[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.
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.
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.
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.
