cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5242879
title: Finnish DBnary archive in original Lemon format

description: The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Finnish language edition, ranging from 3rd September 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>
DOI: 10.5281/zenodo.5243188
title: Italian DBnary archive in original Lemon format

description: The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Italian language edition, ranging from 27th August 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.
DOI: 10.5281/zenodo.5242878
title: Finnish DBnary archive in original Lemon format

description: The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Finnish language edition, ranging from 3rd September 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>
DOI: 10.6084/m9.figshare.7588859
title: Harnessing the full potential of biomethane towards tomorrow’s bioeconomy: a national case study coupling sustainable agricultural intensification, emerging biogas technologies and energy system analysis - complete dataset

description: This dataset describes all key figures behind the paper of Hamelin et al. (Harnessing the full potential of biomethane towards tomorrow's bioeconomy: a national case study coupling sustainable agricultural intensification, emerging biogas technologies and energy system analysis). It among others details the calculation of the biomass potentials under the various sustainable intensification measures considered. It also details the calculation of the (hour per hour) fluctuating power deficits that could be buffered by biomethane. It further presents the calculation of the biomethane potentials for the 6 scenarios considered in the above-mentioned paper.
DOI: 10.6084/m9.figshare.7588859.v1
title: Harnessing the full potential of biomethane towards tomorrow’s bioeconomy: a national case study coupling sustainable agricultural intensification, emerging biogas technologies and energy system analysis - complete dataset

description: This dataset describes all key figures behind the paper of Hamelin et al. (Harnessing the full potential of biomethane towards tomorrow's bioeconomy: a national case study coupling sustainable agricultural intensification, emerging biogas technologies and energy system analysis). It among others details the calculation of the biomass potentials under the various sustainable intensification measures considered. It also details the calculation of the (hour per hour) fluctuating power deficits that could be buffered by biomethane. It further presents the calculation of the biomethane potentials for the 6 scenarios considered in the above-mentioned paper.
DOI: 10.6084/m9.figshare.16419945
title: Effects of Different Sources of Dietary Fibre of Growth Performance and Foie Gras Quality of Geese: A Meta-Analysis and Meta Regression’. Extended data; fig share

description: 1. The aim of this meta-analysis was to investigate the effects of different sources of dietary fibre on growth performance and foie gras quality of geese. A dataset was arranged based on the algorithm for peer-reviewed published article from 1995 to 2021. The peer-reviewed published articles were evaluated strictly following the eligibility criteria for inclusion. 2. The final dataset consisted of 21 in vivo studies with 83 treatments units. Meta-analysis and meta-regression were performed using non-linear mixed model (nlme) library from R Studio 4.0.2. The structure algorithm conducted using library “magicks”; “ggplot”; “ggplot2”; and “cowplot” was added to represent heat-map countries of origin. 3. The quadratic patterns were shown (<i>p </i>&lt; 0.001) on growth performances from the result of meta-analyses on geese. The linear pattern shown (p &lt; 0.001) on foie gras quality. However, the blood parameters, probiotics decreased triglycerides (p &lt; 0.001) and concomitantly decreased albumin (p &lt; 0.01) in geese. The total population of the geese used on the experiment had effect on the outcomes 4. Meta-regression presented source of fibre used in the experiments were associated with growth performance and foie grass quality with the intercept (78.33 and 68.44, respectively); (<i>p</i>= 0.0056 and P&lt;0.051, respectively). Moreover, slope were presented (0.33 and 82.13, respectively); (<i>p</i>= 0.0077 and &lt;0.032 respectively) (Table 3). 5. Descriptive model shown that the carcase was 79.74±12.67% with Q25; Q50; Q75 was 71; 85.8; 87.7 % respectively. In instance, the Q25; Q50; Q75 of slaughtered weight (SW) at the 2780; 3320; 3410 g, respectively. Meanwhile, foie gras weight (FGW) result was 605.57±189.68 g/kg with each minimum weight at the 445 g/kg and maximum was 1026 g/kg. In line, both liver and hear present Q25; Q50; Q75 was 2.04; 2.39; 7.45 g/Kg and 0.65; 1.02; 22.01 g/Kg, respectively. Additionally, lightness represented 50.20±11.32 with Q25; Q50; Q75 was 39.01; 49.75; 51.42 g, respectively. In line, minimum result at the treatment was 39.01 and maximum result was 38.14 g. Moreover, redness result was 15.35±2.53 with Q25; Q50; Q75 was 14.23; 14.69; 18.52 g, respectively. Last, yellowness presented that the minimum result was 3.08 and maximum result was 23.8 with Q25; Q50; Q75 was 3.19; 7.27; 7.48, respectively. 6. The scientific evidence from the meta-analysis based on the in-vivo studies demonstrates that the dietary fibre is effective to enhance the intestinal villus number and improving the foie gras quality.
DOI: 10.6084/m9.figshare.16419945.v1
title: Effects of Different Sources of Dietary Fibre of Growth Performance and Foie Gras Quality of Geese: A Meta-Analysis and Meta Regression’. Extended data; fig share

