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

You might also read

Related Articles

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

Sort by
Same author

Evolution of the Fatigue Failure Prediction Process from Experiment to Artificial Intelligence: A Review.

Materials (Basel, Switzerland)·2025
Same author

Using Deep Learning to Recognize Therapeutic Effects of Music Based on Emotions.

Sensors (Basel, Switzerland)·2023
Same author

Influence of Heat and Thermochemical Treatment Parameters on C75 Steel Fatigue Resistance.

Materials (Basel, Switzerland)·2022
Same author

Investigations Regarding the Addition of ZnO and Li<sub>2</sub>O-TiO<sub>2</sub> to Phosphate-Tellurite Glasses: Structural, Chemical, and Mechanical Properties.

Materials (Basel, Switzerland)·2022
Same author

Nanocrystallized Ge-Rich SiGe-HfO<sub>2</sub> Highly Photosensitive in Short-Wave Infrared.

Materials (Basel, Switzerland)·2021
Same author

Reconfigurable Wireless Sensor Node Remote Laboratory Platform with Cloud Connectivity.

Sensors (Basel, Switzerland)·2021

Related Experiment Video

Updated: Feb 25, 2026

Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
07:59

Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors

Published on: December 6, 2018

8.7K

Using Noise and Fluctuations for In Situ Measurements of Nitrogen Diffusion Depth.

Cornel Samoila1, Doru Ursutiu2, Walter-Harald Schleer3

  • 1Department of Materials Science, Transylvania University of Brasov, Brasov 500036, Romania. csam@unitbv.ro.

Materials (Basel, Switzerland)
|August 5, 2017
PubMed
Summary

This study introduces a novel in situ monitoring method for diffusion layer depth in manufacturing using noise and fluctuation measurements. This technique offers direct control, improving process efficiency and reducing failures in nitriding processes.

Keywords:
diffusionfurnacemagneticmanufacturingnitridingsensorstemperaturethermochemistry

More Related Videos

Measurement of the Potential Rates of Dissimilatory Nitrate Reduction to Ammonium Based on 14NH4+/15NH4+ Analyses via Sequential Conversion to N2O
08:05

Measurement of the Potential Rates of Dissimilatory Nitrate Reduction to Ammonium Based on 14NH4+/15NH4+ Analyses via Sequential Conversion to N2O

Published on: October 7, 2020

6.7K
Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace
09:03

Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace

Published on: September 6, 2018

13.1K

Related Experiment Videos

Last Updated: Feb 25, 2026

Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
07:59

Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors

Published on: December 6, 2018

8.7K
Measurement of the Potential Rates of Dissimilatory Nitrate Reduction to Ammonium Based on 14NH4+/15NH4+ Analyses via Sequential Conversion to N2O
08:05

Measurement of the Potential Rates of Dissimilatory Nitrate Reduction to Ammonium Based on 14NH4+/15NH4+ Analyses via Sequential Conversion to N2O

Published on: October 7, 2020

6.7K
Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace
09:03

Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace

Published on: September 6, 2018

13.1K

Area of Science:

  • Materials Science and Engineering
  • Manufacturing Process Control
  • Surface Engineering

Background:

  • Accurate control of diffusion layer depth is critical in manufacturing processes like nitriding.
  • Current methods rely on post-process calibration or indirect measurements, leading to inefficiencies and uncertainties.
  • Lack of in situ monitoring makes processes vulnerable to variations in parameters such as gas concentration and temperature.

Purpose of the Study:

  • To propose and validate a novel in situ method for monitoring diffusion layer depth evolution.
  • To enable direct control of the nitriding process by measuring parameters in contact with the material.
  • To investigate the application of noise and fluctuation measurements for real-time process monitoring.

Main Methods:

  • Utilized Barkhausen noise measurements on nitrided samples in laboratory tests.
  • Developed a specialized sensor based on conductivity noise for shop-floor experiments at nitriding temperatures.
  • Analyzed the frequency exponent in the Hooge equation to correlate noise measurements with nitriding time.

Main Results:

  • A linear relationship was established between the frequency exponent and nitriding time using Barkhausen noise.
  • The frequency exponent remained a valid parameter for monitoring process evolution even with conductivity noise measurements.
  • The proposed method allows for direct measurement of layer depth evolution via noise analysis.

Conclusions:

  • Noise and fluctuation measurements offer a direct and reliable method for in situ monitoring of diffusion layer depth.
  • The frequency exponent is a robust indicator for tracking nitriding process evolution across different noise measurement techniques.
  • This approach enhances process control, potentially reducing inefficiencies and failures in manufacturing.