Tag: thermodynamics

World-Watching: Science First Release, 10 July 2025

[from Science]

Accepted papers posted online prior to journal publication.

NASA Earth Science Division provides key data

by Dylan B. Millet, Belay B. Demoz, et al.

In May, the US administration proposed budget cuts to NASA, including a more than 50% decrease in funding for the agency’s Earth Science Division (ESD), the mission of which is to gather knowledge about Earth through space-based observation and other tools. The budget cuts proposed for ESD would cancel crucial satellites that observe Earth and its atmosphere, gut US science and engineering expertise, and potentially lead to the closure of NASA research centers. As former members of the recently dissolved NASA Earth Science Advisory Committee, an all-volunteer, independent body chartered to advise ESD, we warn that these actions would come at a profound cost to US society and scientific leadership.

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Spin-filter tunneling detection of antiferromagnetic resonance with electrically tunable damping

by Thow Min Jerald Cham, Daniel G. Chica, et al.

Antiferromagnetic spintronics offers the potential for higher-frequency operations and improved insensitivity to magnetic fields compared to ferromagnetic spintronics. However, previous electrical techniques to detect antiferromagnetic dynamics have utilized large, millimeter-scale bulk crystals. Here we demonstrate direct electrical detection of antiferromagnetic resonance in structures on the few-micrometer scale using spin-filter tunneling in PtTe2/bilayer CrSBr/graphite junctions in which the tunnel barrier is the van der Waals antiferromagnet CrSBr. This sample geometry allows not only efficient detection, but also electrical control of the antiferromagnetic resonance through spin-orbit torque from the PtTe2 electrode. The ability to efficiently detect and control antiferromagnetic resonance enables detailed studies of the physics governing these high-frequency dynamics.

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Scalable emulation of protein equilibrium ensembles with generative deep learning

by Sarah Lewis, Tim Hempel, et al.

Following the sequence and structure revolutions, predicting functionally relevant protein structure changes at scale remains an outstanding challenge. We introduce BioEmu, a deep learning system that emulates protein equilibrium ensembles by generating thousands of statistically independent structures per hour on a single GPU. BioEmu integrates over 200 milliseconds of molecular dynamics (MD) simulations, static structures and experimental protein stabilities using novel training algorithms. It captures diverse functional motions—including cryptic pocket formation, local unfolding, and domain rearrangements—and predicts relative free energies with 1 kcal/mol accuracy compared to millisecond-scale MD and experimental data. BioEmu provides mechanistic insights by jointly modeling structural ensembles and thermodynamic properties. This approach amortizes the cost of MD and experimental data generation, demonstrating a scalable path toward understanding and designing protein function.

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Negative capacitance overcomes Schottky-gate limits in GaN high-electron-mobility transistors

by Asir Intisar Khan, Jeong-Kyu Kim, et al.

For high-electron-mobility transistors based on two-dimensional electron gas (2DEG) within a quantum well, such as those based on AlGaN/GaN heterostructure, a Schottky-gate is used to maximize the amount of charge that can be induced and thereby the current that can be achieved. However, the Schottky-gate also leads to very high leakage current through the gate electrode. Adding a conventional dielectric layer between the nitride layers and gate metal can reduce leakage; but this comes at the price of a reduced drain current. Here, we used a ferroic HfO2 – ZrO2 bilayer as the gate dielectric and achieved a simultaneous increase in the ON current and decrease in the leakage current, a combination otherwise not attainable with conventional dielectrics. This approach surpasses the conventional limits of Schottky GaN transistors and provides a new pathway to improve performance in transistors based on 2DEG.

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Meaningfulness versus Informativeness

The Decoding Reality book is a classic contemporary analysis of the foundations of physics and the implications for the human world. The scientists don’t see that physics and science are the infrastructure on which the human “quest for meaning” takes place. Ortega (Ortega y Gasset, died in 1955) tells us that a person is “a point of view directed at the universe.” This level of meaning cannot be reduced to bits or qubits or electrons since man is a “linguistic creature” who invents fictional stories to explain “things” that are not things.

The following dialog between Paul Davies (the outstanding science writer) and Vlatko Vedral (the distinguished physicist) gropes along on these issues: the difference between science as one kind of story and the human interpretation of life and self expressed in “tales” and parables, fictions and beliefs:

Davies: “When humans communicate, a certain quantity of information passes between them. But that information differs from the bits (or qubits) physicists normally consider, inasmuch as it possesses meaning. We may be able to quantify the information exchanged, but meaning is a qualitative property—a value—and therefore hard, maybe impossible, to capture mathematically. Nevertheless the concept of meaning obviously has, well… meaning. Will we ever have a credible physical theory of ‘meaningful information,’ or is ‘meaning’ simply outside the scope of physical science?”

Vedral: “This is a really difficult one. The success of Shannon’s formulation of ‘information’ lies precisely in the fact that he stripped it of all “meaning” and reduced it only to the notion of probability. Once we are able to estimate the probability for something to occur, we can immediately talk about its information content. But this sole dependence on probability could also be thought of as the main limitation of Shannon’s information theory (as you imply in your question). One could, for instance, argue that the DNA has the same information content inside as well as outside of a biological cell. However, it is really only when it has access to the cell’s machinery that it starts to serve its main biological purpose (i.e., it starts to make sense). Expressing this in your own words, the DNA has a meaning only within the context of a biological cell. The meaning of meaning is therefore obviously important. Though there has been some work on the theory of meaning, I have not really seen anything convincing yet. Intuitively we need some kind of a ‘relative information’ concept, information that is not only dependent on the probability, but also on its context, but I am afraid that we still do not have this.”

For a physicist, all the world is information. The universe and its workings are the ebb and flow of information. We are all transient patterns of information, passing on the recipe for our basic forms to future generations using a four-letter digital code called DNA.

See Decoding Reality.

In this engaging and mind-stretching account, Vlatko Vedral considers some of the deepest questions about the universe and considers the implications of interpreting it in terms of information. He explains the nature of information, the idea of entropy, and the roots of this thinking in thermodynamics. He describes the bizarre effects of quantum behavior—effects such as “entanglement,” which Einstein called “spooky action at a distance” and explores cutting edge work on the harnessing quantum effects in hyper-fast quantum computers, and how recent evidence suggests that the weirdness of the quantum world, once thought limited to the tiniest scales, may reach into the macro world.

Vedral finishes by considering the answer to the ultimate question: Where did all of the information in the universe come from? The answers he considers are exhilarating, drawing upon the work of distinguished physicist John Wheeler. The ideas challenge our concept of the nature of particles, of time, of determinism, and of reality itself.

Science is an “ontic” quest. Human life is an “ontological” quest. They are a “twisted pair” where each strand must be seen clearly and not confused. The content of your telephone conversation with your friend, say. is not reducible to the workings of a phone or the subtle electrical engineering and physics involved. A musical symphony is not just “an acoustical blast.”

The “meaning of meaning” is evocative and not logically expressible. There’s a “spooky action at a distance” between these levels of meaning versus information but they are different “realms” or “domains.”