description: 1. The aim of this meta-analysis was to investigate the effects of different sources of dietary fibre on growth performance and foie gras quality of geese. A dataset was arranged based on the algorithm for peer-reviewed published article from 1995 to 2021. The peer-reviewed published articles were evaluated strictly following the eligibility criteria for inclusion. 2. The final dataset consisted of 21 in vivo studies with 83 treatments units. Meta-analysis and meta-regression were performed using non-linear mixed model (nlme) library from R Studio 4.0.2. The structure algorithm conducted using library “magicks”; “ggplot”; “ggplot2”; and “cowplot” was added to represent heat-map countries of origin. 3. The quadratic patterns were shown (<i>p </i>&lt; 0.001) on growth performances from the result of meta-analyses on geese. The linear pattern shown (p &lt; 0.001) on foie gras quality. However, the blood parameters, probiotics decreased triglycerides (p &lt; 0.001) and concomitantly decreased albumin (p &lt; 0.01) in geese. The total population of the geese used on the experiment had effect on the outcomes 4. Meta-regression presented source of fibre used in the experiments were associated with growth performance and foie grass quality with the intercept (78.33 and 68.44, respectively); (<i>p</i>= 0.0056 and P&lt;0.051, respectively). Moreover, slope were presented (0.33 and 82.13, respectively); (<i>p</i>= 0.0077 and &lt;0.032 respectively) (Table 3). 5. Descriptive model shown that the carcase was 79.74±12.67% with Q25; Q50; Q75 was 71; 85.8; 87.7 % respectively. In instance, the Q25; Q50; Q75 of slaughtered weight (SW) at the 2780; 3320; 3410 g, respectively. Meanwhile, foie gras weight (FGW) result was 605.57±189.68 g/kg with each minimum weight at the 445 g/kg and maximum was 1026 g/kg. In line, both liver and hear present Q25; Q50; Q75 was 2.04; 2.39; 7.45 g/Kg and 0.65; 1.02; 22.01 g/Kg, respectively. Additionally, lightness represented 50.20±11.32 with Q25; Q50; Q75 was 39.01; 49.75; 51.42 g, respectively. In line, minimum result at the treatment was 39.01 and maximum result was 38.14 g. Moreover, redness result was 15.35±2.53 with Q25; Q50; Q75 was 14.23; 14.69; 18.52 g, respectively. Last, yellowness presented that the minimum result was 3.08 and maximum result was 23.8 with Q25; Q50; Q75 was 3.19; 7.27; 7.48, respectively. 6. The scientific evidence from the meta-analysis based on the in-vivo studies demonstrates that the dietary fibre is effective to enhance the intestinal villus number and improving the foie gras quality.
DOI: 10.6084/m9.figshare.7363775
title: A spatially-explicit and dynamic assessment framework to uncover the role of biogas for local bioeconomy. Case study in a Polish municipality - complete dataset

description: This is the complete dataset accompanying the unpublished material "A spatially-explicit and dynamic assessment framework to uncover the role of biogas for local bioeconomy"
DOI: 10.6084/m9.figshare.7363775.v1
title: A spatially-explicit and dynamic assessment framework to uncover the role of biogas for local bioeconomy. Case study in a Polish municipality - complete dataset

description: This is the complete dataset accompanying the unpublished material "A spatially-explicit and dynamic assessment framework to uncover the role of biogas for local bioeconomy"
DOI: 10.5281/zenodo.4906451
title: Review: A bibliometric survey of live feed for marine finfish and shrimp larvae production. Dataset.

description: MySQL files containing abstracts from World aquaculture society, European aquaculture society and International fish & shellfish larviculture symposia. Most abstracts are also freely available at the symposia websites. See Hansen and Møller (2021), DOI: 10.1111/are.15460. Users must present approvals from the three societies in order to get access to these data. Please contact moller@ruc.dk for further information,
description: The study was supported by Innovation Fund Denmark, projects IMProvement of Aquaculture high quality fish fry production—IMPAQ grant (J. no. 10-093522) and COpepod egg Mass production in Aquaculture -COMA grant (J. no. 67-2013-1) to B.W.H.
DOI: 10.5281/zenodo.4906450
title: Review: A bibliometric survey of live feed for marine finfish and shrimp larvae production. Dataset.

