PRESS-NEWS.org - Press Release Distribution
PRESS RELEASES DISTRIBUTION

A novel machine learning model for the characterization of material surfaces

A novel machine learning model for the characterization of material surfaces
2024-04-12
(Press-News.org)

The design and development of novel materials with superior properties demands a comprehensive analysis of their atomic and electronic structures. Electron energy parameters such as ionization potential (IP), the energy needed to remove an electron from the valence band maximum, and electron affinity (EA), the amount of energy released upon the attachment of an electron to the conduction band minimum, reveal important information about the electronic band structure of surfaces of semiconductors, insulators, and dielectrics. The accurate estimation of IPs and EAs in such nonmetallic materials can indicate their applicability for use as functional surfaces and interfaces in photosensitive equipment and optoelectronic devices.

Additionally, IPs and EAs depend significantly on the surface structures, which adds another dimension to the complex procedure of their quantification. Traditional computation of IPs and EAs involves the use of accurate first-principles calculations, where the bulk and surface systems are separately quantified. This time-consuming process prevents quantifying IPs and EAs for many surfaces, which necessitates the use of computationally efficient approaches.

To address the wide-ranging issues affecting the quantification of IPs and EAs of nonmetallic solids, a team of scientists from Tokyo Institute of Technology (Tokyo Tech), led by Professor Fumiyasu Oba, have turned their focus towards machine learning (ML). Their research findings have been published in the Journal of the American Chemical Society.

Prof. Oba shares the motivation behind the present research, “In recent years, ML has gained a lot of attention in materials science research. The ability to virtually screen materials based on ML technology is a very efficient way to explore novel materials with superior properties. Also, the ability to train large datasets using accurate theoretical calculations allows for the successful prediction of important surface characteristics and their functional implications.”

The researchers employed an artificial neural network to develop a regression model, incorporating the smooth overlap of atom positions (SOAPs) as numerical input data. Their model accurately and efficiently predicted the IPs and EAs of binary oxide surfaces by using the information on bulk crystal structures and surface termination planes.

Moreover, the ML-based prediction model could ‘transfer learning,’ a scenario where a model developed for a particular purpose can be made to incorporate newer datasets and reapplied for additional tasks. The scientists included the effects of multiple cations in their model by developing ‘learnable’ SOAPs and predicted the IPs and EAs of ternary oxides using transfer learning.

Prof. Oba concludes by saying, “Our model is not restricted to the prediction of surface properties of oxides but can be extended to study other compounds and their properties.”

 

About Tokyo Institute of Technology

Tokyo Tech stands at the forefront of research and higher education as the leading university for science and technology in Japan. Tokyo Tech researchers excel in fields ranging from materials science to biology, computer science, and physics. Founded in 1881, Tokyo Tech hosts over 10,000 undergraduate and graduate students per year, who develop into scientific leaders and some of the most sought-after engineers in industry. Embodying the Japanese philosophy of “monotsukuri,” meaning “technical ingenuity and innovation,” the Tokyo Tech community strives to contribute to society through high-impact research. https://www.titech.ac.jp/english/

END


[Attachments] See images for this press release:
A novel machine learning model for the characterization of material surfaces

ELSE PRESS RELEASES FROM THIS DATE:

Presence of specific lipids indicate tissue ageing and can be decreased through exercise

2024-04-12
Scientists have discovered that a type of fat accumulates as tissue ages and that this accumulation can be reversed through exercise. Researchers from Amsterdam UMC, together with colleagues from Maastricht UMC+, analysed both mice and human tissue before and after exercise allowing them to draw this conclusion. The results are published today in Nature Aging.   "The idea that we could reverse aging is something that was long considered science fiction, but these findings do allow us to understand a lot more about the ...

Brightest gamma-ray burst of all time came from the collapse of a massive star

Brightest gamma-ray burst of all time came from the collapse of a massive star
2024-04-12
In October 2022, an international team of researchers, including Northwestern University astrophysicists, observed the brightest gamma-ray burst (GRB) ever recorded, GRB 221009A. Now, a Northwestern-led team has confirmed that the phenomenon responsible for the historic burst — dubbed the B.O.A.T. (“brightest of all time”) — is the collapse and subsequent explosion of a massive star. The team discovered the explosion, or supernova, using NASA’s James Webb Space Telescope (JWST).  While this discovery solves one mystery, another mystery deepens.  The researchers ...

Stellar winds of three sun-like stars detected for the first time

Stellar winds of three sun-like stars detected for the first time
2024-04-12
An international research team led by a researcher from the University of Vienna has for the first time directly detected stellar winds from three Sun-like stars by recording the X-ray emission from their astrospheres, and placed constraints on the mass loss rate of the stars via their stellar winds. The study is currently published in Nature Astronomy. Astrospheres, stellar analogues of the heliosphere that surrounds our solar system, are very hot plasma bubbles blown by stellar winds into the interstellar medium, a space filled with gas and dust. The ...

Iconic savanna mammals face genetic problems due to fences and roads

Iconic savanna mammals face genetic problems due to fences and roads
2024-04-12
Whether by way of Attenborough, Disney or National Geographic, the iconic scene is familiar to many. The ground trembles and clouds of dust swirl as enormous hordes of large animals thunder across the African savanna, cross rivers en masse and are picked off by lions, hyena and crocodiles. The annual migration of 1.3 million wildebeest through Tanzania’s Serengeti and Kenya’s Masai Mara attracts hundreds of thousands of tourists, and the phenomenon has put the Serengeti on UNESCO's list of World Heritage sites. Besides its majestic sight, the migration of this emblematic species ...

