Extensive trial and error in the variable space is the main cause of low efficiency and high
cost in material development. The experimental tasks can be reduced significantly in the …

Artificial intelligence (AI) technology is being applied to various industries such as medical
care, security, education, and manufacturing, and its application is rapidly expanding. AI has …

Predicting chemical activation energies is one of the longstanding and important challenges
in computational chemistry. Recent advances have shown that machine learning can be …

Advancements in modern semiconductor devices increasingly depend on the utilization of
amorphous materials and the reduction of material thickness, pushing the boundaries of …

Recent advancements in artificial intelligence (AI), particularly in algorithms and computing
power, have led to the widespread adoption of AI techniques in various scientific and …

The main limitations of the current dynamic random access memory (DRAM) technology are
its scalability and power consumption. These constraints can be overcome by using an In …

The recent technological progresses in lithography and patterning techniques used in the
integration of nanoelectronic devices open the possibility to create complex multilayer stacks …

기계학습, 심층학습과 같은 인공지능 기술의 발달로 재료과학 분야에서도 컴퓨터 계산을 통한
재료의 특성을 예측하고자 하는 학문적 움직임이 활발히 일어나고 있다. 이 연구는 큰 밴드갭을 …