We present a new theoretical strategy, ab initio rate constants plus integration of rate equations, that is used to characterize the role of entropy in driving high-temperature/low-pressure hydrocarbon chemical kinetics typical of filament-assisted diamond growth environments. Twelve elementary processes were analyzed that produce a viable pathway for converting methane in a feed gas to acetylene. These calculations clearly relate the kinetics of this conversion to the properties of individual species, demonstrating that (1) loss of translational entropy restricts addition of hydrogen (and other radical species) to unsaturated carbon-carbon bonds, (2) rotational entropy determines the direction of the rate-limiting abstraction reactions, and (3) the overall pathway is enhanced by high beta-scission reaction rates driven by translational entropy. These results suggest that the proposed strategy is likely applicable to understand gas-phase chemistry occurring in the systems of combustion and other chemical vapor depositions.
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Acc Chem Res
January 2025
School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
ConspectusSymmetry is a pervasive phenomenon spanning diverse fields, from art and architecture to mathematics and science. In the scientific realms, symmetry reveals fundamental laws, while symmetry breaking─the collapse of certain symmetry─is the underlying cause of phenomena. Research on symmetry and symmetry breaking consistently provides valuable insights across disciplines, from parity violation in physics to the origin of homochirality in biology.
View Article and Find Full Text PDFPhys Eng Sci Med
January 2025
Amrita School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Bangalore, India.
Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogram (EEG) plays an important role in diagnosing PD as it offers a non-invasive continuous assessment of the disease progression and reflects these complex patterns. This study focuses on the non-linear analysis of resting state EEG signals in PD, with a gender-specific, brain region-specific, and EEG band-specific approach, utilizing recurrence plots (RPs) and machine learning (ML) algorithms for classification.
View Article and Find Full Text PDFNat Commun
January 2025
School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore, 637371, Singapore.
Designing efficient Ruthenium-based catalysts as practical anodes is of critical importance in proton exchange membrane water electrolysis. Here, we develop a self-assembly technique to synthesize 1 nm-thick rutile-structured high-entropy oxides (RuIrFeCoCrO) from naked metal ions assembly and oxidation at air-molten salt interface. The RuIrFeCoCrO requires an overpotential of 185 mV at 10 m A cm and maintains the high activity for over 1000 h in an acidic electrolyte via the adsorption evolution mechanism.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
Faculty of Chemistry and Geosciences, Vilnius University, 03225 Vilnius, Lithuania.
There is a growing focus on sustainability, characterized by making changes that anticipate future needs and adapting them to present requirements. Sustainability is reflected in various areas of materials science as well. Thus, more research is focused on the fabrication of advanced materials based on earth-abundant metals.
View Article and Find Full Text PDFEntropy (Basel)
January 2025
Department of Condensed Matter Physics, University of Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain.
Directed networks are essential for representing complex systems, capturing the asymmetry of interactions in fields such as neuroscience, transportation, and social networks. Directionality reveals how influence, information, or resources flow within a network, fundamentally shaping the behavior of dynamical processes and distinguishing directed networks from their undirected counterparts. Robust null models are crucial for identifying meaningful patterns in these representations, yet designing models that preserve key features remains a significant challenge.
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