cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3588336
title: Molecules generated with G-SchNet (QCArchive View Formatted)

description: Data curated by the QCArchive team, originally sourced from quantum-machine.org. Molecules (not in QM9) generated by G-SchNet, trained on QM9. Geometries are relaxed at the B3LYP/6-31G(2d,p) level of theory. For more information, see http://qcarchive.molssi.org/apps/ml_datasets/.
description: {"references": ["Gebauer, N. W. A.; Gastegger, M. & Sch\u00fctt, K. T. Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules. arXiv:1906.00957, 2019 https://arxiv.org/abs/1906.00957"]}
DOI: 10.18716/nmrshiftdb2/21619
title: NMR data for (3-chloro-5-methoxy-phenyl) [(Z)-(1-propenyl)] ether); (3-chloro-5-methoxy-phenyl) [(Z)-(prop-1enyl)] ether
DOI: 10.5281/zenodo.3588337
title: QM7 (QCArchive View Formatted)

description: Data curated by the QCArchive team, originally sourced from qmml.org and quantum-machine.org. Small organic molecules with up to 7 heavy atoms, sampled from GDB-13 and optimized at the PBE0 level of theory. All molecules are neutral singlets. For more information, see http://qcarchive.molssi.org/apps/ml_datasets/.
description: {"references": ["Blum, L. C. & Reymond, J.-L. 970 million druglike small molecules for virtual screening in the chemical universe database GDB-13. JACS, 2009, 131, 8732-8733. https://pubs.acs.org/doi/abs/10.1021/ja902302h", "Rupp, M.; Tkatchenko, A.; M\u00fcller, K.-R. & von Lilienfeld, O. A. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning. Phys. Rev. Lett., 2012, 108, 058301. https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.058301"]}
DOI: 10.5281/zenodo.3588338
title: GDB13-T (QCArchive View Formatted)

description: Data curated by the QCArchive team, originally sourced from data.caltech.edu. 1,000 small organic molecules with up to 13 heavy atoms sampled from GDB-13 and thermalized with 350K MD at the B3LYP/6-31g* level of theory. Energies are provided at the HF/cc-pVTZ and MP2/cc-pVTZ levels of theory. All molecules are neutral singlets. For more information, see http://qcarchive.molssi.org/apps/ml_datasets/.
description: {"references": ["Welborn, M.; Cheng, L. & Miller III, T. F. Transferability in machine learning for electronic structure via the molecular orbital basis. J. Chem. Theory Comput., 2018, 14, 4772-4779. https://pubs.acs.org/doi/abs/10.1021/acs.jctc.8b00636", "Cheng, L.; Welborn, M.; Christensen, A. S. & Miller III, T. F. A universal density matrix functional from molecular orbital-based machine learning: Transferability across organic molecules. J. Chem. Phys., 2019, 150, 131103. https://aip.scitation.org/doi/full/10.1063/1.5088393"]}
DOI: 10.7910/dvn/klogrx/1i7mjg
title: Figure1.mat

description: This is a Matlab .mat file comprising the data used for Figure 1 in the corresponding manuscript
DOI: 10.7910/dvn/klogrx/bd70je
title: Figure4.mat

description: This is a Matlab .mat file comprising the data used for Figure 4 in the corresponding manuscript
DOI: 10.7910/dvn/klogrx/fdxzsd
title: Figure3.mat

description: This is a Matlab .mat file comprising the data used for Figure 3 in the corresponding manuscript
DOI: 10.7910/dvn/klogrx/g1dmmz
title: Figure2.mat

description: This is a Matlab .mat file comprising the data used for Figure 2 in the corresponding manuscript
DOI: 10.14469/hpc/6514
title: Spectral data for 3a-3j

description: NMR spectroscopy data for isolated fluoroallyl-alcohols, 3a-3j.
DOI: 10.18716/nmrshiftdb2/21744
title: NMR data for 2-[(5-methoxy-2-thienyl)ethynyl]-5-nitrothiophene
DOI: 10.5281/zenodo.3588339
title: QM9 (QCArchive View Formatted)

