6 research outputs found
Determining thresholds using adaptive procedures and psychometric fits: evaluating efficiency using theory, simulations, and human experiments
When measuring thresholds, careful selection of stimulus amplitude can increase efficiency by increasing the precision of psychometric fit parameters (e.g., decreasing the fit parameter error bars). To find efficient adaptive algorithms for psychometric threshold (“sigma”) estimation, we combined analytic approaches, Monte Carlo simulations, and human experiments for a one-interval, binary forced-choice, direction-recognition task. To our knowledge, this is the first time analytic results have been combined and compared with either simulation or human results. Human performance was consistent with theory and not significantly different from simulation predictions. Our analytic approach provides a bound on efficiency, which we compared against the efficiency of standard staircase algorithms, a modified staircase algorithm with asymmetric step sizes, and a maximum likelihood estimation (MLE) procedure. Simulation results suggest that optimal efficiency at determining threshold is provided by the MLE procedure targeting a fraction correct level of 0.92, an asymmetric 4-down, 1-up staircase targeting between 0.86 and 0.92 or a standard 6-down, 1-up staircase. Psychometric test efficiency, computed by comparing simulation and analytic results, was between 41 and 58 % for 50 trials for these three algorithms, reaching up to 84 % for 200 trials. These approaches were 13–21 % more efficient than the commonly used 3-down, 1-up symmetric staircase. We also applied recent advances to reduce accuracy errors using a bias-reduced fitting approach. Taken together, the results lend confidence that the assumptions underlying each approach are reasonable and that human threshold forced-choice decision making is modeled well by detection theory models and mimics simulations based on detection theory models.National Institute on Deafness and Other Communication Disorders (U.S.) (Grants R01-DC04158, R56-DC12038 and R03-DC013635
Selective Activation of Methane on Single-Atom Catalyst of Rhodium Dispersed on Zirconia for Direct Conversion
Direct methane conversion into value-added
products has become
increasingly important. Because of inertness of methane, cleaving
the first C–H bond has been very difficult, requiring high
reaction temperature on the heterogeneous catalysts. Once the first
C–H bond becomes activated, the remaining C–H bonds
are successively dissociated on the metal surface, hindering the direct
methane conversion into chemicals. Here, a single-atom Rh catalyst
dispersed on ZrO<sub>2</sub> surface has been synthesized and used
for selective activation of methane. The Rh single atomic nature was
confirmed by extended X-ray fine structure analysis, electron microscopy
images, and diffuse reflectance infrared Fourier transform spectroscopy.
A model of the single-atom Rh/ZrO<sub>2</sub> catalyst was constructed
by density functional theory calculations, and it was shown that CH<sub>3</sub> intermediates can be energetically stabilized on the single-atom
catalyst. The direct conversion of methane was performed using H<sub>2</sub>O<sub>2</sub> in the aqueous solution or using O<sub>2</sub> in gas phase as oxidants. Whereas Rh nanoparticles produced CO<sub>2</sub> only, the single-atom Rh catalyst produced methanol in aqueous
phase or ethane in gas phase