cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.58032/agh/pdodwg
title: Role of foreign phases, synergistic effects, and morphology in the HER performance of trimetallic pentlandites with une-quimolar Co:Fe:Ni ratio - research data

description: Since pentlandites are among the most promising catalysts for hydrogen evolution reactions (HER), in this study, we investigated the influence of different cobalt, iron, and nickel substitutions in the cationic sublattice and the form of the material (powder, ingot, sintered pellet) on catalytic performance. This complements previous results regarding a multi-component approach in these chalcogenides. It was shown that in the case of sulfur-rich pentlandites with non-equimolar ratio of Co, Fe, and Ni, the impact of intrinsic material properties is smaller than surface-related effects. Among powder forms, catalysts based on a combination of Fe and Co perform the best. However, in volumetric forms, extremely high contents of individual metals are favorable, albeit associated with active precipitations of foreign phases. The presence of these phases positively affects the recorded currents but slows down the reaction kinetics. These findings shed light on the nuanced interplay between material composition, form, and HER properties, offering insights for tailored catalyst design.
DOI: 10.15468/dl.j6y5hp
title: Occurrence Download

description: A dataset containing 1580 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Clusia panapanari (Aubl.) Choisy, Clusia microphylla Engl., Renggeria comans (Mart.) Meisn. ex Engl., Clusia colorans Engl., Clusia comans (Mart.) Pipoly, Quapoya panapanari Aubl., Renggeria littoralis Poepp., Clusia pana-panare (Aubl.) Choisy)"
 ]
}

 The dataset includes 1580 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011626-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z3fng6
title: Occurrence Download

description: A dataset containing 563 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Periclimenes yucatanicus (Ives, 1891)"
 ]
}

 The dataset includes 563 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011628-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v59qnc
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus japonicus Ishikawa, 1908",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 64 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011627-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k8whws
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-68.592 -59.037,-55.565 -59.037,-55.565 -52.093,-68.592 -52.093,-68.592 -59.037))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (December, November, October, September)",
 "TaxonKey is Lagenorhynchus obscurus (Gray, 1828)",
 "Year 2023-2024"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011629-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mntfth
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AAH8593"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011630-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xwtbwt
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myoxocephalus polyacanthocephalus (Pallas, 1814)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011631-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jtmtjf
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:ADK3076"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011634-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fc3zah
title: Occurrence Download

description: A dataset containing 816 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Clusia insignis Mart.)"
 ]
}

 The dataset includes 816 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011633-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ge23g8
title: Occurrence Download

description: A dataset containing 237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argis toyamaensis (Yokoya, 1933)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 237 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011635-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11070256
title: Data for "Unusually Low Dust Activity in North Africa in June 2023: Causes, Impacts and Future Projections"

description: Datasets for manuscript entitled "Unusually Low Dust Activity in North Africa in June 2023: Causes, Impacts and Future Projections"
DOI: 10.5281/zenodo.11070257
title: Data for "Unusually Low Dust Activity in North Africa in June 2023: Causes, Impacts and Future Projections"

description: Datasets for manuscript entitled "Unusually Low Dust Activity in North Africa in June 2023: Causes, Impacts and Future Projections"
DOI: 10.5281/zenodo.12644300
title: Data for "Unusually Low Dust Activity in North Africa in June 2023: Causes, Impacts and Future Projections"

description: Datasets for manuscript entitled "Unusually Low Dust Activity in North Africa in June 2023: Causes, Impacts and Future Projections"
DOI: 10.6084/m9.figshare.25423291
title: <b>Supporting Information for the paper: </b>Detection of functional diversity patterns and their geoclimatic filters is sensitive to data types (occurrence vs. abundance) and spatial scales (sites vs. regions). Plant Diversity. 10.1016/j.pld.2024.06.004

