AI is being leveraged to provide machines with the capacity to match or even outperform humans in many endeavors. So what does this mean for the synthetic chemist?
Results for "Machine learning"
Designing auxetics with artificial intelligence: Identifying next-generation metamaterial designs
Researchers from UC Berkeley are utilizing deep learning to bypass iterative finite element calculations. Their deep learning model is trained using finite element simulation data to predict the deformation behavior of favorable designs.
Automating the Production of Advanced Materials
Engineers create a robotic platform to automate the production of new, functional polymers for advanced materials.
A Journey Through the Last Decade
Advanced Science News takes a look back at the major achievements and stories in science from the 2010s.
Epidermal Electronics – A Step Closer to Wearable Diagnostic “Labs”
Skin-friendly epidermal electronic devices fabricated using flexible, stretchable, and degradable protein-based substrates could offer a viable solution to real-time health and fitness monitoring.
Methods Perspectives: Assessing Battery Interfaces via NMR
Michal Leskes and Shira Haber assess the capabilities of NMR in analyzing solid-state interfaces.
The Translational “Valley of Death” for Engineered Tissues
Whilst tissue engineering has benefited modern surgery, thousands of patents fail to see real-world applications.
Hybrid Modeling to Address Cancer Complexity
State of the art of mathematical hybrid modeling of cancer development and treatment.
A Quantum Autoencoder via Quantum Adders
A quantum autoencoder via approximate quantum adders in the Rigetti cloud quantum computer is carried out employing up to three qubits.
Cell-free DNA Fragments to Identify Cancer
It is now possible to distinguish the pattern of DNA fragments of normal cells from cancerous cells within the blood of individuals with surgically-operable early stage cancers.1 Regions of the genome have their own local differences in cancer-specific,...
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