description: Data curated by the QCArchive team, originally sourced from https://figshare.com/collections/Quantum_chemistry_structures_and_properties_of_134_kilo_molecules/978904. Small organic molecules with up to 9 heavy atoms sampled from GDB-17, optimized at the B3LYP/6-31G(2df,p) level of theory. Ground state, orbital, and thermodynamic properties are available (at the B3LYP/6-31G(2df,p) level). All molecules are neutral singlets. For more information, see http://qcarchive.molssi.org/apps/ml_datasets/.
description: {"references": ["Blum, L. C. & Reymond, J.-L. 970 million druglike small molecules for virtual screening in the chemical universe database GDB-13. JACS, 2009, 131, 8732-8733. https://pubs.acs.org/doi/abs/10.1021/ja902302h", "Ramakrishnan, R.; Dral, P. O.; Rupp, M. & Von Lilienfeld, O. A. Quantum chemistry structures and properties of 134 kilo molecules. Sci. Data, 2014, 1, 140022. https://www.nature.com/articles/sdata201422"]}
DOI: 10.5281/zenodo.3588340
title: QM7b (QCArchive View Formatted)

description: Data curated by the QCArchive team, originally sourced from qmml.org and quantum-machine.org. Small organic molecules with up to 7 heavy atoms, sampled from GDB-13 and optimized at the PBE0 level of theory. Ground and excited state properties are evaluated at the PBE0, ZINDO, and GW levels of theory. For more information, see http://qcarchive.molssi.org/apps/ml_datasets/.
description: {"references": ["Blum, L. C. & Reymond, J.-L. 970 million druglike small molecules for virtual screening in the chemical universe database GDB-13. JACS, 2009, 131, 8732-8733. https://pubs.acs.org/doi/abs/10.1021/ja902302h", "Montavon, G.; Rupp, M.; Gobre, V.; Vazquez-Mayagoitia, A.; Hansen, K.; Tkatchenko, A.; M\u00fcller, K.-R. & Von Lilienfeld, O. A. Machine learning of molecular electronic properties in chemical compound space. New J. Phys., 2013, 15, 095003. https://iopscience.iop.org/article/10.1088/1367-2630/15/9/095003/meta"]}
DOI: 10.5281/zenodo.3588341
title: COMP6 (QCArchive View Formatted)

description: Data curated by the QCArchive team, originally sourced from https://github.com/isayev/COMP6. For more information, see http://qcarchive.molssi.org/apps/TODO.
DOI: 10.5519/qd.tdi9zagc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4131 records)
DOI: 10.14469/hpc/6515
title: DFT coordinate files for reactions with 2c

description: XYZ coordinate files for fluoroallylation reaction of 2c with carbonyls. Functionals - B3LYP, B3PW91, M06L.
DOI: 10.18716/nmrshiftdb2/21660
title: NMR data for 2-bromo-5-methyl-7H-[1,3,4]thiadiazolo[3,2-a]pyrimidin-7-one
DOI: 10.18716/nmrshiftdb2/21827
title: NMR data for Pachyclavulides B
DOI: 10.7910/dvn/aynpy3/m1ubtw
title: Table 2. Statistical analysis of the research directions and the number of articles published in core journals on disease prevention campaigns in China and abroad-1.tab

description: :unav
DOI: 10.7910/dvn/aynpy3/r2jnli
title: Figure 1. Seven-step process for screening articles published in Chinese core journals.jpg

description: :unav
DOI: 10.7910/dvn/aynpy3/wa1tdw
title: Table 1. Examples of the use of campaign and Chinese translations of the term in Chinese journal articles.tab

description: :unav
DOI: 10.7910/dvn/il0lue/lauy68
title: product_process_patents_2_ind_100_ep_nanotech.png

description: :unav
DOI: 10.7910/dvn/il0lue/lmsdmk
title: product_process_patents_pred_ind_100_us_Handling.png

description: :unav
DOI: 10.7910/dvn/il0lue/mcdequ
title: product_process_patents_pred_100_ep_Environmental technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/rlku0e
title: product_process_patents_2_ind_100_us_Basic communication processes.png

description: :unav
DOI: 10.7910/dvn/il0lue/xmkxav
title: product_process_patents_2_ind_100_us_Computer technology.png

description: :unav
DOI: 10.5281/zenodo.3588265
title: Phenological metrics for Protected Area "Hardangervidda-h18v03", MODIS aqua tile h18v03