description: MySQL files containing abstracts from World aquaculture society, European aquaculture society and International fish & shellfish larviculture symposia. Most abstracts are also freely available at the symposia websites. See Hansen and Møller (2021), DOI: 10.1111/are.15460. Users must present approvals from the three societies in order to get access to these data. Please contact moller@ruc.dk for further information,
description: The study was supported by Innovation Fund Denmark, projects IMProvement of Aquaculture high quality fish fry production—IMPAQ grant (J. no. 10-093522) and COpepod egg Mass production in Aquaculture -COMA grant (J. no. 67-2013-1) to B.W.H.
DOI: 10.5281/zenodo.3862966
title: Learning to embed lifetime social behavior from interaction dynamics - Data

description: <strong>Interaction matrices and metadata used in "Learning to embed lifetime social behavior from interaction dynamics"</strong> The following files are included: interactions_bn16_sparse.npz and interactions_bn19_sparse.npz: These are the interaction affinity matrices for the BN16 and BN19 datasets as described in the publication. The data is stored as compressed sparse tensors with time on the first, and the individuals on the second and third dimensions. The data was stored using the pydata/sparse library 0.9.1 alive_bn16.csv and alive_bn19.csv: These files contain the dates of emergence (also corresponding to the dates they were introduced into the colonies) and heuristically determined number days alive for all individuals in the interaction matrices. Death dates were determined using a bayesian changepoint model and the number of daily detections of each individual rhythmicity_bn16.csv and rhythmicity_bn19.csv: These files contain the circadian rhythmicity values used in the evaluation of the method. The circadian rhythmicity is the \(R^2\) value of a sine with a 24 hour period fitted to the individuals' movement velocities over a three day window indices_bn16.csv and indices_bn19.csv: These files contain the mapping between the original marker IDs used during the recording of the data (which has gaps, because not all markers were used) and the sequential indices used in the interaction matrices. These files can therefore be used to look up the original ID of an individual based on it's index in the interaction matrix and vice versa time_spent_on_substrates.csv: This data was used for the mapping from factors to the proportion of time spent on various cell substrates (Figure 5). The positions of the individuals were accumulated by minute, and the column "location_descriptor_count" contains the total number of minutes on the respective day that the individual was detected See 10.1101/2020.05.06.076943 for more details about the bayesian changepoint model, circadian rhythmicity calculation, and location mapping.
DOI: 10.5281/zenodo.5243184
title: GAP interatomic potential for amorphous carbon

description: <strong>Gaussian approximation potential</strong> (GAP) for <strong>amorphous carbon</strong> [1]. It has been fitted with <strong>QUIP/GAP</strong> [1,2] by recomputing the <strong>a-C database of Deringer and Csányi</strong> [3] at the <strong>PBE+MBD</strong> level of theory [4,5] using the VASP code [6,7,8]. This potential uses <strong>2-body</strong> (distance_2b) and <strong>3-body</strong> (angle_3b) descriptors [3] plus <strong>SOAP-type descriptors</strong> (soap_turbo) [9,10], as implemented in the <strong>TurboGAP</strong> code [11]. The files can be used both with QUIP/GAP (compiled with the TurboGAP libraries) and TurboGAP. More details will follow in a scientific publication in due course (bibligraphical data will be added as it becomes available). Changes introduced in version 2 of this potential: More dimer configurations More graphite configurations A tabulated "core potential" to account for short-range repulsion and long-range dispersion interactions explicitly <strong>References</strong> A.P. Bartók, M.C. Payne, R. Kondor, and G. Csányi. Phys. Rev. Lett. 104, 136403 (2010). LibAtoms: https://libatoms.github.io V.L. Deringer and G. Csányi. Phys. Rev. B 95, 094203 (2017). J.P. Perdew, K. Burke, and M. Ernzerhof. Phys Rev. Lett. 77, 3865 (1996). A. Tkatchenko, R.A. Di Stasio, R. Car, and M. Scheffler, Phys. Rev. Lett. 108, 236402 (2012). VASP: http://vasp.at G. Kresse and J. Furthmüller. Phys. Rev. B 54, 11169 (1996). T. Bucko, S. Lebègue, T. Gould, and J.G. Ángyán, J. Phys.: Condens. Matter 28, 045201 (2016). A.P. Bartók, R. Kondor, and G. Csányi. Phys. Rev. B 87, 184115 (2013). M.A. Caro. Phys. Rev. B 100, 024112 (2019). TurboGAP: http://turbogap.fi
DOI: 10.5281/zenodo.4000210
title: GAP interatomic potential for amorphous carbon

