The set of known stable phases of water may not be complete, and some of the phase boundaries between them are fuzzy. Starting from liquid water and a comprehensive set of 50 ice structures, we compute the phase diagram at three hybrid density-functional-theory levels of approximation, accounting for thermal and nuclear fluctuations as well as proton disorder. Such calculations are only made tractable because we combine machine-learning methods and advanced free-energy techniques. The computed phase diagram is in qualitative agreement with experiment, particularly at pressures ≲ 8000 bar, and the discrepancy in chemical potential is comparable with the subtle uncertainties introduced by proton disorder and the spread between the three hybrid functionals. None of the hypothetical ice phases considered is thermodynamically stable in our calculations, suggesting the completeness of the experimental water phase diagram in the region considered. Our work demonstrates the feasibility of predicting the phase diagram of a polymorphic system from first principles and provides a thermodynamic way of testing the limits of quantum-mechanical calculations.
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http://dx.doi.org/10.1038/s41467-020-20821-w | DOI Listing |
Small
January 2025
SUNAG Laboratory, Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751 005, India.
Understanding the resistive switching (RS) behavior of oxide-based memory devices at nanoscale is crucial for advancement of high-integration density in-memory computing platforms. This study explores a comprehensive growth parameter space to address the RS behavior of pulsed-laser-deposited substoichiometric TiO (TiO) thin films in search of tailored nanoscale memristors with low-power consumption and high stability. Conductive-atomic-force-microscopy-based measurements facilitate deciphering the switching behavior at nanoscale, providing a direct avenue to understand the microstructure-property relationships.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, U.K.
Accurate prediction of chlorophyll- (Chl-) concentrations, a key indicator of eutrophication, is essential for the sustainable management of lake ecosystems. This study evaluated the performance of Kolmogorov-Arnold Networks (KANs) along with three neural network models (MLP-NN, LSTM, and GRU) and three traditional machine learning tools (RF, SVR, and GPR) for predicting time-series Chl- concentrations in large lakes. Monthly remote-sensed Chl- data derived from Aqua-MODIS spanning September 2002 to April 2024 were used.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, D-70569 Stuttgart, Germany.
Effective potential methods, obtained by applying a quantum correction to a classical pair potential, are widely used for describing the thermophysical properties of fluids with mild nuclear quantum effects. In case of strong nuclear quantum effects, such as for liquid hydrogen and helium, the accuracy of these quantum corrections deteriorates significantly, but at present no simple alternatives are available. In this work, we solve this issue by developing a new, three-parameter corresponding-states principle that remains applicable in the regions of the phase diagram where quantum effects become significant.
View Article and Find Full Text PDFSci Rep
January 2025
Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China.
To achieve rapid and stable detumbling of a space noncooperative satellite, an adaptive variable admittance control method for the manipulator is proposed and verified through simulation study and the ground experiment. The control block diagram of the proposed method is presented, and the adaptive variable admittance compliant detumbling control model is established. The proposed controller includes the fixed admittance controller in manipulator task space, the adaptive pose compensator for the grasping point on docking ring, and the damping adaptive regulator based on manipulator joint angular velocity, and the stability is proven by the Lyapunov method.
View Article and Find Full Text PDFChaos
January 2025
Departamento de Física, Universidade Federal de Santa Catarina, Florianópolis 88040-900, Santa Catarina, Brazil.
The presence of chaos is ubiquitous in mathematical models of neuroscience. In experimental neural systems, chaos was convincingly demonstrated in membranes, neurons, and small networks. However, its effects on the brain have long been debated.
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