(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
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 ...
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 ...
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 ...
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 ...
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 ...
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 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
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 ...
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 ...
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 ...