description: <strong>Gaussian approximation potential</strong> (GAP) for <strong>amorphous carbon</strong> [1]. It has been fitted with <strong>QUIP/GAP</strong> [1,2] by recomputing the <strong>a-C database of Deringer and Csányi</strong> [3] at the <strong>PBE+MBD</strong> level of theory [4,5] using the VASP code [6,7,8]. This potential uses <strong>2-body</strong> (distance_2b) and <strong>3-body</strong> (angle_3b) descriptors [3] plus <strong>SOAP-type descriptors</strong> (soap_turbo) [9,10], as implemented in the <strong>TurboGAP</strong> code [11]. The files can be used both with QUIP/GAP (compiled with the TurboGAP libraries) and TurboGAP. More details will follow in a scientific publication in due course (bibligraphical data will be added as it becomes available). Changes introduced in version 2 of this potential: More dimer configurations More graphite configurations A tabulated "core potential" to account for short-range repulsion and long-range dispersion interactions explicitly <strong>References</strong> A.P. Bartók, M.C. Payne, R. Kondor, and G. Csányi. Phys. Rev. Lett. 104, 136403 (2010). LibAtoms: https://libatoms.github.io V.L. Deringer and G. Csányi. Phys. Rev. B 95, 094203 (2017). J.P. Perdew, K. Burke, and M. Ernzerhof. Phys Rev. Lett. 77, 3865 (1996). A. Tkatchenko, R.A. Di Stasio, R. Car, and M. Scheffler, Phys. Rev. Lett. 108, 236402 (2012). VASP: http://vasp.at G. Kresse and J. Furthmüller. Phys. Rev. B 54, 11169 (1996). T. Bucko, S. Lebègue, T. Gould, and J.G. Ángyán, J. Phys.: Condens. Matter 28, 045201 (2016). A.P. Bartók, R. Kondor, and G. Csányi. Phys. Rev. B 87, 184115 (2013). M.A. Caro. Phys. Rev. B 100, 024112 (2019). TurboGAP: http://turbogap.fi
DOI: 10.5517/ccdc.csd.cc277k24
title: CCDC 2062835: Experimental Crystal Structure Determination

description: Related Article: Mert Olgun Karataş, Namık Özdemir, Melda Sarıman, Selami Günal, Engin Ulukaya, İsmail Özdemir|2021|Dalton Trans.|50|11596|doi:10.1039/D1DT02008K
DOI: 10.5517/ccdc.csd.cc27937x
title: CCDC 2064328: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc27938y
title: CCDC 2064329: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc27939z
title: CCDC 2064330: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793b0
title: CCDC 2064331: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793c1
title: CCDC 2064332: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793d2
title: CCDC 2064333: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793f3
title: CCDC 2064334: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793g4
title: CCDC 2064335: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793h5
title: CCDC 2064336: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793j6
title: CCDC 2064337: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793k7
title: CCDC 2064338: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793l8
title: CCDC 2064339: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793m9
title: CCDC 2064340: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793nb
title: CCDC 2064341: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793pc
title: CCDC 2064342: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793qd
title: CCDC 2064343: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793rf
title: CCDC 2064344: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793sg
title: CCDC 2064345: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793th
title: CCDC 2064346: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793vj
title: CCDC 2064347: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793wk
title: CCDC 2064348: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793xl
title: CCDC 2064349: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793ym
title: CCDC 2064350: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc2793zn
title: CCDC 2064351: Experimental Crystal Structure Determination

description: Related Article: Hao Fu, Xin Wu, Wei-Hui Fang, Lei Zhang, Fei Wang, Jian Zhang|2021|Inorg.Chem.Front.|8|4102|doi:10.1039/D1QI00779C
DOI: 10.5517/ccdc.csd.cc27dbbb
title: CCDC 2067431: Experimental Crystal Structure Determination

description: Related Article: Di Wu, Bei Zhang, Qichao Yao, Baohong Hou, Lina Zhou, Chuang Xie, Junbo Gong, HongXun Hao, Wei Chen|2021|Cryst.Growth Des.|21|4531|doi:10.1021/acs.cgd.1c00415
DOI: 10.5517/ccdc.csd.cc27lq8v
title: CCDC 2073567: Experimental Crystal Structure Determination

description: Related Article: Krishnamoorthy Paramasivam, Carina B. Fialho, Tiago F. C. Cruz, Ana I. Rodrigues, Bruno Ferreira, Clara S. B. Gomes, Diogo Vila-Viçosa, Ana Charas, José M. S. S. Esperança, Luís F. Vieira Ferreira, Maria José Calhorda, António L. Maçanita, Jorge Morgado, Pedro T. Gomes|2021|Inorg.Chem.Front.|8|3960|doi:10.1039/D1QI00403D