We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The soni...
The rapid development of artificial intelligence techniques and future advanced robot systems sparks emergent demand on the accurate perception and understanding of the external environments via visual sensing systems that can co-locate the self-adap...
The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gr...
Memristors based on 2D layered materials could provide biorealistic ionic interactions and potentially enable construction of energy-efficient artificial neural networks capable of faithfully emulating neuronal interconnections in human brains. To bu...
The global burden of cancer, severe diagnostic bottlenecks in underserved regions, and underfunded health care systems are fueling the need for inexpensive, rapid, and treatment-informative diagnostics. On the basis of advances in computational optic...
This paper presents aligned carbon nanotube (CNT) synaptic transistors for large-scale neuromorphic computing systems. The synaptic behavior of these devices is achieved via charge-trapping effects, commonly observed in carbon-based nanoelectronics. ...
In the present study, we demonstrate a tunneling nanogap technique to identify individual RNA nucleotides, which can be used as a mechanism to read the nucleobases for direct sequencing of RNA in a solid-state nanopore. The tunneling nanogap is compo...
We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the human ocular microbiome and resides on the cornea and conjunctiva. Using S. aureus-specific antibodies a...
Neuromorphic or "brain-like" computation is a leading candidate for efficient, fault-tolerant processing of large-scale data as well as real-time sensing and transduction of complex multivariate systems and networks such as self-driving vehicles or I...
Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level precision. This pr...