Exceptionally high decarboxylation rate of a primary aliphatic acyloxy radical determined by radical product yield analysis and quantitative 1 H-CIDNP spectroscopy

2011 ◽  
Vol 24 (9) ◽  
pp. 809-820 ◽  
Author(s):  
Alicia Fraind ◽  
Ryan Turncliff ◽  
Teri Fox ◽  
Justin Sodano ◽  
Lev R. Ryzhkov
Keyword(s):  
Product Yield ◽  
Radical Product ◽  
Yield Analysis ◽  
Decarboxylation Rate

Pyrolysis of three different categories of automotive tyre wastes: Product yield analysis and characterization

2018 ◽  
Vol 135 ◽  
pp. 379-389 ◽  
Author(s):  
Rohit Kumar Singh ◽  
Biswajit Ruj ◽  
Anusua Jana ◽  
Sourav Mondal ◽  
Banibrata Jana ◽  
...  
Keyword(s):  
Product Yield ◽  
Yield Analysis

Energy Recovery from Tyre Waste Pyrolysis: Product Yield Analysis and Characterization

2019 ◽  
pp. 33-43 ◽  
Author(s):  
Rohit Kumar Singh ◽  
Biswajit Ruj ◽  
Anup Kumar Sadhukhan ◽  
Parthapratim Gupta
Keyword(s):  
Energy Recovery ◽  
Pyrolysis Product ◽  
Product Yield ◽  
Yield Analysis ◽  
Tyre Waste

CH3CO + O2 + M (M = He, N2) Reaction Rate Coefficient Measurements and Implications for the OH Radical Product Yield

2015 ◽  
Vol 119 (28) ◽  
pp. 7481-7497 ◽  
Author(s):  
Vassileios C. Papadimitriou ◽  
Emmanuel S. Karafas ◽  
Tomasz Gierczak ◽  
James B. Burkholder
Keyword(s):  
Reaction Rate ◽  
Rate Coefficient ◽  
Product Yield ◽  
Oh Radical ◽  
Reaction Rate Coefficient ◽  
Radical Product

Device Selection for Failure Analysis of Chain Fails Using Diagnosis Driven Yield Analysis

2011 ◽  
Author(s):  
Chris Schuermyer ◽  
Brady Benware ◽  
Graham Rhodes ◽  
Davide Appello ◽  
Vincenzo Tancorre ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Case Studies ◽  
Yield Analysis ◽  
Analysis Methodology ◽  
Device Selection ◽  
Selection For ◽  
Random Defects

Abstract This work presents the first application of a diagnosis driven approach for identifying systematic chain fail defects in order to reduce the time spent in failure analysis. The zonal analysis methodology that is applied separates devices into systematic and random populations of chain fails in order to prevent submitting random defects for failure analysis. Two silicon case studies are presented to validate the production worthiness of diagnosis driven yield analysis for chain fails. The defects uncovered in these case studies are very subtle and would be difficult to identify with any other methodology.

Advanced Scan Diagnosis Based Fault Isolation and Defect Identification for Yield Learning

2005 ◽  
Author(s):  
Chris Eddleman ◽  
Nagesh Tamarapalli ◽  
Wu-Tung Cheng
Keyword(s):  
Failure Analysis ◽  
Fault Location ◽  
Effective Means ◽  
Fault Isolation ◽  
Yield Enhancement ◽  
Yield Analysis ◽  
Isolation Techniques ◽  
Yield Learning ◽  
Time Required ◽  
Inspection Data

Abstract Yield analysis of sub-micron devices is an ever-increasing challenge. The difficulty is compounded by the lack of in-line inspection data as many companies adopt foundry or fab-less models for acquiring wafers. In this scenario, failure analysis is increasingly critical to help drive yields. Failure analysis is a process of fault isolation, or a method of isolating failures as precisely as possible followed by identification of a physical defect. As the number of transistors and metal layers increase, traditional fault isolation techniques are less successful at isolating a cause of failures. Costs are increasing due to the amount of time needed to locate the physical defect. One solution to the yield analysis problem is scan diagnosis based fault isolation. Previous scan diagnosis based techniques were limited with little information about the type of fault and confidence of diagnosis. With new scan diagnosis algorithms it is now possible to not only isolate, but to identify the type of fault as well as assigning a confidence ranking prior to any destructive analysis. This paper presents multiple case studies illustrating the application of scan diagnosis as an effective means to achieve yield enhancement. The advanced scan diagnostic tool used in this study provides information about the fault type as well as fault location. This information focuses failure analysis efforts toward a suspected defect, decreasing the cycle time required to determine root cause, as well as increasing the over all success rate.

Zinc Sulfamate Catalyzed Efficient Selective Synthesis of Benzimidazole Derivatives under Ambient Conditions

2019 ◽  
Vol 16 (9) ◽  
pp. 740-749
Author(s):  
Sushil R. Mathapati ◽  
Arvind H. Jadhav ◽  
Mantosh B. Swami ◽  
Jairaj K. Dawle
Keyword(s):  
Benzimidazole Derivative ◽  
Sulfamic Acid ◽  
Aromatic Aldehydes ◽  
Catalytic Amount ◽  
Product Yield ◽  
Lewis Acidity ◽  
Benzimidazole Derivatives ◽  
Ambient Conditions ◽  
Reaction Condition ◽  
Green Approach

Zinc sulfamate (Zn(NH2SO3)2 is a derivative of sulfamic acid (H3NSO3) which possesses “Lewis acidity” and finds well suited in a number of catalytic applications. The present paper describes an efficient, eco-friendly, and clean synthesis of 2-substituted benzimidazole derivatives by reacting diverse o-phenylenediamine with various substituted aromatic aldehydes using a catalytic amount of zinc sulfamate in ethanol at ambient temperature. As a result, 10 mol.% of Zinc sulfamate catalyst showed 92% of respective product yield with 100% conversion using short reaction period in ethanol. Meanwhile, effect of reaction parameters, such as amount of catalyst, different solvents, and reaction temperature on reaction product, was also studied. In addition, in the optimized reaction condition various substituted biological important benzimidazoles derivatives were prepared by using optimized reaction condition in good to efficient yield. In addition, possible reaction mechanism in the presence of zinc sulfamate for the preparation of benzimidazole derivative was sketched and discussed. The present green approach showed significances with faster reaction rate with inexpensive catalyst, which showed excellent and clean yield of benzimidazole in mild reaction condition with easy work-up procedure.

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