Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Random and Systematic Errors01:20

Random and Systematic Errors

14.2K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
14.2K
Genome Copying Errors02:46

Genome Copying Errors

4.9K
DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
4.9K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.2K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.2K
Contaminants and Errors01:16

Contaminants and Errors

299
Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
299
Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

1.1K
In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
1.1K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

98.8K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
98.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Vibrational Stabilization in Cyclacene Carbon Nanobelts.

The journal of physical chemistry. A·2025
Same author

Catalysis enabled synthesis, structures, and reactivities of fluorinated S<sub>8</sub>-corona[<i>n</i>]arenes (<i>n</i> = 8-12).

Chemical science·2023
Same author

Static Electron Correlation in Anharmonic Molecular Vibrations: A Hybrid TAO-DFT Study.

The journal of physical chemistry. A·2022
Same author

Wavelength dependent photoextrusion and tandem photo-extrusion reactions of ninhydrin bis-acetals for the synthesis of 8-ring lactones, benzocyclobutenes and orthoanhydrides.

Chemical communications (Cambridge, England)·2022
Same author

Kernel Methods for Predicting Yields of Chemical Reactions.

Journal of chemical information and modeling·2021
Same author

Computational chemistry experiments performed directly on a blockchain virtual computer.

Chemical science·2021

Related Experiment Video

Updated: Dec 12, 2025

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.4K

Calculating with Permanent Marker: How Blockchains Record Immutable Mistakes in Computational Chemistry.

Magnus W D Hanson-Heine1, Alexander P Ashmore2

  • 1School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.

The Journal of Physical Chemistry Letters
|August 14, 2020
PubMed
Summary

Blockchain technology enhances scientific transparency and reproducibility. However, its immutable ledger preserves calculation errors, offering unique insights into scientific error correction processes for carbon monoxide simulations.

More Related Videos

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.9K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.6K

Related Experiment Videos

Last Updated: Dec 12, 2025

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.4K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.9K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.6K

Area of Science:

  • Computational science
  • Blockchain technology
  • Environmental science

Background:

  • Open blockchain environments offer enhanced transparency, reproducibility, and censorship resistance for computational science experiments.
  • The immutable, append-only nature of blockchains presents challenges for correcting historical calculation errors.

Purpose of the Study:

  • To demonstrate the utility of blockchain for preserving the scientific process of error correction.
  • To showcase the application of this method in simulations of carbon monoxide.

Main Methods:

  • Utilizing an open blockchain environment for computational science experiments.
  • Conducting simulations of carbon monoxide (CO).
  • Leveraging the append-only ledger to record and preserve error correction data.

Main Results:

  • Demonstrated the feasibility of using blockchain for computational science.
  • Successfully preserved historical data related to calculation errors and their correction.
  • Provided a transparent record of the scientific process for CO simulations.

Conclusions:

  • Blockchain technology can be effectively applied to computational science, enhancing transparency and reproducibility.
  • The immutability of blockchain, while posing error correction challenges, uniquely preserves the scientific process of error identification and correction.
  • This approach offers valuable, otherwise unavailable data on scientific error correction, as exemplified by carbon monoxide simulations.