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

Biasing of Metal-Semiconductor Junctions01:27

Biasing of Metal-Semiconductor Junctions

458
Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...
458
Metal-Semiconductor Junctions01:24

Metal-Semiconductor Junctions

750
The contact of metal and semiconductor can lead to the formation of a junction with either Schottky or Ohmic behavior.
Schottky Barriers
Schottky barriers arise when a metal with a work function (Φm) contacts a semiconductor with a different work function (Φs). Initially, electrons transfer until the Fermi levels of the metal and semiconductor align at equilibrium. For instance, if Φm > Φs, the semiconductor Fermi level is higher than the metal's before contact. The...
750
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

421
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
421
Electro-mechanical Systems01:19

Electro-mechanical Systems

1.4K
Electromechanical systems are intricate configurations that effectively combine electrical and mechanical elements to achieve a desired outcome. Central to many of these systems is the DC motor, a device that converts electrical energy into mechanical motion, enabling various applications ranging from simple fans to complex robotic mechanisms.
A key component of the DC motor is the armature, a rotating circuit positioned within a magnetic field. As an electric current passes through the...
1.4K
Reliability and Validity01:29

Reliability and Validity

13.6K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.6K
Response Surface Methodology01:16

Response Surface Methodology

474
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
474

You might also read

Related Articles

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

Sort by
Same author

Synapse-inspired energy networks: a neuromorphic approach to microgrid protection without communication links.

Communications engineering·2026
Same author

Digital Twin Approach for Fault Diagnosis in Photovoltaic Plant DC-DC Converters.

Sensors (Basel, Switzerland)·2025
Same author

AI-aided power electronic converters automatic online real-time efficiency optimization method.

Fundamental research·2025
Same author

Resource management with kernel-based approaches for grid-connected solar photovoltaic systems.

Heliyon·2022
Same author

Electric Power Grids Under High-Absenteeism Pandemics: History, Context, Response, and Opportunities.

IEEE access : practical innovations, open solutions·2021
Same author

Intelligent long-term performance analysis in power electronics systems.

Scientific reports·2021

Related Experiment Video

Updated: Dec 9, 2025

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
08:46

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Published on: April 13, 2016

10.4K

Correlation-driven machine learning for accelerated reliability assessment of solder joints in electronics.

Vahid Samavatian1, Mahmud Fotuhi-Firuzabad1, Majid Samavatian2

  • 1Department of Electrical Engineering, Sharif University of Technology, 68260, Tehran, Iran.

Scientific Reports
|September 10, 2020
PubMed
Summary

This study introduces a new machine learning framework to quickly and accurately predict the useful lifetime of solder joints in electronic devices. The model uses material properties and thermal cycling data to assess reliability, reducing costs and time.

More Related Videos

Using Laser Scanning Microscopy to Determine Electromigration in Molybdenum Disilicide
09:41

Using Laser Scanning Microscopy to Determine Electromigration in Molybdenum Disilicide

Published on: May 23, 2025

457
A 3D-printed Chamber for Organic Optoelectronic Device Degradation Testing
08:29

A 3D-printed Chamber for Organic Optoelectronic Device Degradation Testing

Published on: August 10, 2018

8.3K

Related Experiment Videos

Last Updated: Dec 9, 2025

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
08:46

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Published on: April 13, 2016

10.4K
Using Laser Scanning Microscopy to Determine Electromigration in Molybdenum Disilicide
09:41

Using Laser Scanning Microscopy to Determine Electromigration in Molybdenum Disilicide

Published on: May 23, 2025

457
A 3D-printed Chamber for Organic Optoelectronic Device Degradation Testing
08:29

A 3D-printed Chamber for Organic Optoelectronic Device Degradation Testing

Published on: August 10, 2018

8.3K

Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Artificial Intelligence

Background:

  • Assessing the reliability of solder joints under thermo-mechanical stress is complex and time-consuming.
  • Existing methods for electronic device reliability assessment are slow and expensive due to numerous failure parameters.

Purpose of the Study:

  • To develop a novel machine learning framework for rapid and accurate reliability assessment of solder joints.
  • To create a correlation-driven neural network model for predicting solder joint useful lifetime.

Main Methods:

  • Developed a novel machine learning framework incorporating a correlation-driven neural network.
  • Utilized material properties, device configuration, and thermal cycling variations as input parameters.
  • Conducted a case study to evaluate solder material and joint thickness effects on reliability.

Main Results:

  • The machine learning model achieved high prediction accuracy for solder joint useful lifetime.
  • Demonstrated that thermal cycling variations dictate damage evolution (creep or fatigue).
  • Showcased how optimizing solder thickness balances damage and enhances useful lifetime.

Conclusions:

  • The proposed framework significantly accelerates reliability assessment for electronic devices.
  • Provides a roadmap for developing new electronic materials and optimizing processing.
  • Highlights the critical role of solder joint thickness and thermal cycling in device longevity.