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588266
title: Phenological metrics for Protected Area "Hardangervidda-h18v03", MODIS aqua tile h18v03

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.7910/dvn/aynpy3/x2frrp
title: Appendix.pdf

description: :unav
DOI: 10.7910/dvn/il0lue/9s42kg
title: product_process_patents_2_100_us_A01N.png

description: :unav
DOI: 10.7910/dvn/il0lue/exinkm
title: product_process_patents_pred_ind_100_ep_antibiotics.png

description: :unav
DOI: 10.7910/dvn/il0lue/gbyxmk
title: product_process_patents_2_ind_100_us_C05.png

description: :unav
DOI: 10.7910/dvn/il0lue/lu6jsb
title: product_process_patents_abstr_us_Machine tools.png

description: :unav
DOI: 10.7910/dvn/il0lue/ouj1j3
title: product_process_patents_2_ind_100_ep_Chemical engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/pdcext
title: product_process_patents_2_100_ep_Furniture, games.png

description: :unav
DOI: 10.7910/dvn/il0lue/qcarzb
title: product_process_patents_pred_100_ep_Digital communication.png

description: :unav
DOI: 10.7910/dvn/il0lue/rtvn7u
title: product_process_patents_2_ind_100_ep_Other consumer goods.png

description: :unav
DOI: 10.7910/dvn/il0lue/xdnkrf
title: product_process_patents_2_100_us_Audio-visual technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/yvxswe
title: product_process_patents_2_ind_100_ep_Digital communication.png

description: :unav
DOI: 10.14469/hpc/6516
title: DFT coordinate files for reactions with 2d

description: XYZ coordinate files for hydrodefluorination-fluoroallylation reactions with carbonyls for 2d. Functional - B3LYP
DOI: 10.5281/zenodo.3588270
title: Additional CPT's Raw Data performed by Istanbul University-Cerrahpasa in scope of LIQUEFACT project (H2020, 700748)

description: Additional CPT's Raw Data performed by Istanbul University-Cerrahpasa in scope of LIQUEFACT project (H2020, 700748)
DOI: 10.5281/zenodo.3588271
title: Additional CPT's Raw Data performed by Istanbul University-Cerrahpasa in scope of LIQUEFACT project (H2020, 700748)

description: Additional CPT's Raw Data performed by Istanbul University-Cerrahpasa in scope of LIQUEFACT project (H2020, 700748)
DOI: 10.5281/zenodo.3588272
title: Phenological metrics for Protected Area "NorthernLimestone", MODIS terra tile h18v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588273
title: Phenological metrics for Protected Area "NorthernLimestone", MODIS terra tile h18v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588344
title: Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis

