Deterministic lateral displacement (DLD) pillar arrays are an efficient technology to sort, separate and enrich micrometre-scale particles, which include parasites, bacteria, blood cells and circulating tumour cells in blood. However, this technology has not been translated to the true nanoscale, where it could function on biocolloids, such as exosomes. Exosomes, a key target of 'liquid biopsies', are secreted by cells and contain nucleic acid and protein information about their originating tissue. One challenge in the study of exosome biology is to sort exosomes by size and surface markers. We use manufacturable silicon processes to produce nanoscale DLD (nano-DLD) arrays of uniform gap sizes ranging from 25 to 235 nm. We show that at low Péclet (Pe) numbers, at which diffusion and deterministic displacement compete, nano-DLD arrays separate particles between 20 to 110 nm based on size with sharp resolution. Further, we demonstrate the size-based displacement of exosomes, and so open up the potential for on-chip sorting and quantification of these important biocolloids.

Graphical Abstract Highlights d The exRNA Atlas provides access to human exRNA profiles and web-accessible tools d Atlas analysis reveals six exRNA cargo types present across five human biofluids d Five of the cargo types associate with specific vesicular and non-vesicular carriers d These findings and resources empower studies of extracellular RNA communication An extracellular RNA atlas from five human biofluids (serum, plasma, cerebrospinal fluid, saliva, and urine) reveals six extracellular RNA cargo types, including both vesicular and nonvesicular carriers. SUMMARY To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously.To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Performance of graphene electronics is limited by contact resistance associated with the metal-graphene (M-G) interface, where unique transport challenges arise as carriers are injected from a 3D metal into a 2D-graphene sheet. In this work, enhanced carrier injection is experimentally achieved in graphene devices by forming cuts in the graphene within the contact regions. These cuts are oriented normal to the channel and facilitate bonding between the contact metal and carbon atoms at the graphene cut edges, reproducibly maximizing "edge-contacted" injection. Despite the reduction in M-G contact area caused by these cuts, we find that a 32% reduction in contact resistance results in Cu-contacted, two-terminal devices, while a 22% reduction is achieved for top-gated graphene transistors with Pd contacts as compared to conventionally fabricated devices. The crucial role of contact annealing to facilitate this improvement is also elucidated. This simple approach provides a reliable and reproducible means of lowering contact resistance in graphene devices to bolster performance. Importantly, this enhancement requires no additional processing steps.

Rapid, continuous flow enrichment of EVs is enabled by integrating >1000 nanoDLD arrays.