• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Saturday, October 4, 2025
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News Chemistry

Observing individual atoms in 3D nanomaterials and their surfaces

Bioengineer by Bioengineer
May 12, 2021
in Chemistry
Reading Time: 3 mins read
0
IMAGE
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

IMAGE

Credit: KAIST

Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography.

Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface. This research was reported at Nature Communications.

Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect.

“We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang.

The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials.

The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination.

“The main idea behind this deep learning-based approach is atomicity–the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang.

“A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.”

The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved.

Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale.

Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.”

###

This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project.

-About KAIST

KAIST is the first and top science and technology university in Korea. KAIST was established in 1971 by the Korean government to educate scientists and engineers committed to the industrialization and economic growth of Korea.

Since then, KAIST and its 64,739 graduates have been the gateway to advanced science and technology, innovation, and entrepreneurship. KAIST has emerged as one of the most innovative universities with more than 10,000 students enrolled in five colleges and seven schools including 1,039 international students from 90 countries.

On the precipice of its semi-centennial anniversary in 2021, KAIST continues to strive to make the world better through the pursuit in education, research, entrepreneurship, and globalization.

Media Contact
Younghye Cho
[email protected]

Original Source

https://news.kaist.ac.kr/newsen/html/news/?mode=V&mng_no=13811&skey=&sval=&list_s_date=&list_e_date=&GotoPage=1

Related Journal Article

http://dx.doi.org/10.1038/s41467-021-22204-1

Tags: Atomic PhysicsChemistry/Physics/Materials Sciences
Share12Tweet8Share2ShareShareShare2

Related Posts

Building Larger Hydrocarbons for Optical Cycling

Building Larger Hydrocarbons for Optical Cycling

October 4, 2025
blank

Scientists Discover How Enzymes “Dance” During Their Work—and Why It Matters

October 4, 2025

Electron Donor–Acceptor Complexes Enable Asymmetric Photocatalysis

October 4, 2025

AI Advances Enhance Sustainable Recycling of Livestock Waste

October 3, 2025
Please login to join discussion

POPULAR NEWS

  • New Study Reveals the Science Behind Exercise and Weight Loss

    New Study Reveals the Science Behind Exercise and Weight Loss

    93 shares
    Share 37 Tweet 23
  • New Study Indicates Children’s Risk of Long COVID Could Double Following a Second Infection – The Lancet Infectious Diseases

    90 shares
    Share 36 Tweet 23
  • Physicists Develop Visible Time Crystal for the First Time

    75 shares
    Share 30 Tweet 19
  • New Insights Suggest ALS May Be an Autoimmune Disease

    69 shares
    Share 28 Tweet 17

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

HIRAID Framework Enhances Nurse and Patient Outcomes

tRF-34-86J8WPMN1E8Y2Q Fuels Gastric Cancer Progression

Discovering Wuwei Xiaodu Decoction’s Anti-Inflammatory Mechanisms

Subscribe to Blog via Email

Enter your email address to subscribe to this blog and receive notifications of new posts by email.

Join 62 other subscribers
  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.