Science
Machine-learning helps sort out massive materials’ databases – Mirage News
EPFL and MIT scientists have used machine-learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic…
EPFL and MIT scientists have used machine-learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.Metal-organic frameworks (MOFs) are a class of materials that contain nano-sized pores. These pores give MOFs record-breaking internal surface areas, which can measure up to 7,800 m2 in a single gram of material. As a result, MOFs are extremely versatile and find multiple uses: separating petrochemicals and gases, mimicking DN…
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