Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Polymers: Molecular Weight Distribution

Polymers: Molecular Weight Distribution

For any given polymer, the weight average molecular weight (Mw) is higher than, if not equal to, the number average molecular weight (Mn). The only situation in which the weight average molecular weight and the number average molecular weight are equal is when a polymer consists only of chains with equal molecular weight. However, this never happens in a synthetic polymer, since it is difficult to control the polymerization process up to a molecular level with accuracy to a hundred percent.

¹H NMR: Interpreting Distorted and Overlapping Signals

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...

Precipitate Formation and Particle Size Control

Precipitate Formation and Particle Size Control

In precipitation gravimetry, the precipitating agent should react specifically or selectively with the analyte. While a specific reagent reacts with the analyte alone, a selective reagent can react with a limited number of chemical species.
The obtained precipitate should be either a pure substance of known composition or easily converted to one by a simple process, such as ignition or drying. In addition, the precipitate should be insoluble and easily filterable. In general, filterability...

You might also read

Related Articles

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

Sort by

Same author

Influence of block microstructure on the interaction of styrene-maleic acid copolymer aggregates and lipid nanodiscs.

Soft matter·2026

Same author

Anisotropic diffraction of materials with fibre symmetry: application to chitin cuticle.

IUCrJ·2025

Same author

Efficient silicon-containing di-chain anionic surfactants for stabilizing oil-water interfaces in microemulsions.

Soft matter·2025

Same author

Molecular and pore-scale structure evolution in amorphous solid water.

Physical chemistry chemical physics : PCCP·2025

Same author

Line tension controls the spontaneous formation of vesicles.

Soft matter·2025

Same author

Disentangling autoencoders and spherical harmonics for efficient shape classification in crystal growth simulations.

Communications physics·2025

Search research articles

Related Experiment Video

Updated: Sep 1, 2025

Assembly and Characterization of Polyelectrolyte Complex Micelles

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

Parameter inversion of a polydisperse system in small-angle scattering.

Kuangdai Leng¹, Stephen King², Tim Snow³

¹Scientific Computing Department, STFC, Rutherford Appleton Laboratory, Didcot OX11 0QX, United Kingdom.

Journal of Applied Crystallography

|August 17, 2022

Summary

This summary is machine-generated.

This study presents a new method for analyzing polydisperse systems using small-angle scattering (SAS) data. The approach accurately reconstructs parameter distributions, offering insights into complex material structures.

Keywords:

X-ray scattering inversion neutron scattering nonlinear programming polydispersity small-angle scattering

More Related Videos

Author Spotlight: Advances in Nanoscale Infrared Spectroscopy to Explore Multiphase Polymeric Systems

Author Spotlight: Advances in Nanoscale Infrared Spectroscopy to Explore Multiphase Polymeric Systems

Published on: June 23, 2023

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

Published on: January 9, 2017

Related Experiment Videos

Last Updated: Sep 1, 2025

Assembly and Characterization of Polyelectrolyte Complex Micelles

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

Author Spotlight: Advances in Nanoscale Infrared Spectroscopy to Explore Multiphase Polymeric Systems

Author Spotlight: Advances in Nanoscale Infrared Spectroscopy to Explore Multiphase Polymeric Systems

Published on: June 23, 2023

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

Published on: January 9, 2017

Area of Science:

Materials Science
Physics
Computational Science

Background:

Small-angle scattering (SAS) experiments provide crucial data on material structures.
Analyzing polydisperse systems requires inverting complex parameter distributions.
Existing methods often face limitations in generality and accuracy.

Purpose of the Study:

To develop a general and accurate method for inverting parameter distributions from SAS data.
To address the challenges of non-uniqueness and structural ambiguity in SAS inversion.
To provide a robust computational framework for analyzing polydisperse systems.

Main Methods:

Generalizing the forward problem as a multi-linear map using a Green tensor.
Formulating the inverse problem as a constrained nonlinear programming (NLP) problem.
Employing automatic data scaling and GPU acceleration for enhanced accuracy and efficiency.

Main Results:

Demonstrated a highly accurate and efficient method for SAS data inversion.
Validated the approach with synthetic data and real neutron/X-ray scattering datasets.
Highlighted the inherent non-uniqueness and structural ambiguity in SAS inversion problems.

Conclusions:

The developed method offers a powerful tool for characterizing polydisperse systems.
The NLP formulation provides near-optimal solutions with ultra-high accuracy.
The findings advance the application of SAS in materials science and nanotechnology.