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A simple crystal with ultralow thermal conductivity has applications in thermal insulation and thermoelectrics

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A simple crystal with ultralow thermal conductivity has applications in thermal insulation and thermoelectrics


A simple crystal with ultralow thermal conductivity has applications in thermal insulation and thermoelectrics
Structure analysis and experimental thermal conductivity of AgTlI2. Structural projection a along c-axis, b along [111] and focus on a [AgI2] chain. Ag, Tl, and I atoms are drawn using blue, green, and purple circles, respectively. c Orange arrow: Residual electron density (red: positive and green: negative) in the area of the Ag site for a harmonic description of Ag. Red arrow: Anharmonic three-dimensional probability density function (pdf) isosurfaces of Ag (red cloud); displacements are pointing toward the faces of the tetrahedron. d Experimental thermal conductivity of AgTlI2 from 4 to 325 K measured by Physical Property Measurement System (PPMS). Credit: Nature Communications (2024). DOI: 10.1038/s41467-024-46799-3

An engineering research team led by Professor Yue Chen from the Department of Mechanical Engineering at the University of Hong Kong (HKU) has achieved a remarkable milestone in the realm of thermal transport in crystals.

The research highlights the potential of simple crystal structures to achieve low thermal conductivity. This discovery not only underscores the importance of exploring new materials for applications in thermal insulation and thermoelectrics but also calls for further experimental investigations to expand the repertoire of materials with ultralow thermal conductivity.

The work is published in the journal Nature Communications.

Traditionally, efforts to lower the lattice thermal conductivity of materials have focused on complex material systems, where lower thermal conductivity is typically observed. However, the pursuit of simple crystals with ultralow thermal conductivity has proven to be a challenging task.

In their research, the team identified an exceptional candidate, AgTlI2, which defies conventional expectations by exhibiting an extraordinarily low thermal conductivity of 0.25 W/mK at room temperature—a rarity among simple crystals.

Through a combination of state-of-the-art experimental techniques, including X-ray diffraction experiments and ab initio molecular dynamics simulations, coupled with advanced anharmonic lattice dynamics, the team gained comprehensive insights into the complex thermal transport mechanisms of AgTlI2 at room temperature.

Their findings revealed the coexistence of ultralow particle-like and wavelike phonon thermal transports in AgTlI2, elucidating the underlying nature of its ultralow thermal conductivity.

Moreover, leveraging their understanding of thermal transport in AgTlI2, the team proposed an effective alternative approach for identifying other simple materials with ultralow thermal conductivity, promising to expand the repertoire of materials with strongly suppressed thermal transport.

This interdisciplinary study was conducted in collaboration with Professor Emmanuel Guilmeau’s team from CRISMAT at Normandie University in France, Professor Zheyong Fan’s team from Bohai University, China, and Professor Pierric Lemoine from Institute Jean Lamour, France.

The collaborative effort allowed for the integration of expertise from multiple research groups, including sample preparation, synchrotron X-ray scattering, low-temperature thermal conductivity measurement, and ab initio simulations.

“The discovery of the ultralow thermal conductivity of AgTlI2 is a result of a combined effort of both theorists and experimentalists,” stated the first author of the paper, Dr. Zezhu Zeng.

He is currently a Post-doctoral Fellow in Professor Geoff Thornton’s group at University College London and Professor Bingqing Cheng’s group at University of California, Berkeley and Institute of Science and Technology, Austria. Dr. Xingchen Shen from CRISMAT at the French National Center for Scientific Research (CNRS) also contributed as a co-first author.

“This work implies the important role of simple crystals on thermal insulation, paving the way for new research directions,” said Professor Chen.

More information:
Zezhu Zeng et al, Pushing thermal conductivity to its lower limit in crystals with simple structures, Nature Communications (2024). DOI: 10.1038/s41467-024-46799-3

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A simple crystal with ultralow thermal conductivity has applications in thermal insulation and thermoelectrics (2024, June 25)
retrieved 25 June 2024
from https://techxplore.com/news/2024-06-simple-crystal-ultralow-thermal-applications.html

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Hidden mechanisms behind hermaphroditic plant self-incompatibility revealed

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Hidden mechanisms behind hermaphroditic plant self-incompatibility revealed


Hidden mechanisms behind hermaphroditic plant self-incompatibility revealed
A shift of paradigm in the molecular recognition model: from one-to-one (left) into many-to-many (right). Description: Previous models of self-incompatibility accounted for only one-to-one interactions between male and female-determinant proteins. The new model allows for a more general network of interactions, where each protein can interact with any number of partners. Credit: Tamar Friedlander and Amit Jangid

A new study presents an evolutionary-biophysical model that sheds new light on the evolution of the collaborative non-self recognition self-incompatibility, a genetic mechanism in plants that prevents self-fertilization and promotes cross-fertilization. The innovative model introduces promiscuous molecular interactions as a key ingredient, enhancing our understanding of genetic diversity and evolution in hermaphroditic plants.

