Fluorescence Polarization Anisotropy in Microdroplets.
The journal of physical chemistry letters
Chemical reactions can be greatly accelerated in microdroplets, but the factors that lead to acceleration are still being elucidated. Using rhodamine 6G (R6G) as a model compound, we studied the density distribution and fluorescence polarization anisotropy of this dye in water-in-oil microdroplets. We found the density of R6G is higher on the surface of the microdroplets, and the ratio of the surface density to that of the center grows with increasing microdroplet radius or with decreasing R6G concentration. The measured fluorescence polarization anisotropy at the surface is almost the same for droplets of different sizes but becomes larger when the concentration is lowered. We also performed three-dimensional simulations by treating R6G+ and its associated anion as a dipole of fixed length and magnitude. The simulation results match quite well the experimental measurements, showing that the density distribution and fluorescence polarization anisotropy can be largely explained by a simple electrostatic model.
View details for DOI 10.1021/acs.jpclett.8b01129
View details for PubMedID 29763551
Optimizing Chemical Reactions with Deep Reinforcement Learning
ACS CENTRAL SCIENCE
2017; 3 (12): 1337–44
Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient exploration strategy by drawing the reaction conditions from certain probability distributions, which resulted in an improvement on regret from 0.062 to 0.039 compared with a deterministic policy. Combining the efficient exploration policy with accelerated microdroplet reactions, optimal reaction conditions were determined in 30 min for the four reactions considered, and a better understanding of the factors that control microdroplet reactions was reached. Moreover, our model showed a better performance after training on reactions with similar or even dissimilar underlying mechanisms, which demonstrates its learning ability.
View details for DOI 10.1021/acscentsci.7b00492
View details for Web of Science ID 000418706200016
View details for PubMedID 29296675
View details for PubMedCentralID PMC5746857
- Upgrading Asphaltenes by Oil Droplets Striking a Charged TiO2-Immobilized Paper Surface ENERGY & FUELS 2017; 31 (11): 12685–90
Personal Information from Latent Fingerprints Using Desorption Electrospray Ionization Mass Spectrometry and Machine Learning
2017; 89 (2): 1369-1372
Desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) was applied to latent fingerprints to obtain not only spatial patterns but also chemical maps. Samples with similar lipid compositions as those of the fingerprints were collected by swiping a glass slide across the forehead of consenting adults. A machine learning model called gradient boosting tree ensemble (GDBT) was applied to the samples that allowed us to distinguish between different genders, ethnicities, and ages (within 10 years). The results from 194 samples showed accuracies of 89.2%, 82.4%, and 84.3%, respectively. Specific chemical species that were determined by the feature selection of GDBT were identified by tandem mass spectrometry. As a proof-of-concept, the machine learning model trained on the sample data was applied to overlaid latent fingerprints from different individuals, giving accurate gender and ethnicity information from those fingerprints. The results suggest that DESI-MSI imaging of fingerprints with GDBT analysis might offer a significant advance in forensic science.
View details for DOI 10.1021/acs.analchem.6b04498
View details for Web of Science ID 000392458100047
View details for PubMedID 28194988
Nanotip Ambient Ionization Mass Spectrometry
2016; 88 (10): 5542-5548
A method called nanotip ambient ionization mass spectrometry (NAIMS) is described, which applies high voltage between a tungsten nanotip and a metal plate to generate a plasma in which ionized analytes on the surface of the metal plate are directed to the inlet and analyzed by a mass spectrometer. The dependence of signal intensity is investigated as a function of the tip-to-plate distance, the tip size, the voltage applied at the tip, and the current. These parameters are separately optimized to achieve sensitivity or high spatial resolution. A partially observable Markov decision process is used to achieve a stabilized plasma as well as high ionization efficiency. As a proof of concept, the NAIMS technique has been applied to phenanthrene and caffeine samples for which the limits of detection were determined to be 0.14 fmol for phenanthrene and 4 amol for caffeine and to a printed caffeine pattern for which a spatial resolution of 8 ± 2 μm, and the best resolution of 5 μm, was demonstrated. The limitations of NAIMS are also discussed.
View details for DOI 10.1021/acs.analchem.6b01212
View details for Web of Science ID 000376223500071
View details for PubMedID 27087600
A dual amplification strategy for DNA detection combining bio-barcode assay and metal-enhanced fluorescence modality
2014; 50 (87): 13373–76
Silver-enhanced fluorescence was coupled with a bio-barcode assay to facilitate a dual amplification assay to demonstrate a non-enzymatic approach for simple and sensitive detection of DNA. In the assay design, magnetic nanoparticles seeded with silver nanoparticles were modified with the capture DNA, and silver nanoparticles were modified with the binding of ssDNA and the fluorescently labeled barcode dsDNA. Upon introduction of the target DNA, a sandwich structure was formed because of the hybridization reaction. By simple magnetic separation, silver-enhanced fluorescence of barcode DNAs could be readily measured without the need of a further step to liberate barcode DNAs from silver nanoparticles, endowing the method with simplicity and high sensitivity with a detection limit of 1 pM.
View details for DOI 10.1039/c4cc05554c
View details for Web of Science ID 000343965700046
View details for PubMedID 25233044
A distance-dependent metal-enhanced fluorescence sensing platform based on molecular beacon design
BIOSENSORS & BIOELECTRONICS
2014; 52: 367–73
A new metal-enhanced fluorescence (MEF) based platform was developed on the basis of distance-dependent fluorescence quenching-enhancement effect, which combined the easiness of Ag-thiol chemistry with the MEF property of noble-metal structures as well as the molecular beacon design. For the given sized AgNPs, the fluorescence enhancement factor was found to increase with a d(6) dependency in agreement with fluorescence resonance energy transfer mechanism at shorter distance and decrease with a d(-3) dependency in agreement with plasmonic enhancement mechanism at longer distance between the fluorophore and the AgNP surface. As a proof of concept, the platform was demonstrated by a sensitive detection of mercuric ions, using thymine-containing molecular beacon to tune silver nanoparticle (AgNP)-enhanced fluorescence. Mercuric ions were detected via formation of a thymine-mercuric-thymine structure to open the hairpin, facilitating fluorescence recovery and AgNP enhancement to yield a limit of detection of 1 nM, which is well below the U.S. Environmental Protection Agency regulation of the Maximum Contaminant Level Goal (10nM) in drinking water. Since the AgNP functioned as not only a quencher to reduce the reagent blank signal but also an enhancement substrate to increase fluorescence of the open hairpin when target mercuric ions were present, the quenching-enhancement strategy can greatly improve the detection sensitivity and can in principle be a universal approach for various targets when combined with molecular beacon design.
View details for DOI 10.1016/j.bios.2013.09.013
View details for Web of Science ID 000328095400056
View details for PubMedID 24080216