description: We release dynamical ejecta data from binary neutron star merger simulations. The outflows are extracted at a fixed coordinate sphere with radius 300 G/c^2 Msun (= 443 km). Only material unbound according to the geodesic criterion is considered to be part of the dynamical ejecta. See [1] for more details. Included data: `Table2.txt`: Table 2 of the paper in machine readable format `tabulated_nucsyn.h5`: nucleosynthesis yields from pre-computed parametrized trajectories. The first three indices of each dataset are Ye, entropy, and expansion timescale tau. For example `Y_final[iYe, ientr, itau, iiso]` gives the final abundance of isotope `iiso` with `A[iiso]` and `Z[iiso]` for a trajectory with initial Ye = `Ye[iYe]`, initial entropy `s[ientr]`, and expansion timescale `tau[itau]`. `tabulated_rho.h5`: gives the density at T = 6 GK corresponding to the Ye, entropy, and expansion timescale used in `tabulated_nucsyn.h5`. `[model].tar`: ejecta data for individual simulations. The naming convention is the same as in the paper. For each model we provide: `outflow.txt`: angle integrated outflow rate and cumulated ejecta mass. Data are given in units with Msun = G = c = 1 (eg, the conversion factor for time to seconds is 4.9258e-6). `hist_entropy.dat`: histogram of the ejecta as a function of the entropy (in kb) `hist_vinf.dat`: histogram of the ejecta as a function of the asymptotic velocity (in units of c) `hist_ye.dat`: histogram of the ejecta as a function of the electron fraction Ye. `profile.txt`: time integrated ejecta profiles as a function of the polar angle. `hist_vinf_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle. `hist_ye_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle. `hist_ye_entropy_tau.h5`: histograms of the ejecta as a function of Ye, entropy, and expansion timescale tau. Additionally we distribute: Initial data generated with LORENE and associated EOS tables. EOS tables used for the evolution Parameter file used for each simulation For the multidimensional histograms the indices are ordered as specified in the file name, ie the file `hist_ye_theta.h5` tabulates the ejecta mass as a function of Ye (first index) and polar angle theta (second index). <br> [1] D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts, <em>Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis</em>, ApJ 869:130 (2018), arXiv:1809.11161
description: {"references": ["D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts,\u00a0Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis,\u00a0ApJ 869:130 (2018),\u00a0arXiv:1809.11161"]}
DOI: 10.7910/dvn/il0lue/7knflm
title: product_process_patents_2_100_us_Macromolecular chemistry, polymers.png

description: :unav
DOI: 10.7910/dvn/il0lue/d3k9hi
title: product_process_patents_pred_ind_100_ep_F02B.png

description: :unav
DOI: 10.7910/dvn/il0lue/jxn2er
title: product_process_patents_pred_ind_100_ep_Medical technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/ncew0f
title: product_process_patents_abstr_us_Pharmaceuticals.png

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DOI: 10.7910/dvn/il0lue/oolfsc
title: product_process_patents_pred_ind_100_us_Organic fine chemistry.png

description: :unav
DOI: 10.7910/dvn/il0lue/u8aegg
title: product_process_patents_pred_100_us_smartphones.png

description: :unav
DOI: 10.7910/dvn/il0lue/uvdxt8
title: product_process_patents_pred_ind_100_us_Furniture, games.png

description: :unav
DOI: 10.7910/dvn/il0lue/dshjvw
title: product_process_patents_pred_ind_100_us_Basic materials chemistry .png

description: :unav
DOI: 10.7910/dvn/il0lue/hklakd
title: product_process_patents_pred_ind_100_ep_Telecommunications.png

description: :unav
DOI: 10.7910/dvn/il0lue/ibviil
title: product_process_patents_pred_ind_100_ep_Digital communication.png

description: :unav
DOI: 10.7910/dvn/il0lue/ixudw1
title: product_process_patents_2_100_us_Pharmaceuticals.png

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DOI: 10.7910/dvn/il0lue/jkp4fb
title: product_process_patents_pred_ind_100_us_F02B.png

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DOI: 10.7910/dvn/il0lue/msywhi
title: product_process_patents_pred_ind_100_us_A01N.png

description: :unav
DOI: 10.7910/dvn/il0lue/qum92w
title: product_process_patents_abstr_ep_F02B.png

description: :unav
DOI: 10.7910/dvn/il0lue/r9zbg7
title: product_process_patents_2_100_us_IT methods for management.png

description: :unav
DOI: 10.7910/dvn/il0lue/xfnu7m
title: product_process_patents_2_100_ep_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/3mzqsb
title: product_process_patents_pred_ind_100_us_Engines, pumps, turbines.png

description: :unav
DOI: 10.7910/dvn/il0lue/4xqiys
title: product_process_patents_2_ind_100_ep_Thermal processes and apparatus.png

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DOI: 10.7910/dvn/il0lue/7xcuyo
title: product_process_patents_2_ind_100_ep_F02B.png

description: :unav
DOI: 10.7910/dvn/il0lue/fvqu7v
title: product_process_patents_pred_100_ep_Analysis of biological materials.png

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DOI: 10.7910/dvn/il0lue/kmjo54
title: product_process_patents_2_ind_100_ep_Organic fine chemistry.png

