
title:  Columbia River at Nicholson Bridge 

description: The Columbia Shuswap Invasive Species Society (CSISS) collects plankton samples for several waterbodies in the Northern Columbia Basin which are tested for the presence of larval stages of invasive mussels and clams. Along with the plankton samples, ancillary data including surface pH, surface temperature and Secchi depth are measured. Data is collected from July to September, either every 2 weeks or every month (depending on the waterbody’s risk of infestation).
DOI: 10.34740/kaggle/dsv/2958921
title: persian sms dataset
DOI: 10.26007/aajh-r451
title: Rosetta Shape Model of Asteroid Lutetia V1.0

description: Detailed plate shape model of asteroid 21 Lutetia, as derived from the Rosetta images obtained around the time of closest approach. Twelve different versions of the model, at different resolutions, are given.
DOI: 10.6084/m9.figshare.4930094.v3
title: Bibliography for newcomers to translation & interpreting studies: 2020 edition

description: This is a bibliography for newcomers to translation and interpreting studies, and covers general introductions and reference works. We will update this bibliography approximately once a year.<br><br>Major changes in the 2020 edition: we added more works and clarified what we consider 'open' access
DOI: 10.26007/55fk-cb77
title: Rosetta Shape Model of Asteroid Steins V1.0

description: Detailed plate shape model of asteroid 2867 Steins, as derived from the Rosetta images obtained around the time of closest approach.
DOI: 10.34740/kaggle/dsv/2958920
title: persian news dataset
DOI: 10.6084/m9.figshare.17424062
title: contigs_acc_No.txt

description: no ab
DOI: 10.6084/m9.figshare.17424062.v1
title: contigs_acc_No.txt

description: no ab
DOI: 10.5517/ccdc.csd.cc26nfq1
title: CCDC 2045433: Experimental Crystal Structure Determination

description: Related Article: Wei Lin, Qun Zhao, Yao Li, Ming Pan, Chen Yang, Guo-Hui Yang, Xin Li|2022|Chemical Science|13|141|doi:10.1039/D1SC05360D
DOI: 10.5517/ccdc.csd.cc275rfm
title: CCDC 2061110: Experimental Crystal Structure Determination

description: Related Article: Christopher Timmermann, Paula Thiem, Dominik Wanitschke, Mareike Hüttenschmidt, Johanna Romischke, Alexander Villinger, Wolfram W. Seidel|2022|Chemical Science|13|123|doi:10.1039/D1SC06149F
DOI: 10.5517/ccdc.csd.cc275rgn
title: CCDC 2061111: Experimental Crystal Structure Determination

description: Related Article: Christopher Timmermann, Paula Thiem, Dominik Wanitschke, Mareike Hüttenschmidt, Johanna Romischke, Alexander Villinger, Wolfram W. Seidel|2022|Chemical Science|13|123|doi:10.1039/D1SC06149F
DOI: 10.5517/ccdc.csd.cc275rhp
title: CCDC 2061112: Experimental Crystal Structure Determination

description: Related Article: Christopher Timmermann, Paula Thiem, Dominik Wanitschke, Mareike Hüttenschmidt, Johanna Romischke, Alexander Villinger, Wolfram W. Seidel|2022|Chemical Science|13|123|doi:10.1039/D1SC06149F
DOI: 10.5517/ccdc.csd.cc275rjq
title: CCDC 2061113: Experimental Crystal Structure Determination

description: Related Article: Christopher Timmermann, Paula Thiem, Dominik Wanitschke, Mareike Hüttenschmidt, Johanna Romischke, Alexander Villinger, Wolfram W. Seidel|2022|Chemical Science|13|123|doi:10.1039/D1SC06149F
DOI: 10.5517/ccdc.csd.cc275rkr
title: CCDC 2061114: Experimental Crystal Structure Determination

description: Related Article: Christopher Timmermann, Paula Thiem, Dominik Wanitschke, Mareike Hüttenschmidt, Johanna Romischke, Alexander Villinger, Wolfram W. Seidel|2022|Chemical Science|13|123|doi:10.1039/D1SC06149F
DOI: 10.5517/ccdc.csd.cc275rls
title: CCDC 2061115: Experimental Crystal Structure Determination

description: Related Article: Christopher Timmermann, Paula Thiem, Dominik Wanitschke, Mareike Hüttenschmidt, Johanna Romischke, Alexander Villinger, Wolfram W. Seidel|2022|Chemical Science|13|123|doi:10.1039/D1SC06149F