description: This repository contains spreadsheets with the references used to compile trait and species composition data (occurrence and abundance) of the Atlantic Forest woody flora in South America, among other information.Description of files:(1) "references-composition-compilation.xlsx": This file contains information about the studies used to compile species composition data (occurrence and abundance) used in the main analyses, among other information.(2) "references_trait_compilation.xlsx": This file contains the references used to compile data from the seven target traits, used in the main analyses, and three additional traits, used exclusively in the trait data cleaning process, among other information.(3) "trait-coverage.xlsx": This file contains information about local trait coverages and relative species richness per site in the occurrence and abundance datasets, among other information.
DOI: 10.6084/m9.figshare.26176950
title: Bioactivation and reactivity research advances–2023 year in review

description: Advances in the field of bioactivation have significantly contributed to our understanding and prediction of drug-induced liver injury (DILI). It has been established that many adverse drug reactions, including DILI, are associated with the formation and reactivity of metabolites. Modern methods allow us to detect and characterize these reactive metabolites in earlier stages of drug development, which helps anticipate and circumvent the potential for DILI. Improved <i>in silico</i> models and experimental techniques that better reflect in vivo environments are enhancing predictive capabilities for DILI risk. Further, studies on the mechanisms of bioactivation, including enzyme interactions and the role of individual genetic differences, have provided valuable insights for drug optimizations. Cumulatively, this progress is continually refining our approaches to drug safety evaluation and personalized medicine. Shuai Wang and Cyrus Khojasteh, on behalf of the authors.
DOI: 10.6084/m9.figshare.26176950.v1
title: Bioactivation and reactivity research advances–2023 year in review

description: Advances in the field of bioactivation have significantly contributed to our understanding and prediction of drug-induced liver injury (DILI). It has been established that many adverse drug reactions, including DILI, are associated with the formation and reactivity of metabolites. Modern methods allow us to detect and characterize these reactive metabolites in earlier stages of drug development, which helps anticipate and circumvent the potential for DILI. Improved <i>in silico</i> models and experimental techniques that better reflect in vivo environments are enhancing predictive capabilities for DILI risk. Further, studies on the mechanisms of bioactivation, including enzyme interactions and the role of individual genetic differences, have provided valuable insights for drug optimizations. Cumulatively, this progress is continually refining our approaches to drug safety evaluation and personalized medicine. Shuai Wang and Cyrus Khojasteh, on behalf of the authors.
DOI: 10.5281/zenodo.12644136
title: Top-down vs. bottom-up synthesis of Ga based supported catalytically active liquid metal solutions (SCALMS) for the dehydrogenation of isobutane
DOI: 10.5281/zenodo.12644137
title: Top-down vs. bottom-up synthesis of Ga based supported catalytically active liquid metal solutions (SCALMS) for the dehydrogenation of isobutane
DOI: 10.15468/dl.dx8pc9
title: Occurrence Download

description: A dataset containing 1601 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Petrochirus diogenes (Linnaeus, 1758)"
 ]
}

 The dataset includes 1601 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011636-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10521607
title: Data for Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents

description: Full set of data related to the publication "Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents", published in ACS Nano with DOI:10.1021/acsnano.4c01950

 Full details on data treatment and logging are included in the file "DataLogging.pdf". All data use ASCII encoding in delimited .txt files.
DOI: 10.5281/zenodo.10521608
title: Data for Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents

description: Full set of data related to the publication "Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents", published in ACS Nano with DOI:10.1021/acsnano.4c01950

 Full details on data treatment and logging are included in the file "DataLogging.pdf". All data use ASCII encoding in delimited .txt files.
DOI: 10.5281/zenodo.11358277
title: High-resolution harvester data for estimating rolling resistance and forest trafficability

description: This study describes an extensive, high-resolution data on rolling resistance coefficient collected in a boreal forest landscape in Southern Finland during the non-frost period of 2021, covering roughly 50~km of harvester routes and used in the following study:

Salmivaara, A., Holmström, E., Kulju, S., Ala-Ilomäki, J., Virjonen, P., Nevalainen, P., Heikkonen, J., and Launiainen, S. 2024.High-resolution harvester data for estimating rolling resistance and forest trafficability. European Journal of Forest Reseach. doi: 10.1007/s10342-024-01717-6

The coordinates are in metric system, and the relative position between sites are maintained. However, they have been converted and do not refer to actual locations.

