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Debra J. Searles

Researcher at University of Queensland

Publications -  229
Citations -  9010

Debra J. Searles is an academic researcher from University of Queensland. The author has contributed to research in topics: Fluctuation theorem & Ab initio. The author has an hindex of 40, co-authored 221 publications receiving 7589 citations. Previous affiliations of Debra J. Searles include Kavli Institute for Theoretical Physics & University of Basel.

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The Fluctuation Theorem

TL;DR: The Fluctuation Theorem (FT) as discussed by the authors gives an analytical expression for the probability of observing Second Law violating dynamicaluctuations in thermostatted dissipative non-equilibrium systems.
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Experimental Demonstration of Violations of the Second Law of Thermodynamics for Small Systems and Short Time Scales

TL;DR: The fluctuation theorem is experimentally demonstrated by following the trajectory of a colloidal particle captured in an optical trap that is translated relative to surrounding water molecules to show entropy consumption can occur over colloidal length and time scales.
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Equilibrium microstates which generate second law violating steady states

TL;DR: It is proved that the measure of those phases that generate second law violating phase space trajectories vanishes exponentially with time.
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Coordination of Atomic Co-Pt Coupling Species at Carbon Defects as Active Sites for Oxygen Reduction Reaction.

TL;DR: A locally distributed atomic Pt-Co nitrogen-carbon-based catalyst with high activity and robust durability for ORR (267 times higher than commercial Pt/C in mass activity) and a high selectivity for the 4e- pathway in ORR, differing from the reported 2 e- pathway characteristic of atomic Pt catalysts.
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Fluctuation Theorems

TL;DR: Fluctuation theorems as discussed by the authors describe the statistical fluctuations in time-averaged properties of many-particle systems such as fluids driven to nonequilibrium states, and provide some of the very few analytical expressions that describe none-ilibrium states Quantitative predictions on fluctuations in small systems that are monitored over short periods can also be made.