Recent advances in computing power have enabled the generation of large datasets for materials,enabling data-driven approaches to problem-solving in materials science,including materials discovery.Machine learning is ...Recent advances in computing power have enabled the generation of large datasets for materials,enabling data-driven approaches to problem-solving in materials science,including materials discovery.Machine learning is a primary tool for manipulating such large datasets,predicting unknown material properties and uncovering relationships between structure and property.Among state-of-the-art machine learning algorithms,gradient-boosted regression trees(GBRT)are known to provide highly accurate predictions,as well as interpretable analysis based on the importance of features.Here,in a search for lead-free perovskites for use in solar cells,we applied the GBRT algorithm to a dataset of electronic structures for candidate halide double perovskites to predict heat of formation and bandgap.Statistical analysis of the selected features identifies design guidelines for the discovery of new lead-free perovskites.展开更多
The use of 3D food printing as an alternative to manufacturing customized food is gaining popularity.In this study,functional powders of guava leaf (GL),green tea (GT),and barley sprouts (BS) were tested as edible ink...The use of 3D food printing as an alternative to manufacturing customized food is gaining popularity.In this study,functional powders of guava leaf (GL),green tea (GT),and barley sprouts (BS) were tested as edible ink ingredients for printing cheesecake,and their physicochemical and functional properties were evaluated.Particle size and water and oil holding capacities were highest in GL powder,whereas the water-soluble index was highest in BS.In functional powder-added cheesecake,pseudoplastic and shear-thinning behavior was observed which is ideal for 3D printing.The shear modulus (1.87 kPa) of the control cheesecake (without functional powder) was significantly increased to 5 kPa or higher by adding functional powder.The in vitro glycemic index was lowest in GL cheesecake,whereas antioxidant activity and polyphenol content were highest in GT cheesecake.GL and GT powders would be beneficial as an edible ink to improve functional properties,such as antioxidant activity for GT and blood-glucose-lowering effect for BS,with enhanced printability and textural stability of 3D printed cheesecake.展开更多
基金This research was supported by the Nano·Material Technology Development Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Science and ICT(NRF-2016M3A7B4025408 and NRF-2017M3A7B4049366).
文摘Recent advances in computing power have enabled the generation of large datasets for materials,enabling data-driven approaches to problem-solving in materials science,including materials discovery.Machine learning is a primary tool for manipulating such large datasets,predicting unknown material properties and uncovering relationships between structure and property.Among state-of-the-art machine learning algorithms,gradient-boosted regression trees(GBRT)are known to provide highly accurate predictions,as well as interpretable analysis based on the importance of features.Here,in a search for lead-free perovskites for use in solar cells,we applied the GBRT algorithm to a dataset of electronic structures for candidate halide double perovskites to predict heat of formation and bandgap.Statistical analysis of the selected features identifies design guidelines for the discovery of new lead-free perovskites.
基金funded in 2020-2021(grant number PJ01453706)by the Korea Rural Development Administration.
文摘The use of 3D food printing as an alternative to manufacturing customized food is gaining popularity.In this study,functional powders of guava leaf (GL),green tea (GT),and barley sprouts (BS) were tested as edible ink ingredients for printing cheesecake,and their physicochemical and functional properties were evaluated.Particle size and water and oil holding capacities were highest in GL powder,whereas the water-soluble index was highest in BS.In functional powder-added cheesecake,pseudoplastic and shear-thinning behavior was observed which is ideal for 3D printing.The shear modulus (1.87 kPa) of the control cheesecake (without functional powder) was significantly increased to 5 kPa or higher by adding functional powder.The in vitro glycemic index was lowest in GL cheesecake,whereas antioxidant activity and polyphenol content were highest in GT cheesecake.GL and GT powders would be beneficial as an edible ink to improve functional properties,such as antioxidant activity for GT and blood-glucose-lowering effect for BS,with enhanced printability and textural stability of 3D printed cheesecake.