Two datasets collected by a Ponsse Ergo harvester are available: 

1) All non-frost period of 2021, with 8m*8m grid means of rolling resistance ('grid mean rr'), along with grid mean longitudinal inclination of the machine ('grid mean pitch'), time, topographic wetness index ('twi') and binary indication whether a road is within 4m radius from the grid centerpoint ('roads'). 

2) Data including all 11 test sites with all first pass harvester machine data ('time', 'E_conv', 'N_conv', 'dtorq', 'drpm', 'peng', 'cooling', 'phydr', 'pwheels', 'v_ms', 'fmotive', 'slopeforce', 'normalforce', 'pitch', 'rr') and grid means of spatial data ('grid', 'grid mean rr', 'grid mean pitch', 'roads', 'site', 'slope_deg_terrain', 'bmroot_all'. 'c_bmroot_ratio', 'broadlv_rootbm_ratio', 'p_bmroot_ratio','s_bmroot_ratio', 'age', 'diameter', 'standheight', 'b_vol', 'b_pulp_vol', 'b_timber_vol', 's_vol', 's_pulp_vol', 's_timber_vol', 'p_vol', 'p_pulp_vol', 'p_timber_vol', 'broadlv_vol','broadlv_pulp_vol', 'broadlv_timber_vol', 'canopy_cov', 'broadlv_canopy_cov', 'ba', 'volume', 'dem', 'devMeanElev16', 'devMeanElev8', 'diffMeanElev8', 'erosion risk', 'tri', 'roughness_mag', 'roughness_scale', 'dtw00_5ha', 'dtw_01_0ha', 'dtw_04_0ha', 'dtw_10_0ha', 'twi', 'sat_deficit_doy', vol_moisture_doy, 'bare_rock_areas', 'lakes', 'streams', 'peat', 'topsoil', 'aspect', 'aspect_sin', 'aspect_cos', 'main_class_fertility_class_comb')
DOI: 10.15468/dl.6qsckn
title: Occurrence Download

description: A dataset containing 314 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Calophyllum longifolium Willd.)"
 ]
}

 The dataset includes 314 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011637-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.crna5x
title: Occurrence Download

description: A dataset containing 183 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Haliotis diversicolor Reeve, 1846",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 183 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011638-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12635302
title: IAM_COMPACT_NDCs_LTTs_Database

description: This dataset contains Nationally Determined Contributions (NDCs) for 2030, and new long-term strategies (LTSs) for 2050, which were put in place in the run-up to, during, and after the COP26 conference. 



NDC targets reflect the level of short-term ambition to which most countries are dedicated to through law or policy, but with risks of falling short if dedication is not high enough and/or changes occur in the political landscape.

Long-term targets (LTT) reflect the level of longer-term ambition which many countries have stated to fulfil their part in mitigating climate change, but in most cases not backed with an actual policy agenda. These will come on top of pledged NDC targets, to create another increased level of proposed ambition. These pledges will be included for each separate model region as a linear pathway from the 2030 NDC target (NDC_LTT).
DOI: 10.15468/dl.rh9vp5
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Petrochirus bahamensis (J.F.W.Herbst, 1791)"
 ]
}

 The dataset includes 62 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011639-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14272/dummy/chmo0000630.2
title: infrared absorption spectroscopy (IR) ()

description: dataset for infrared absorption spectroscopy (IR)
DOI: 10.14272/dummy.7

description: This is a physical chemical entity[CHEBI_24431] which was not directly associated with a molecule[CHEBI_25367].
 The physical chemical entity[CHEBI_24431] can be described by the molecular mass descriptor [cheminf_000088]: 0.0.
 
