Evidence map›Paper›PMID 34408023›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Cross-correlation analysis of X-ray photon correlation spectroscopy to extract rotational diffusion coefficients.

Zixi Hu, Jeffrey J Donatelli, James A Sethian

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Controlling nosocomial transmission of respiratory infections in neurological wards: insights from COVID-19 pandemic data.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. 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.

Zixi HuDepartment of Mathematics, University of California, Berkeley, CA 94720; zixihu@berkeley.edu sethian@math.berkeley.edu.ORCID 0000-0002-5365-7351
Jeffrey J DonatelliCenter for Advanced Mathematics for Energy Research Applications, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.
James A SethianDepartment of Mathematics, University of California, Berkeley, CA 94720; zixihu@berkeley.edu sethian@math.berkeley.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coefficients for translational and rotational diffusion characterize the Brownian motion of particles. Emerging X-ray photon correlation spectroscopy (XPCS) experiments probe a broad range of length scales and time scales and are well-suited for investigation of Brownian motion. While methods for estimating the translational diffusion coefficients from XPCS are well-developed, there are no algorithms for measuring the rotational diffusion coefficients based on XPCS, even though the required raw data are accessible from such experiments. In this paper, we propose angular-temporal cross-correlation analysis of XPCS data and show that this information can be used to design a numerical algorithm (Multi-Tiered Estimation for Correlation Spectroscopy [MTECS]) for predicting the rotational diffusion coefficient utilizing the cross-correlation: This approach is applicable to other wavelengths beyond this regime. We verify the accuracy of this algorithmic approach across a range of simulated data.

Indexed as

angular cross-correlationcorrelation spectroscopyrotational diffusionspeckle pattern analysisX-ray photon correlation spectroscopy

Identifiers

PMID34408023
PMCPMC8403868

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.