Nonlinear Effect
The nonlinear effect refers to a nonlinear relationship between the enantiomeric excess of the product and the enantiomeric excess of the catalyst in asymmetric catalysis, which can amplify an initial chiral bias.
Core Facts
The chemical essence of the nonlinear effect lies in the fact that chiral catalyst molecules can form dimers or multimers, and different aggregation states have completely different catalytic activity and chiral selectivity.
In 1986, Kagan reported that in certain catalytic systems, the relationship between catalyst ee and product ee is nonlinear, that is, a positive nonlinear effect or a negative nonlinear effect.
Timeline (last 90 days)
Kagan's discovery of nonlinear effects and Soai's autocatalytic reaction together form the theoretical cornerstone for understanding the origin of homochirality in life.
In an ideal linear relationship, the ee value of the catalyst should be roughly equal to the ee value of the product; but actual systems often deviate from this expectation, showing amplification or reduction.
This chemistry prize was awarded for the discovery of nonlinear effects and autocatalysis in asymmetric organic synthesis.
The research of Kagan and Soai revealed that under certain conditions, a small excess of one chiral molecule can trigger a chain reaction, greatly amplifying the proportion of that chirality in the product, far beyond the proportion initially input.
Common amplification mechanisms include nonlinear effects, autocatalysis, and crystallization-induced chiral amplification.
Autocatalysis and nonlinear effects often appear together, jointly forming the chemical basis of chiral amplification.
Kagan found that in certain asymmetric catalytic systems, using a catalyst with a low ee value can nonetheless yield a product with a high ee value, and even a positive nonlinear effect occurs, in which a small amount of chiral catalyst can induce a large amount of chiral product.
In 1986, Kagan's team reported three reactions and found that the relationship between catalyst purity and product purity was not linear but curved—sometimes a catalyst of only half purity could produce a product of far higher purity, which is known as the nonlinear effect.
The chemical essence of the nonlinear effect lies in the fact that chiral catalyst molecules can form dimers or multimers, and different aggregation states have completely different catalytic activity and chiral selectivity.
In 1986, Henry B. Cogon revealed the nonlinear effect, demonstrating that an initial deviation so small it is almost negligible can be amplified in the reaction far beyond expectations, and that product purity can be higher than catalyst purity.
7 more timeline events
All Facts (17)
The chemical essence of the nonlinear effect lies in the fact that chiral catalyst molecules can form dimers or multimers, and different aggregation states have completely different catalytic activity and chiral selectivity.
80%Partially VerifiedIn 1986, Kagan reported that in certain catalytic systems, the relationship between catalyst ee and product ee is nonlinear, that is, a positive nonlinear effect or a negative nonlinear effect.
80%UnverifiedKagan's discovery of nonlinear effects and Soai's autocatalytic reaction together form the theoretical cornerstone for understanding the origin of homochirality in life.
60%UnverifiedIn an ideal linear relationship, the ee value of the catalyst should be roughly equal to the ee value of the product; but actual systems often deviate from this expectation, showing amplification or reduction.
50%UnverifiedThe research of Kagan and Soai revealed that under certain conditions, a small excess of one chiral molecule can trigger a chain reaction, greatly amplifying the proportion of that chirality in the product, far beyond the proportion initially input.
50%UnverifiedAutocatalysis and nonlinear effects often appear together, jointly forming the chemical basis of chiral amplification.
50%UnverifiedThis chemistry prize was awarded for the discovery of nonlinear effects and autocatalysis in asymmetric organic synthesis.
50%UnverifiedCommon amplification mechanisms include nonlinear effects, autocatalysis, and crystallization-induced chiral amplification.
50%UnverifiedKagan found that in certain asymmetric catalytic systems, using a catalyst with a low ee value can nonetheless yield a product with a high ee value, and even a positive nonlinear effect occurs, in which a small amount of chiral catalyst can induce a large amount of chiral product.
50%UnverifiedIn 1986, Kagan's team reported three reactions and found that the relationship between catalyst purity and product purity was not linear but curved—sometimes a catalyst of only half purity could produce a product of far higher purity, which is known as the nonlinear effect.
50%UnverifiedIn 1986, Henry B. Cogon revealed the nonlinear effect, demonstrating that an initial deviation so small it is almost negligible can be amplified in the reaction far beyond expectations, and that product purity can be higher than catalyst purity.
50%UnverifiedCogon discovered that the ee value of the product and the ee value of the catalyst can exhibit a nonlinear relationship; for example, using a chiral catalyst with an ee value of only 10% may still yield a product with an ee value as high as above 90%.
50%UnverifiedHenri B. Kagan revealed a nonlinear effect: under certain conditions, a tiny difference in catalyst chirality can have a huge impact on the proportion of enantiomers in the product.
50%UnverifiedKagan and Soai were recognized for the discovery of nonlinear effects and autocatalysis in asymmetric organic synthesis.
50%UnverifiedIn 1986, Kagan published findings on nonlinear effects, discovering that product ratios do not change linearly with the catalyst but follow a curve, which can significantly increase the proportion of the target mirror-image molecule.
50%UnverifiedKagan experimentally confirmed the nonlinear effect model in a sulfide oxidation reaction, and the relevant findings were published in 1986.
50%UnverifiedWhen measurement error is present in the independent variable x, a originally apparent nonlinear effect may be smoothed out in the data, appearing close to linear.
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