Evidence map›Paper›PMID 35441154›Full record

ArticleTetrahedron chem2022

Working at the interfaces of data science and synthetic electrochemistry.

Jesus I Martinez Alvarado, Jonathan M Meinhardt, Song Lin

Abstract read
In one paragraph

Article in Tetrahedron chem, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jesus I Martinez AlvaradoDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, 14853, United States.
Jonathan M MeinhardtDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, 14853, United States.
Song LinDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, 14853, United States.

Funding

Electrochemistry as an enabling tool for reaction discoveryR01GM130928 · NIGMS · STANFORD UNIVERSITY · PI Song Lin · 2018 to 2026
$3.4M
NIGMS NIH HHS R01 GM130928
6 · The paper itself

Abstract

Electrochemistry is quickly entering the mainstream of synthetic organic chemistry. The diversity of new transformations enabled by electrochemistry is to a large extent a consequence of the unique features and reaction parameters in electrochemical systems including redox mediators, applied potential, electrode material, and cell construction. While offering chemists new means to control reactivity and selectivity, these additional features also increase the dimensionalities of a reaction system and complicate its optimization. This challenge, however, has spawned increasing adoption of data science tools to aid reaction discovery as well as development of high-throughput screening platforms that facilitate the generation of high quality datasets. In this Perspective, we provide an overview of recent advances in data-science driven electrochemistry with an emphasis on the opportunities and challenges facing this growing subdiscipline.

Indexed as

Data scienceDesign of experimentsElectrocatalysisElectrochemistryHigh-throughput experimentationMachine learning

Identifiers

PMID35441154
PMCPMC9014485

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.