Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 305

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Terahertz Wave Accelerates DNA Unwinding: A Molecular Dynamics Simulation Study

Wu, Kaijie, Qi, Chonghai, Zhu, Zhi, Wang, Chunlei, Song, Bo, Chang, Chao·2020·The Journal of Physical Chemistry Letters

Abstract

Unwinding the double helix of the DNA molecule is the basis of gene duplication and gene editing, and the acceleration of this unwinding process is crucial to the rapid detection of genetic information. Based on the unwinding of six-base-pair DNA duplexes, we demonstrate that a terahertz stimulus at a characteristic frequency (44.0 THz) can serve as an efficient, nonthermal, and long-range method to accelerate the unwinding process of DNA duplexes. The average speed of the unwinding process increased by 20 times at least, and its temperature was significantly reduced. The mechanism was revealed to be the resonance between the terahertz stimulus and the vibration of purine connected by the weak hydrogen bond and the consequent break in hydrogen bond connections between these base pairs. Our findings potentially provide a promising application of terahertz technology for the rapid detection of nucleic acids, biomedicine, and therapy.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acs.jpclett.0c01850

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 27 references

Metadata

Authors
Wu, K., Qi, C., Zhu, Z., Wang, C., Song, B., & Chang, C.
Venue
The Journal of Physical Chemistry Letters
Published
2020-08-03
Volume
11
Issue
17
Pages
7002-7008
ISSN
1948-7185 (ISSN-L)
OpenAlex
W3047487730
Cited by
305
References
27
FWCI
4.70
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Terahertz Wave Accelerates DNA Unwinding: A Molecular Dynamics Simulation Study. https://app.cochat.ai/papers/10.1021/acs.jpclett.0c01850
The paper
Wu, K., Qi, C., Zhu, Z., Wang, C., Song, B., & Chang, C. (2020). Terahertz Wave Accelerates DNA Unwinding: A Molecular Dynamics Simulation Study. The Journal of Physical Chemistry Letters. https://doi.org/10.1021/acs.jpclett.0c01850

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.