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Analytical Chemistry

Summary:

Analytical chemistry is one of the oldest scientific disciplines and an interdisciplinary science, combining methods of physical, inorganic and organic chemistry. Analytical chemistry aims to acquire, process, and evaluate signals to qualify and quantify the composition and to unravel the structure of matter. The analytical chemist applies classical (wet) chemistry and instrumental methods for separation, identification (qualification) and quantification. The discipline is related to many research fields in life, environmental, earth, and engineering sciences, such as metabolomics, medicine, and geochemistry.
A typical workflow begins with the conceptualisation of the research question, and the planning of experiments, methods, and surveys to evaluate the hypotheses. Surveys are utilised in life, environmental, and earth sciences to perform experiments and/or to obtain samples required to support the research (e.g., laboratory and field campaigns, cohort studies). Experiments are conducted and samples are processed applying existing or newly established methods along with recording of accompanying metadata. Analytical chemistry applies already in the experimental or sampling stage as conditions need to be controlled or metadata has to be acquired (e.g., pH, temperature, colour). Once the product of the experiment or sample processing is obtained, it is analysed with suitable direct or combined methods for identification and quantification. Processing and interpretation of the acquired research data and metadata support the answering of the research question and decisions for further experiments, research, and measures.

Type of experiments for chemical analysis

Sampling

  • Collecting of materials for analysis
  • Transport and storage without alteration of samples
  • Small-scale experiments to develop / optimise approaches and equipment
  • Upscaling of methods to obtain sufficient material for a comprehensive analysis

Sample processing

  • Preparation of the sample for analysis:
    • Direct methods: no further treatment (e.g., pH, RFA, MALDI, direct infusion)
    • Single methods:
      • Dissolving
      • Extraction
      • Pulverising
    • Combined methods:
      • Extraction and enrichment (e.g., solid-phase extraction, aqua regia digestion, volatilisation of solvents)
      • Separation of interfering compounds (e.g., chromatography, precipitation)
      • Chemical transforming in measurable form (e.g., complexing, derivatisation)
  • Small-scale experiments for screening / optimization of separation conditions and upscaling

Determination and evaluation

  • Product characterisation with feasible methods (e.g., NMR spectroscopy, mass spectrometry, IR spectroscopy, UV/vis spectroscopy, elemental analysis)
    • to identify analytes (targeted and non-targeted)
    • to assess the constitution of mixtures
    • to quantify analytes

Planning of experiments

  • New and reused analytical methods and research ideas are derived from previous work of the own research group, scientific literature, datasets published in repositories, and requirements of public calls for research, development and demonstration projects.
  • Experimental design follows a logical order to achieve a specific goal, such as analytical selectivity and sensitivity, or in the case of a non-targeted analysis (e.g., in metabolomics), a coverage of a broad physical-chemical domain of analytes.
  • Planning is concluded by adding the experimental details. All metadata is documented in an ELN (e.g., Chemotion ELN) including references.

Documentation of experiments

  • Documentation of research data and metadata is carried out digitally using an ELN.
  • Experimental conditions (e.g., solvents, temperature, duration, pressure) are noted in the ELN and if available a laboratory information system.
  • Observations and results of analytical methods with no digital output (i.e. no data files) are added manually to the ELN entry of the experiment, which may include temperatures, or the pH (with metadata where applicable).
  • Obtained data from analytical instruments (e.g., NMR, MS, or IR data) are uploaded to the Chemotion ELN in open file formats and directly attached to the respective ELN experiment entry including instrumental setup metadata.
  • In case instrumental metadata is not convertible to open format without information loss, conditions need to be documented in the ELN.
  • Metadata related to the obtained data, such as mass, volumes, or solvent of measurement, have to be provided according to metadata standards.

Data producing methods

  • Data can be collected during the experiment or after the experiment by analysing the obtained product.
  • Manually determined data: Experimental observations, mass, volumes, pH, etc.
  • Digital data are obtained with analytical instruments. An overview of file extensions, file sizes, and converters for several analytical methods is given in the table below.
  • Raw data files in proprietary file formats should be saved alongside interoperable open file formats by using converters or the analytical device software. If no specific open format is currently available, export as .txt or .csv is recommended. Please be aware that metadata included in the header of .txt or .csv files may not follow a defined (open) format and metadata should be additionally also added into the ELN.
Click to filter:
Analytical methodExemplary proprietary file extensionsTypical size of proprietary fileConverterf to open file formatRecommendation for open file extension*File formatFile size of open formatMonomer characterizationPolymer characterization
NMR spectroscopyset of files, no typical extension<1-50 MBnmrium.org.jdx
.zip
JCAMP-DX (raw)
NMReDATA (assignments)
<1-50 MB
Mass spectrometry.raw
.d
.baf
~250 MBProteowizard.mzMLmzML~250 MB
IR spectroscopy.ispd
.icIR
<1 MB.dxJCAMP-DX<1 MB
Raman spectroscopy.dpt
.spc
.icRaman
.sps
.acs
<1 MBproprietary software.dxJCAMP-DX<1 MB
UV/vis spectroscopy.dsw
.str
.bsk
.bkn
.ksd
.jws
.jwb
.str8
.spc
.sre
<1 MBproprietary software.csvcomma-separated values<1 MB
Fluorescence spectroscopy.fds
.fs2f
.jws
.opj
<1 MBproprietary software.dxJCAMP-DX<1 MB
Single crystal XRD.raw~1 GBproprietary software.cifcrystallographic information file<1 MB
Powder XRD.raw<1 MBproprietary software.xydtext file<1 MB
Gas chromatography.gcd
.d
~2 MBproprietary software.txttext file<1 MB
HPLC.xls<1 MBproprietary software.csvcomma-separated values<1 MB
Cyclic voltammetry.nox
.pssession
~8 MBproprietary software.txttext file<1 MB
EPR spectroscopy.spe<1 MBproprietary software.txttext file<1 MB
Differential scanning calorimetry.ngb-dsu
.ngb-taa
<1 MBproprietary software.csvcomma-separated values<1 MB
Elemental analysisproprietary software.txttext file<1 MB
Physisorption.smp<1 MBproprietary software.csvcomma-separated values<1 MB
*This table will be continuously updated with new recommendations on interoperable open file formats.

Data analysis

  • Research data can be processed, analysed and compared (also to data of other experiments) within the Chemotion ELN.
  • Optionally, preprocessing of digital data with software of analytical device before data are transferred to the Chemotion ELN (cf. data producing methods).
  • A detailed view, evaluation and interpretation of results is carried out with the Chemotion ELN features.

Publishing research data

  • In addition to a research article in a scientific journal, the underlying research data are published in a repository and linked to the article to realise research data management according to the FAIR data principles (Best practice examples).
  • Data publications in repositories include raw and processed data for reuse.
  • The use of the Chemotion ELN enables a direct transfer of research data and the respective metadata to the Chemotion Repository. Subsequently, these data are automatically shared with other repositories, e.g. PubChem. For the publication of research data in other discipline-specific repositories, such as the MassBank for reference mass spectra, data have to be exported from the Chemotion ELN and submitted to the respective database.
  • A persistent identifier (e.g., DOI) is generated for a dataset by a repository (e.g., DataCite for the Chemotion Repository), which is given in the journal article or corresponding supporting information to link the data publication with the manuscript.