Publications by authors named "Antonio C M Padilha"
Memristors (MRs) are considered promising devices with the enormous potential to replace complementary metal-oxide-semiconductor (CMOS) technology, which approaches the scale limit. Efforts to fabricate MRs-based hybrid materials may result in suitable operating parameters coupled to high mechanical flexibility and low cost. Metal-organic frameworks (MOFs) arise as a favorable candidate to cover such demands.
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- Recent computational advances have improved algorithms and technologies for simulating molecular and materials systems, leading to a significant increase in available data.
- The rise of computational databases and democratization of data access has opened up new opportunities for data-driven methods in addressing chemical and materials challenges.
- Machine learning is increasingly used for predicting new materials and properties, but successful application requires expert knowledge to navigate technical details, indicating a need for further development in this area to benefit various countries.