A study led by Dr. Tamar Friedlander and her team at The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture at the Hebrew University, in collaboration with Prof. Ohad Feldheim from the Einstein Institute of Mathematics at the Hebrew University has developed an evolutionary-biophysical model that sheds new light on the evolution of collaborative non-self recognition self-incompatibility in plants.

The study, appearing in Nature Communications, introduces a novel theoretical framework that incorporates promiscuous molecular interactions, which have been largely overlooked by traditional models.

Self-incompatibility (SI) is a widespread biological mechanism in plants having both male and female reproductive organs, that prevents self-fertilization and promotes genetic diversity. Under this mechanism, fertilization relies on the specific recognition between highly diverse proteins: the RNase (female determinant) and the SLF (male determinant).

The interaction between these proteins ensures that plants are only compatible with non-self mates, thus maintaining a diverse gene pool.

The new model proposed by Dr. Friedlander and her team represents a significant advancement in understanding the evolutionary dynamics of self-incompatibility proteins. By allowing for promiscuous interactions—where interactions with unfamiliar partners are likely—and for multiple distinct partners per protein, the model aligns more closely with empirical findings than previous models that assumed only one-to-one interactions.

This promiscuity enables a flexible interaction pattern between male and female proteins, offering new insights into how these proteins evolve and interact over generations.

“Our research shows that the ability of proteins to engage in promiscuous interactions is crucial for the long-term evolutionary maintenance of self-incompatibility systems,” explained Dr. Friedlander.

“We propose that the default state of this system is that recognition is likely and evolutionary pressure is needed to avoid it, in contrast to what was previously thought. This flexibility not only helps in maintaining genetic diversity but also suggests that similar mechanisms could be operating in other biological systems.”

The study also reveals how populations of these plants spontaneously organize into distinct compatibility classes, ensuring full compatibility across different classes while maintaining incompatibility within the same class.

The model predicts various evolutionary paths that could lead to the formation or elimination of these compatibility classes based solely on point mutations. The dynamic balance between the emergence and decay of these classes, which provides a sustainable model of evolution, was analyzed by the researchers using a mixture of empirical and theoretical tools borrowed from the field of statistical mechanics in physics.

“These insights from our study have profound implications not only for plant biology but also for understanding the fundamental principles of molecular recognition and its impact on the evolution of biological networks,” Dr. Friedlander added. “Our findings could also help in the conservation of plant biodiversity.”

This research, which highlights the role of promiscuous and multi-partner molecular interactions, is likely to inspire seeking these two elements in additional biological systems, and help in explaining the evolution of various complex molecular networks. It enriches the understanding of plant biology and has broader implications for deciphering the evolution of biological networks and managing biodiversity.

More information:
Keren Erez et al, The role of promiscuous molecular recognition in the evolution of RNase-based self-incompatibility in plants, Nature Communications (2024). DOI: 10.1038/s41467-024-49163-7

Citation:
Hidden mechanisms behind hermaphroditic plant self-incompatibility revealed (2024, June 25)
retrieved 25 June 2024
from https://phys.org/news/2024-06-hidden-mechanisms-hermaphroditic-incompatibility-revealed.html

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part may be reproduced without the written permission. The content is provided for information purposes only.





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Amazon fined nearly $6 million for violations at Inland Empire warehouses

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Amazon fined nearly  million for violations at Inland Empire warehouses


Amazon
Credit: Unsplash/CC0 Public Domain

California has fined Amazon nearly $6 million for violating a law meant to protect warehouse workers from misuse of production quotas, state officials announced Tuesday.

The $5.9 million in penalties, which were issued last month, stem from demands that the behemoth e-commerce company placed on thousands of workers at two of its Inland Empire fulfillment centers. The California Labor Commissioner’s Office found that managers at the facilities failed to provide employees with adequate explanations of quotas that they were expected to meet as they prepared orders for shipment.

Mindy Acevedo, staff attorney with the Warehouse Worker Resource Center, an advocacy group, said in a statement that “these citations show Amazon failed to follow fundamental parts of the law.”

The law, AB 701, went into effect at the beginning of 2022 and requires that companies explain in writing the speed at which warehouse workers are expected to complete a certain amount of work as well as the discipline the company may impose for failure to meet the quotas. Under the law, an employee cannot be required to meet a quota that prevents them from taking meal or bathroom breaks and rest periods.

Amazon spokesperson Maureen Lynch Vogel said in an email that the company plans to defend itself against the citations.