PFAS exposure from high seafood diets may be underestimated

2024-04-12
A Dartmouth-led study suggests that people who frequently consume seafood may face an increased risk of exposure to PFAS, the family of ubiquitous and resilient human-made toxins known as "forever chemicals." The findings stress the need for more stringent public health guidelines that establish the amount of seafood people can safely consume to limit their exposure to perfluoroalkyl and polyfluoroalkyl substances, the researchers report in the journal Exposure and Health. This need is especially urgent for coastal regions such as New England where a legacy of industry and PFAS pollution bumps up against a cultural predilection for fish, the authors write. "Our recommendation ...

Can TA-NRP increase the number of patients receiving lung transplants?

2024-04-12
Embargoed until 8:30 a.m. Friday, 12 April, 2024 Central European Summer Time or GMT +2 12 April, 2024, Prague, Czech Republic—Re-perfusing the lungs of an organ donor after the heart has irreversibly stopped beating with a technique called normothermic regional perfusion (TA-NRP) could potentially increase the number of patients receiving lung transplants, according to researchers at the Annual Meeting and Scientific Sessions of the International Society for Heart and Lung Transplantation (ISHLT) in Prague.   TA-NRP uses a machine to pass blood through a donor’s abdomen and chest after the heart has irreversibly stopped beating (called ...

Retention ponds can deliver a substantial reduction in tire particle pollution, study suggests

2024-04-12
Retention ponds and wetlands constructed as part of major road schemes can reduce the quantities of tyre particles entering the aquatic environment by an average of 75%, new research has shown. The study analysed samples collected alongside some of the busiest routes in South West England and the Midlands, many used by more than 100,000 vehicles each day. Tyre particles were discovered in each of the 70 samples taken, confirming the findings of previous research which has shown them to pose a considerable ...

Softer tumours fuel more aggressive spread of triple-negative breast cancer

Softer tumours fuel more aggressive spread of triple-negative breast cancer
2024-04-12
Softer tumours fuel more aggressive spread of triple-negative breast cancer Researchers have discovered how the mechanical properties of tumours can prime cancer cells to better survive their spread to other organs. A metabolic ‘survival switch’ controlled by the stiffness of triple-negative breast tumours can significantly influence how successfully their cancerous cells spread to other organs, according to new findings from the Garvan Institute of Medical Research. The study in cell and ...

Dynamic-EC: An efficient dynamic erasure coding method for permissioned blockchain systems

Dynamic-EC: An efficient dynamic erasure coding method for permissioned blockchain systems
2024-04-12
It's interesting to hear about the research led by Minyi Guo that was published in Frontiers of Computer Science on 12 Mar 2024. It seems like they are addressing the challenge of reducing storage overhead in blockchain systems while maintaining data consistency and tolerating malicious nodes. In traditional blockchain networks, full replication is used, where each node stores a complete copy of all blocks, and data consistency is maintained through a consensus protocol. However, this approach can be storage-intensive, especially as the blockchain grows over time. To address ...

How does the STB promote the coordination between environmental protection and agricultural development in Erhai Lake?

How does the STB promote the coordination between environmental protection and agricultural development in Erhai Lake?
2024-04-12
Erhai Lake, covering 252 km2, located in Yunnan Province, is one of the seven largest freshwater lakes in China. However, over the last three decades, the lake has suffered pollution episodes. In order to solve this problem, the local government has taken many protective measures. These measures have achieved some results in the environmental protection of Erhai Lake, but also caused significant socioeconomic impact. The tension between environmental preservation and economic stability in Erhai has even been termed the ‘Erhai dilemma’. The ‘Erhai dilemma’ is representative of those of other lakes in Yunnan Province ...

LAST 30 PRESS RELEASES:

Grafted cucumbers get a boost: pumpkin's secret to withstanding salinity

Unlocking broccoli's genome: key to enhanced health benefits

New insights into methyl jasmonate-induced saponin biosynthesis in balloon flower

Unraveling the role of ADGRF5: Insights into kidney health and function

JMIR Dermatology accepted for MEDLINE indexing

Reduced infections seen in CLL and NHL patients undergoing immunoglobulin testing and replacement therapy

Human activity: A double-edged sword in the face of drought

Portfolio performance in financial management: apraize, analyze, act.

Landmark Nature Medicine study reports promising new treatment reduces suffering in Sanfilippo syndrome

Membrane protein analogues could accelerate drug discovery

Berkeley Lab researchers advance AI-driven plant root analysis

Cleveland Clinic study shows weight loss surgery cuts risk of heart complications and death in patients with obstructive sleep apnea and obesity

SQUID pries open AI black box

Resiliency shaped by activity in the gut microbiome and brain

Inspired by nature: synthetic nightshade molecule effective against leukemia cells

Promise green hydrogen may not always be fulfilled

Unifying behavioral analysis through animal foundation models

Up to 30 percent more time: Climate change makes it harder for women to collect water

Heart failure in space: scientists calculate potential health threats facing future space tourists in microgravity

Experts offer guidance on talking with children about racism at pediatrician's office

Drugs for HIV and AIDS trialed as brain tumor treatment for first time

Breakthrough in nanoscale force measurement opens doors to unprecedented biological insights

Scientists discover new behavior of membranes that could lead to unprecedented separations

When inflicting pain on others pays off T

The Lancet: Managing gestational diabetes much earlier in pregnancy can prevent complications and improve long-term health outcomes, experts say

New study finds dinosaur fossils did not inspire the mythological griffin

NASA astronaut Woody Hoburg to deliver keynote address at ISSRDC focused on developing a space workforce

Study: Fatigue-management training improved sleep, safety, well-being for Seattle police

Guiding humanity beyond the moon: OHIO’s Nate Szewczyk and students coauthor papers published in “Nature” journals that revolutionize human space biology

Grant supports research to identify barriers to health care for Black women

[Press-News.org] A novel machine learning model for the characterization of material surfaces