Machine learning-guided high throughput nanoparticle design

Ana Ortiz‐Perez

doi:10.1039/d4dd00104d

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Machine learning-guided high throughput nanoparticle design

2024-01-01

DOI：10.1039/d4dd00104d

Original

Original request for help

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Abstract

En 中文

Designing nanoparticles with desired properties is challenging due to the large combinatorial space and complex structure–function relationships. This process can be accelerated by combining microfluidics, high content imaging and active learning.

Keywords:

MICROFLUIDIC PLATFORM

Journal

Digital Discovery

IF:

5.6

Papers:

997

Citations:

1.7K

Organization

Eindhoven University of Technology

Scholars:

1.6W

Papers: 1.5W

Citations: 2.2W

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