Quantitative Resonance Theory Based on the Clar Sextet Model

Author(s):  
Yang Wang
Keyword(s):  
2019 ◽  
Author(s):  
M. Alexander Ardagh ◽  
Manish Shetty ◽  
Anatoliy Kuznetsov ◽  
Qi Zhang ◽  
Phillip Christopher ◽  
...  

Catalytic enhancement of chemical reactions via heterogeneous materials occurs through stabilization of transition states at designed active sites, but dramatically greater rate acceleration on that same active site is achieved when the surface intermediates oscillate in binding energy. The applied oscillation amplitude and frequency can accelerate reactions orders of magnitude above the catalytic rates of static systems, provided the active site dynamics are tuned to the natural frequencies of the surface chemistry. In this work, differences in the characteristics of parallel reactions are exploited via selective application of active site dynamics (0 < ΔU < 1.0 eV amplitude, 10<sup>-6</sup> < f < 10<sup>4</sup> Hz frequency) to control the extent of competing reactions occurring on the shared catalytic surface. Simulation of multiple parallel reaction systems with broad range of variation in chemical parameters revealed that parallel chemistries are highly tunable in selectivity between either pure product, even when specific products are not selectively produced under static conditions. Two mechanisms leading to dynamic selectivity control were identified: (i) surface thermodynamic control of one product species under strong binding conditions, or (ii) catalytic resonance of the kinetics of one reaction over the other. These dynamic parallel pathway control strategies applied to a host of chemical conditions indicate significant potential for improving the catalytic performance of many important industrial chemical reactions beyond their existing static performance.


Author(s):  
Jean-François Bony ◽  
Laurent Michel ◽  
Thierry Ramond

Nature ◽  
1934 ◽  
Vol 133 (3374) ◽  
pp. 983-983
Author(s):  
E. B. WEDMORE

2014 ◽  
Vol 543-547 ◽  
pp. 1934-1938
Author(s):  
Ming Xiao

For a clustering algorithm in two-dimension spatial data, the Adaptive Resonance Theory exists not only the shortcomings of pattern drift and vector module of information missing, but also difficultly adapts to spatial data clustering which is irregular distribution. A Tree-ART2 network model was proposed based on the above situation. It retains the memory of old model which maintains the constraint of spatial distance by learning and adjusting LTM pattern and amplitude information of vector. Meanwhile, introducing tree structure to the model can reduce the subjective requirement of vigilance parameter and decrease the occurrence of pattern mixing. It is showed that TART2 network has higher plasticity and adaptability through compared experiments.


1992 ◽  
Vol 03 (01) ◽  
pp. 57-63 ◽  
Author(s):  
Eamon P. Fulcher

WIS-ART merges the self-organising properties of Adaptive Resonance Theory (ART) with the operation of WISARD, an adaptive pattern recognition machine which uses discriminators of conventional Random Access Memories (RAMs). The result is an unsupervised pattern clustering system operating at near real-time that implements the leader algorithm. ART’s clustering is highly dependent upon the value of a “vigilance” parameter, which is set prior to training. However, for WIS-ART hierarchical clustering is performed automatically by the partitioning of discriminators into “multi-vigilance modules”. Thus, clustering may be controlled during the test phase according to the degree of discrimination (hierarchical level) required. Methods for improving the clustering characteristics of WIS-ART whilst still retaining stability are discussed.


Author(s):  
Derek Johnson ◽  
Mahdi Darzi ◽  
Chris Ulishney ◽  
Mehar Bade ◽  
Nima Zamani

Two-stroke engines are often used for their low cost, simplicity, and power density. However, these engines suffer efficiency penalties due to fuel short-circuiting. Increasing power density has previously been an area of focus for performance two-stroke engines — such as in dirt bikes. Smaller-displacement engines have also been used to power remote controlled cars, boats, and aircraft. These engines typically rely on gasoline or higher-octane liquid fuels. However, natural gas is an inherently knock-resistant fuel and small natural gas engines and generators could see increased market penetration. Power generators typically operate at a fixed frequency with varied load, which can take advantage of intake and exhaust system tuning. In addition, stationary engines may not be subject to size restrictions of optimal intake and exhaust systems. This paper examines methods to improve combustion stability, efficiency, and power density of a 29cc air-cooled two-stroke engine converted to operate on natural gas. Initial conversion showed significant penalties on delivery ratio, which lowered power density and efficiency. To overcome these issues a tuned intake pipe, two exhaust resonators, and a combustion dome were designed and tested. The engine was operated at 5400 RPM and fueling was adjusted to yield maximum brake-torque (MBT). All tests were conducted under wide-open throttle conditions. The intake and exhaust systems were designed based on Helmholtz resonance theory and empirical data. The engine utilized a two-piece cylinder head with removable combustion dome. The combustion dome was modified for optimal compression ratio while decreasing squish area and volume. With all designs incorporated, power increased from 0.22 kW to 1.07 kW — a factor of 4.86. Efficiency also increased from 7% to 12%. In addition to these performance gains, the coefficient of variation (COV) of indicated mean effective pressure (IMEP) decreased from just above 11% to less than 4%.


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