 The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]:
 
 The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-38872

 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]:
 Melting point descriptor[CHEMINF_000256]: 
 Boiling point descriptor[CHEMINF_000257]: 
 Refractive index descriptor[CHEMINF_000253]:

 The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]:
 
 CHMO:0000470 | mass spectrometry (MS)
 
 CHMO:0000630 | infrared absorption spectroscopy (IR)
 
 The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: 

 Used ontologies:
 CHEBI - Chemical Entities of Biological Interest
 CHEMINF - chemical information ontology (information entities about chemical entities)
 CHMO - Chemical Methods Ontology
 OBI - Ontology for Biomedical Investigations
DOI: 10.14272/dummy/chmo0000470
title: mass spectrometry (MS) ()

description: dataset for mass spectrometry (MS)
DOI: 10.5281/zenodo.12644199
title: Data for: Cationic Polaron Delocalization in Porphyrin Nanoribbons

description: The xyz coordinates for the calculated geometries (B3LYP/6-31G*) of radical cations PN·+ for N = 1, 2, 3, 4, 6, 10, 14 and 18.
DOI: 10.5281/zenodo.12644200
title: Data for: Cationic Polaron Delocalization in Porphyrin Nanoribbons

description: The xyz coordinates for the calculated geometries (B3LYP/6-31G*) of radical cations PN·+ for N = 1, 2, 3, 4, 6, 10, 14 and 18.
DOI: 10.14272/cdwxnrcewcygqr-uhfffaoysa-l/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2

description: dataset for mass spectrometry (MS)
DOI: 10.14272/cdwxnrcewcygqr-uhfffaoysa-l/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/cdwxnrcewcygqr-uhfffaoysa-l/chmo0000597
title: 19F nuclear magnetic resonance spectroscopy (19F NMR) ()
title: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2

description: dataset for 19F nuclear magnetic resonance spectroscopy (19F NMR)
DOI: 10.14272/cdwxnrcewcygqr-uhfffaoysa-l/chmo0001075
title: elemental analysis (EA) ()
title: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2

description: dataset for elemental analysis (EA)
DOI: 10.14272/cdwxnrcewcygqr-uhfffaoysa-l.1
title: C32H30Ag2F6N10O4
title: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367].
 The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]:
 InChI descriptor[cheminf_000113]: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2, and canonical SMILES descriptor[cheminf_000007]: [O-]C(=O)C(F)(F)F.[O-]C(=O)C(F)(F)F.CCCCc1nnn(c1)c1cnc2c(n1)cccc2.CCCCc1nnn(c1)c1cnc2c(n1)cccc2.[Ag+].[Ag+], and by the IUPAC name[cheminf_000107]: .
 
 The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]:
 
 The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-37067

 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]:
 Melting point descriptor[CHEMINF_000256]: 
 Boiling point descriptor[CHEMINF_000257]: 
 Refractive index descriptor[CHEMINF_000253]:

 The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]:
 
 CHMO:0000597 | 19F nuclear magnetic resonance spectroscopy (19F NMR)
 
 CHMO:0000470 | mass spectrometry (MS)
 
 CHMO:0000630 | infrared absorption spectroscopy (IR)
 
 CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR)
 
 CHMO:0001075 | elemental analysis (EA)
 
 The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: 

 Used ontologies:
 CHEBI - Chemical Entities of Biological Interest
 CHEMINF - chemical information ontology (information entities about chemical entities)
 CHMO - Chemical Methods Ontology
 OBI - Ontology for Biomedical Investigations
DOI: 10.14272/cdwxnrcewcygqr-uhfffaoysa-l/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/2C14H15N5.2C2HF3O2.2Ag/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;2*3-2(4,5)1(6)7;;/h2*4-5,7-10H,2-3,6H2,1H3;2*(H,6,7);;/q;;;;2*+1/p-2

description: dataset for infrared absorption spectroscopy (IR)
DOI: 10.14272/gqjlhayeuvuosm-uhfffaoysa-j/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/2C14H15N5.4ClH.2Pd/c2*1-2-3-6-11-10-19(18-17-11)14-9-15-12-7-4-5-8-13(12)16-14;;;;;;/h2*4-5,7-10H,2-3,6H2,1H3;4*1H;;/q;;;;;;2*+2/p-4

description: dataset for infrared absorption spectroscopy (IR)
DOI: 10.14272/sa-fuhff-uhfffadpsc-gqjlhayeuv-uhfffadpsc-nuhff-juhff-nuhff-zzz/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR)
title: reaction/SA-FUHFF-UHFFFADPSC-GQJLHAYEUV-UHFFFADPSC-NUHFF-JUHFF-NUHFF-ZZZ

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)