We present a microfluidic device that detects trace concentrations of drugs of abuse in saliva within minutes using surface-enhanced Raman spectroscopy (SERS). Its operation is demonstrated using methamphetamine. The detection scheme exploits concentration gradients of chemicals, fostered by the laminar flow in the device, to control the interactions between the analyte, silver nanoparticles (Ag-NPs), and a salt. Also, since all species interact while advecting downstream, the relevant reaction coordinates occur with respect to the position in the channel. The system was designed to allow the analyte first to diffuse into the side stream containing the Ag-NPs, on which it is allowed to adsorb, before salt ions are introduced, causing the Ag-NPs to aggregate, and so creating species with strong SERS signal. The device allows partial separation via diffusion of the analyte from the complex mixture. Also, the reproducible salt-induced NP aggregation decouples the aggregation reaction (necessary for strong SERS) from the analyte concentration or charge. This method enables the creation of a region where detection of the analyte of interest via SERS is optimal, and dramatically extends the classes of molecules and quality of signals that can be measured using SERS, compared to bulk solution methods. The spatial distribution of the SERS signals was used to map the degree of nanoparticle aggregation and species diffusion in the channel, which, together with numerical simulations, was used to describe the kinetics of the colloid aggregation reaction, and to determine the optimal location in the channel for SERS interrogation.

The evaporation rate and internal convective flows of a sessile droplet with a pinned contact line were formulated and investigated numerically. We developed and analyzed a unified numerical model that includes the effects of temperature, droplet volume, and contact angle on evaporation rate and internal flows. The temperature gradient on the air/liquid interface causes an internal flow due to Marangoni stress, which provides good convective mixing within the droplet, depending upon Marangoni number. As the droplet volume decreases, the thermal gradient becomes smaller and the Marangoni flow becomes negligible. Simultaneously, as the droplet height decreases, evaporation-induced flow creates a large jet-like flow radially toward the contact line. For a droplet containing suspended particles, this jet-like convective flow carries particles toward the contact line and deposits them on the surface, forming the so-called "coffee ring stain". In addition, we reported a simple polynomial correlation for dimensionless evaporation time as a function of initial contact angle of the pinned sessile droplet which agrees well with the previous experimental and numerical results.

The aggregation kinetics of silver nanoparticles in sessile droplets were investigated both experimentally and through numerical simulations as a function of temperature gradient and evaporation rate, in order to determine the hydrodynamic and aggregation parameters that lead to optimal surface-enhanced Raman spectroscopic (SERS) detection. Thermal gradients promote effective stirring within the droplet. The aggregation reaction ceases when the solvent evaporates forming a circular stain consisting of a high concentration of silver nanoparticle aggregates, which can be interrogated by SERS leading to analyte detection and identification. We introduce the aggregation parameter, Γa ≡ τ(evap)/τ(a), which is the ratio of the evaporation to the aggregation time scales. For a well-stirred droplet, the optimal condition for SERS detection was found to be Γ(a,opt) = kc(NP)τ(evap) ≈ 0.3, which is a product of the dimerization rate constant (k), the concentration of nanoparticles (cNP), and the droplet evaporation time (τ(evap)). Near maximal signal (over 50% of maximum value) is observed over a wide range of aggregation parameters 0.05 < Γa < 1.25, which also defines the time window during which trace analytes can be easily measured. The results of the simulation were in very good agreement with experimentally acquired SERS spectra using gas-phase 1,4-benzenedithiol as a model analyte.

The increasing power dissipation and decreasing dimensions of microelectronic devices have emphasized the demand for extremely efficient compact cooling technology. Microchannel heat sinks are of particular interest due to high rates of heat transfer, which have become known as one of the effective cooling technologies. In the present work, numerical simulation of incompressible flow in two dimensional microchannels by implementing nonuniform electrokinetic forces is performed using finite volume method. The velocity field and the heat transfer rate are influenced by the wall potential variations through the microchannel. Nondimensional parameters of heat transfer and fluid flows, Debay Huckel length, microchannel size and wall charge potential distribution, have major roles in this investigation. For fixed values of Reynolds number and microchannel size, the patterns of wall potentials are optimized to enhance the heat transfer rate. Velocity profiles are computed and temperature distribution and Nusselt number are obtained for uniform wall heat flux boundary condition. Average and local Nusselt numbers are illustrated for different wall potential configurations and Reynolds number. Velocity vectors and pressure drop are presented for different zeta potentials and Reynolds numbers. Finally, results of nonuniform electrical force are compared to uniform ones.

Next Generation Sequencing (NGS) technologies have revolutionized basic biological and clinical research, especially in oncology. NGS cancer assays are used to determine cancer predisposition, identify tumor mutations, monitor treatment response and develop personalized therapies. Here, GenapSys presents a scalable, low cost, and high accuracy sequencing platform based on electrical impedance detection. We demonstrate that a single run with a 16M sensor chip generates up to 2 Gb of data, with greater than 99% raw accuracy and an average read length of about 150 bp. We highlight its applications for oncology research, using diverse cancer panels on reference and clinical samples. We tested hybrid-capture and multiplex PCR-based cancer panels on a range of DNA sources, including oncology reference standards derived from cell line DNA, cfDNA standards, as well as clinical samples: FFPE, fresh frozen tumor tissue, and blood. For hybrid-capture libraries, we used the IDT xGen Pan Cancer 1.5 and Exome Research panels. We detected low frequency mutations in the range of 1%-24.5% across multiple reference standards with the cancer panel, and observed high correlation in allele frequency with expected values (R2 &gt; 0.99). Similar results were obtained with an amplicon panel, the Ion AmpliSeq Cancer Hotspot Panel v2. Whole exome sequencing and pan cancer sequencing of clinical FFPE, fresh frozen and blood samples showed high concordance (F1-score &gt; 95%) of SNV mutation calling with commonly used NGS technology. Thus, we demonstrate that the GenapSys Sequencing Platform is an accurate, scalable, and low cost solution for oncology research on a wide range of sample types and NGS assays. Citation Format: Saurabh Paliwal, Mohammad Fallahi, Ali Nabi, Tyson A. Clark, Bin Dong, Srijeeta Bagchi, Maryam Jouzi, Hannah Ritchie, Lydia Bonar, Anthony Thomas, Narin Tangprasertchai, Meysam R. Barmi, Xavier Gomes, Subra Sankar, Hesaam Esfandyarpour. Oncology research applications on an electrical impedance based, high accuracy sequencing platform [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-315.