“We disagree with the allegations made in the citations and have appealed. The truth is, we don’t have fixed quotas. At Amazon, individual performance is evaluated over a long period of time, in relation to how the entire site’s team is performing,” Vogel said. “Employees can—and are encouraged to—review their performance whenever they wish. They can always talk to a manager if they’re having trouble finding the information.”

The citations include penalties of more than $1.2 million at a warehouse in Redlands and nearly $4.7 million at one in Moreno Valley.

The fines imposed on Amazon are among the first issued by the Labor Commissioner’s Office for failing to provide written quota descriptions to its workers. Since September 2023, the office has handed down $7.8 million in penalties—a total that includes the Amazon fines, according to the Warehouse Worker Resource Center.

The enforcement comes after years of scrutiny over working conditions inside Amazon’s warehouses, including investigations by state and federal agencies into the company’s safety practices. They also come as California has come under fire for failing to enforce labor laws around wage theft and other violations.

Lilia Garcia-Brower, the California Labor Commissioner, said Tuesday at a news conference in Ontario that Amazon had not been singled out for enforcement. Her office, she said, sent out hundreds of letters notifying companies of possible violations and followed up with inspections on companies that failed to respond or comply.

“We are not playing the game of gotcha here,” Garcia-Brower said.

Garcia-Bower said her office will defend the Amazon citation at an appeal hearing. She encouraged workers to reach out to worker centers and other community organizations for help.

“It is so important for workers to come together, understand it is the bad-faith employer who wants you to feel isolated and alone and unfamiliar with your rights.”

At the news conference, Veronica Kern, who has worked at Amazon for seven years, and currently sorts products and loads them onto conveyor belts at the Moreno Valley warehouse, said it “can be a stressful and intense place,” with managers publicly chastising workers when they decide they aren’t working fast enough.

She described her manager telling her she needed to work faster and that she was performing in the bottom 5% of workers. He would stand outside the bathroom and get workers to hurry back to work, she said.

“They started treating us like a number rather than humans,” Kern said.

Kern recalled how managers would show workers real-time productivity data that they said showed them falling short of production targets, but often would not tell workers what those targets were, she said.

2024 Los Angeles Times. Distributed by Tribune Content Agency, LLC.

Citation:
Amazon fined nearly $6 million for violations at Inland Empire warehouses (2024, June 19)
retrieved 25 June 2024
from https://techxplore.com/news/2024-06-amazon-fined-million-violations-inland.html

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Machine learning enhances GNSS signal stability

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Machine learning enhances GNSS signal stability


Predicting space weather: Machine learning enhances GNSS signal stability
S^4c values for PRN 24 observed by HKOH station from September 14 to September 20, 2014. Credit: Satellite Navigation (2024). DOI: 10.1186/s43020-024-00136-7

Ionospheric scintillation, caused by irregularities in the Earth’s ionosphere, can severely impact Global Navigation Satellite System (GNSS) signal integrity, leading to navigation errors.

Traditional detection methods rely on expensive and specialized ionospheric scintillation monitoring receivers (ISMRs). However, with the increasing reliance on GNSS for various applications, there is a pressing need for a more accessible and cost-effective detection method.

Due to these challenges, there is a need for in-depth research on utilizing common GNSS receivers to detect ionospheric scintillation events.

Led by a team of researchers from Hong Kong Polytechnic University, a new study was published in the journal Satellite Navigation on 3 June 2024. The team introduced a novel strategy that uses common geodetic GNSS receivers to identify ionospheric amplitude scintillation events with remarkable precision, potentially transforming GNSS monitoring.

The research focuses on utilizing the vast network of geodetic GNSS receivers to detect ionospheric scintillation events, which are typically identified by specialized ISMRs. The proposed method employs a pre-trained machine learning decision tree algorithm that processes the carrier-to-noise ratio (C/N0) and elevation angle data collected at 1-Hz intervals.

By mitigating multipath effects through detailed analysis of multipath patterns, the study effectively reduces noise and false alarms, ensuring the accuracy of the scintillation detection. The methodology involves computing an alternative scintillation index (S4c) based on C/N0 measurements from geodetic GNSS receivers.

This index shows a high correlation with the traditional S4 index used by ISMRs, despite the higher susceptibility of geodetic receivers to noise and multipath interference. The machine learning algorithm enhances detection accuracy by leveraging the periodic nature of multipath effects, which differ from the irregularities of scintillation.

Experimental results demonstrate that the decision tree algorithm achieves a remarkable 99.9% detection accuracy, surpassing traditional hard and semi-hard threshold methods.

