Machine Learning in Materials Science

Abstract Development of computation‐ready metal–organic framework databases (MOF DBs) has accelerated high‐throughput computational screening (HTCS) of materials to identify the best candidates for gas storage and separation. These DBs were constructed using structural curations to make MOFs directly usable for molecu…

• İLKNUR ERUÇAR FINDIKÇI

Abstract Development of computation‐ready metal–organic framework databases (MOF DBs) has accelerated high‐throughput computational screening (HTCS) of materials to identify the best candidates for gas storage and separation. These DBs were constructed using structural curations to make MOFs directly usable for molecu…

• ÇİĞDEM ALTINTAŞ

Abstract Development of computation‐ready metal–organic framework databases (MOF DBs) has accelerated high‐throughput computational screening (HTCS) of materials to identify the best candidates for gas storage and separation. These DBs were constructed using structural curations to make MOFs directly usable for molecu…

• SEDA KESKİN AVCI

Abstract Development of computation‐ready metal–organic framework databases (MOF DBs) has accelerated high‐throughput computational screening (HTCS) of materials to identify the best candidates for gas storage and separation. These DBs were constructed using structural curations to make MOFs directly usable for molecu…

• SEDA KESKİN AVCI

An overview of computed thermoelectric properties for more than 48 000 inorganic compounds from the Materials Project (MP).

• UMUT AYDEMİR

Epitaxial assembly of block-copolymer films (see Figure) onto chemically nanopatterned substrates results in arrays of nanoscopic domains that are defect-free, oriented, and registered with the underlying substrate. The range of dimensions of features (or periodicity of structures) that can be patterned with perfectio…

screening of the chemogenomic space, to provide novel DTIs which can be experimentally pursued. The source code, trained "ready-to-use" prediction models, all datasets and the results of this study are available at ; https://github.com/cansyl/DEEPscreen.

• TUNCA DOĞAN

screening of the chemogenomic space, to provide novel DTIs which can be experimentally pursued. The source code, trained "ready-to-use" prediction models, all datasets and the results of this study are available at ; https://github.com/cansyl/DEEPscreen.

• AHMET SÜREYYA RİFAİOĞLU
• ESRA NALBAT
• TUNCA DOĞAN

Electronic transport in materials is governed by a series of tensorial properties such as conductivity, Seebeck coefficient, and effective mass. These quantities are paramount to the understanding of materials in many fields from thermoelectrics to electronics and photovoltaics. Transport properties can be calculated…

• UMUT AYDEMİR

The acceleration in design of new metal organic frameworks (MOFs) has led scientists to focus on high-throughput computational screening (HTCS) methods to quickly assess the promises of these fascinating materials in various applications. HTCS studies provide a massive amount of structural property and performance dat…

• ÇİĞDEM ALTINTAŞ

The acceleration in design of new metal organic frameworks (MOFs) has led scientists to focus on high-throughput computational screening (HTCS) methods to quickly assess the promises of these fascinating materials in various applications. HTCS studies provide a massive amount of structural property and performance dat…

• SEDA KESKİN AVCI

The acceleration in design of new metal organic frameworks (MOFs) has led scientists to focus on high-throughput computational screening (HTCS) methods to quickly assess the promises of these fascinating materials in various applications. HTCS studies provide a massive amount of structural property and performance dat…

• RAMAZAN YILDIRIM