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DOI: 10.7910/dvn/il0lue/kv3sq8
title: product_process_patents_pred_ind_100_us_Electrical machinery, apparatus, energy.png

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DOI: 10.7910/dvn/il0lue/qxjjim
title: product_process_patents_2_100_us_Control.png

description: :unav
DOI: 10.7910/dvn/il0lue/uftfkx
title: product_process_patents_pred_ind_100_us_Macromolecular chemistry, polymers.png

description: :unav
DOI: 10.7910/dvn/il0lue/v5yvbs
title: product_process_patents_2_100_ep_IT methods for management.png

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DOI: 10.7910/dvn/il0lue/w9wd0f
title: product_process_patents_2_100_ep_robotics.png

description: :unav
DOI: 10.14272/usgaesjtvoshev-uhfffaoysa-n.1
title: 4-(4'-cyanophenyl)[2.2]paracyclophane
title: InChI=1S/C23H19N/c24-16-20-9-13-22(14-10-20)23-15-19-6-5-17-1-3-18(4-2-17)7-11-21(23)12-8-19/h1-4,8-10,12-15H,5-7,11H2

description: This dataset contains experimental data from a sample (4-(5-tricyclo[8.2.2.24,7]hexadeca-1(13),4,6,10(14),11,15-hexaenyl)benzonitrile, InChI=1S/C23H19N/c24-16-20-9-13-22(14-10-20)23-15-19-6-5-17-1-3-18(4-2-17)7-11-21(23)12-8-19/h1-4,8-10,12-15H,5-7,11H2). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) fast-atom bombardment mass spectrometry (FABMS) infrared absorption spectroscopy (IR)
DOI: 10.14272/usgaesjtvoshev-uhfffaoysa-n/chmo0000563
title: fast-atom bombardment mass spectrometry (FABMS) (4-(5-tricyclo[8.2.2.24,7]hexadeca-1(13),4,6,10(14),11,15-hexaenyl)benzonitrile)
title: InChI=1S/C23H19N/c24-16-20-9-13-22(14-10-20)23-15-19-6-5-17-1-3-18(4-2-17)7-11-21(23)12-8-19/h1-4,8-10,12-15H,5-7,11H2

description: dataset for fast-atom bombardment mass spectrometry (FABMS) HRMS (C23H20N1+H+) calc. 310.1596, found 310.1594.
DOI: 10.14272/usgaesjtvoshev-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (4-(5-tricyclo[8.2.2.24,7]hexadeca-1(13),4,6,10(14),11,15-hexaenyl)benzonitrile)
title: InChI=1S/C23H19N/c24-16-20-9-13-22(14-10-20)23-15-19-6-5-17-1-3-18(4-2-17)7-11-21(23)12-8-19/h1-4,8-10,12-15H,5-7,11H2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, Chloroform-d) δ [ppm] = 7.80–7.71 (m, 2H), 7.62–7.55 (m, 2H), 6.69–6.46 (m,7H), 3.33 (ddd, J = 12.7 Hz, J = 10.0 Hz, J = 3.0 Hz, 1H), 3.24–3.10 (m, 3H), 3.11–2.84 (m,3H), 2.64 (ddd, J = 13.1 Hz, J = 10.0 Hz, J = 4.5 Hz, 1H).
DOI: 10.14272/usgaesjtvoshev-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (4-(5-tricyclo[8.2.2.24,7]hexadeca-1(13),4,6,10(14),11,15-hexaenyl)benzonitrile)
title: InChI=1S/C23H19N/c24-16-20-9-13-22(14-10-20)23-15-19-6-5-17-1-3-18(4-2-17)7-11-21(23)12-8-19/h1-4,8-10,12-15H,5-7,11H2

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (101 MHz, CDCl3) δ [ppm] = 145.9, 140.3, 140.1, 139.7, 139.6, 137.3, 136.3, 133.5, 133.4, 132.9, 132.5 (2C), 132.2, 132.0, 130.4 (2C), 129.7, 119.2, 110.6, 35.6, 35.3, 35.1, 34.1.