Dr. Yiping Jiang, the lead researcher, stated, “Our study showcases the potential of integrating machine learning with widely available GNSS receivers to revolutionize ionospheric scintillation detection. This method not only provides a cost-effective alternative to specialized equipment but also enhances the accuracy and reliability of space weather monitoring.”

The implications of this research are far-reaching, offering a scalable solution for GNSS users worldwide. By improving the detection of scintillation events, it contributes to the development of more accurate navigation algorithms and techniques.

This advancement is crucial for various applications, including aviation, maritime, and land transportation, where GNSS reliability is paramount.

More information:
Wang Li et al, Amplitude scintillation detection with geodetic GNSS receivers leveraging machine learning decision tree, Satellite Navigation (2024). DOI: 10.1186/s43020-024-00136-7

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Predicting space weather: Machine learning enhances GNSS signal stability (2024, June 19)
retrieved 25 June 2024
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New perspectives on cognitive flexibility

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New perspectives on cognitive flexibility


Unlocking the entrepreneurial brain: new perspectives on cognitive flexibility
(Left) Increase in gray matter volume in the left insula in habitual entrepreneurs compared to managers. Significant clusters are shown on the brain template. The color bar illustrates the corresponding t value. (Right) Correlation plots of left insula gray matter density and the normalized score for divergent thinking. The shaded area represents a 95% confidence interval around the regression line. Credit: @JBVI/University of Liège

In a recent study led by the University of Liège researchers delved into the intersection of the fields of entrepreneurship and neuroscience, looking specifically at the cognitive flexibility of habitual entrepreneurs—those who repeatedly launch new businesses—compared to less experienced entrepreneurs and managers.

Cognitive flexibility—the ability to adapt and shift from one concept or strategy to another—is crucial to entrepreneurial success. Understanding the neural basis of this characteristic can provide valuable information for improving entrepreneurial training and education. Recently published research suggests links between entrepreneurial behavior and brain structure, opening up new perspectives in the emerging field of neuro-entrepreneurship.

“Our study used a two-stage methodology,” explains Frédéric Ooms, Assistant Professor and first author of the study. “First, we collected self-reported measures of cognitive flexibility from 727 participants, including entrepreneurs and managers. Next, we performed structural magnetic resonance imaging (MRI) on a subset of these participants to explore differences in gray matter volume in the brain. This multidisciplinary approach enabled us to correlate self-reported cognitive flexibility with actual brain structure.”

The findings are published in the Journal of Business Venturing Insights.

And what emerges first from the analyses is greater cognitive flexibility and brain differences between entrepreneurs and managers. Habitual entrepreneurs show an increase in gray matter volume in the left insula compared to managers. This brain region is associated with enhanced cognitive agility and divergent thinking, essential traits in entrepreneurship. The study also links gray matter density in the left insula to cognitive flexibility, particularly divergent thinking.

“This finding suggests that the brains of habitual entrepreneurs are specially adapted to foster the cognitive flexibility needed to identify and exploit new opportunities,” explains Steven Laureys, neurologist at ULiège and Laval University.

This research has practical implications for educators and organizations. By recognizing the importance of cognitive flexibility, educational programs can be designed to cultivate this characteristic in aspiring entrepreneurs. Organizations can also benefit by fostering cognitive flexibility among managers, which could lead to more innovative and adaptive business strategies.

“This study is essential for entrepreneurship and neuroscience researchers, educators designing entrepreneurial training programs and business leaders wishing to foster innovation within their organizations,” resumes Bernard Surlemont, Professor of Entrepreneurship. “By understanding the neural basis of cognitive flexibility, stakeholders can better support entrepreneurial success and adaptability.”

The discovery of distinct neural characteristics in habitual entrepreneurs not only advances our understanding of entrepreneurial cognition, but also opens up new avenues of research into how these brain structures develop and change in response to entrepreneurial activities. Longitudinal studies are underway to explore whether these differences result from innate predispositions or the brain’s plastic response to entrepreneurial experiences.

This pioneering research highlights the importance of combining neuroscience with traditional entrepreneurship studies to gain a comprehensive understanding of what makes successful entrepreneurs distinct at the neurological level. “As we continue to explore the role of the brain in entrepreneurship, this study represents an important advance in the field of neuro-entrepreneurship,” concludes Frédéric Ooms.

More information:
Frédéric Ooms et al, Entrepreneurial neuroanatomy: Exploring gray matter volume in habitual entrepreneurs, Journal of Business Venturing Insights (2024). DOI: 10.1016/j.jbvi.2024.e00480

Citation:
Unlocking the entrepreneurial brain: New perspectives on cognitive flexibility (2024, June 21)
retrieved 25 June 2024
from https://phys.org/news/2024-06-entrepreneurial-brain-perspectives-cognitive-flexibility.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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