• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Thursday, August 28, 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

Comprehensive electronic-structure methods review featured in Nature Materials

Bioengineer by Bioengineer
May 27, 2021
in Chemistry
Reading Time: 3 mins read
0
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

IMAGE

Credit: @Nicola Marzari

Over the past 20 years, first-principles simulations have become powerful, widely used tools in many, diverse fields of science and engineering. From nanotechnology to planetary science, from metallurgy to quantum materials, they have accelerated the identification, characterization, and optimization of materials enormously. They have led to astonishing predictions–from ultrafast thermal transport to electron-phonon mediated superconductivity in hydrides to the emergence of flat bands in twisted-bilayer graphene– that have gone on to inspire remarkable experiments.

The current push to complement experiments with simulations; continued, rapid growth in computer throughput capacity; the ability of machine-learning and artificial intelligence to accelerate materials discovery as well as the promise of disruptive accelerators such as quantum computing for exponentially expensive tasks mean it is apparent that these methods will become ever more relevant as time goes by. It is an appropriate time then to review the capabilities as well as the limitations of the electronic-structure methods underlying these simulations. Marzari, Ferretti and Wolverton address this task in the paper “Electronic-structure methods for materials design,” just published in Nature Materials.

“Simulations do not fail in spectacular ways but can subtly shift from being invaluable to barely good enough to just useless,” the authors said in the paper. “The reasons for failure are manifold, from stretching the capabilities of the methods to forsaking the complexity of real materials. But simulations are also irreplaceable: they can assess materials at conditions of pressure and temperature so extreme that no experiment on earth is able to replicate, they can explore with ever-increasing nimbleness the vast space of materials phases and compositions in the search for that elusive materials breakthrough, and they can directly identify the microscopic causes and origin of a macroscopic property. Last, they share with all branches of computational science a key element of research: they can be made reproducible and open and shareable in ways that no physical infrastructure will ever be.”

The authors first look at the framework of density-functional theory (DFT) and give an overview of the increasingly complex approaches that can improve accuracy or extend the scope of simulations. They then discuss the capabilities that computational materials science has developed to exploit this toolbox and deliver predictions for the properties of materials under realistic conditions of ever-increasing complexity. Finally, they highlight how physics- or data-driven approaches can provide rational, high-throughput, or artificial-intelligence avenues to materials discovery, and explain how such efforts are changing the entire research ecosystem.

Looking ahead, the authors say that developing methods that can assess the thermodynamic stability, synthesis conditions, manufacturability, and tolerance of the predicted properties to intrinsic and extrinsic defects in novel materials will be a significant challenge. Researchers may need to augment DFT estimates by more advanced electronic-structure methods or machine learning algorithms to improve accuracy, and use computational methods to address realistic conditions such as vibrational entropies, the concentration of defects and applied electrochemical potentials.

Finally, given the extended role that such methods are likely to play in the coming decades, the authors note that support and planning for the needed computational infrastructures–widely used scientific software, the verification of codes and validation of theories, the dissemination and curation of computational data, tools and workflows as well as the associated career models these entail and require–are only just beginning to emerge.

###

Media Contact
Carey Sargent
[email protected]

Original Source

https://nccr-marvel.ch/news/communication/052021NatMat

Related Journal Article

http://dx.doi.org/10.1038/s41563-021-01013-3

Tags: Chemistry/Physics/Materials SciencesMaterialsTechnology/Engineering/Computer Science
Share12Tweet8Share2ShareShareShare2

Related Posts

Wayne State Study Advances Quality of Life for Individuals with Type 1 Diabetes

Wayne State Study Advances Quality of Life for Individuals with Type 1 Diabetes

August 27, 2025
Wayne State Researchers Pioneer Advances to Enhance Quality of Life for Individuals with Type 1 Diabetes

Wayne State Researchers Pioneer Advances to Enhance Quality of Life for Individuals with Type 1 Diabetes

August 27, 2025

Electrostatic Map Reveals Non-Covalent Metal–Organic Frameworks

August 27, 2025

Widespread Metal, Extraordinary Potential Unveiled

August 27, 2025
Please login to join discussion

POPULAR NEWS

  • blank

    Breakthrough in Computer Hardware Advances Solves Complex Optimization Challenges

    149 shares
    Share 60 Tweet 37
  • Molecules in Focus: Capturing the Timeless Dance of Particles

    142 shares
    Share 57 Tweet 36
  • New Drug Formulation Transforms Intravenous Treatments into Rapid Injections

    115 shares
    Share 46 Tweet 29
  • Neuropsychiatric Risks Linked to COVID-19 Revealed

    82 shares
    Share 33 Tweet 21

About

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

Follow us

Recent News

Amygdala Noise Boosts Exploration During Threat

AI Unveils IVIG-Resistant Kawasaki Disease in Shandong

Challenges in AI-Driven Virtual Cells for Cancer Research

  • 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.