Yihuan Zhao
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Author Swipe
View article: Integrating machine learning, docking analysis, molecular dynamics, and experimental validation for accelerated discovery of novel FLT3 inhibitors against AML
Integrating machine learning, docking analysis, molecular dynamics, and experimental validation for accelerated discovery of novel FLT3 inhibitors against AML Open
Acute myeloid leukemia (AML) is a malignant clonal disorder driven by the excessive proliferation of immature myeloid cells in the bone marrow and blood, often linked to Fms-like tyrosine kinase 3 ( FLT3 ) mutations, which occur in about o…
View article: Combined machine learning models, docking analysis, molecular dynamics and experimental validation for the rapid design of novel FLT3 inhibitors against AML
Combined machine learning models, docking analysis, molecular dynamics and experimental validation for the rapid design of novel FLT3 inhibitors against AML Open
Acute myeloid leukemia (AML) is a malignant clonal disorder driven by the excessive proliferation of immature myeloid cells in the bone marrow and blood, often linked to Fms-like tyrosine kinase 3 (FLT3) mutations, which occur in about one…
View article: Combined machine learning models, docking analysis, ADMET studies and molecular dynamics simulations for the design of novel FAK inhibitors against glioblastoma
Combined machine learning models, docking analysis, ADMET studies and molecular dynamics simulations for the design of novel FAK inhibitors against glioblastoma Open
Gliomas, particularly glioblastoma (GBM), are highly aggressive brain tumors with poor prognosis and high recurrence rates. This underscores the urgent need for novel therapeutic approaches. One promising target is Focal adhesion kinase (F…
View article: A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information
A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information Open
During the development process of complex products, selecting the best desirable alternative supplier is a challenge since an improperly selected alternative may cause losing capacity and increasing the cycle time and cost of development f…
View article: Ultra-fast triplet-triplet-annihilation-mediated high-lying reverse intersystem crossing triggered by participation of nπ*-featured excited states
Ultra-fast triplet-triplet-annihilation-mediated high-lying reverse intersystem crossing triggered by participation of nπ*-featured excited states Open
View article: Data-driven machine learning models for the quick and accurate prediction of thermal stability properties of OLED materials
Data-driven machine learning models for the quick and accurate prediction of thermal stability properties of OLED materials Open
Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, the further development and commercialization of OLEDs requires higher-quality OLED materials, including materials with a high thermal stab…
View article: Data-driven machine learning models for the quick and accurate prediction of thermal stability properties of OLED materials
Data-driven machine learning models for the quick and accurate prediction of thermal stability properties of OLED materials Open
Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, the further development and commercialization of OLEDs requires higher-quality OLED materials, including materials with a high thermal stab…
View article: Data-driven machine learning models for the quick and accurate prediction of Tg and Td of OLED materials
Data-driven machine learning models for the quick and accurate prediction of Tg and Td of OLED materials Open
Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, further development and commercialization of OLEDs requires higher-quality OLED materials, including high thermal stability associated with…
View article: Data-driven machine learning models for the quick and accurate prediction of Tg and Td of OLED materials
Data-driven machine learning models for the quick and accurate prediction of Tg and Td of OLED materials Open
Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, further development and commercialization of OLEDs requires higher-quality OLED materials, including high thermal stability associated with…
View article: Machine Learning based Framework for Quick Prediction of Tg and Td of OLED Materials
Machine Learning based Framework for Quick Prediction of Tg and Td of OLED Materials Open
Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, further development and commercialization of OLEDs requires higher-quality OLED materials, including high thermal stability associated with…
View article: Machine Learning based Framework for Quick Prediction of Tg and Td of OLED Materials
Machine Learning based Framework for Quick Prediction of Tg and Td of OLED Materials Open
Organic light-emitting-diode (OLED) materials have exhibited a wide range of applications. However, further development and commercialization of OLEDs requires higher-quality OLED materials, including high thermal stability associated with…
View article: Cover Feature: Acquiring High‐Performance Deep‐Blue OLED Emitters through an Unexpected Blueshift Color‐Tuning Effect Induced by Electron‐Donating ‐OMe Substituents (Chem. Eur. J. 32/2018)
Cover Feature: Acquiring High‐Performance Deep‐Blue OLED Emitters through an Unexpected Blueshift Color‐Tuning Effect Induced by Electron‐Donating ‐OMe Substituents (Chem. Eur. J. 32/2018) Open
Using 7-(diphenylamino)-4-(phenoxy)coumarin as the molecular framework, this work reports an unexpected blueshift color-tuning effect induced by moderate EDG -OMe substituents on the phenoxy moiety. With the aid of theoretical calculations…