Sub-volt high-speed silicon MOSCAP microring modulator driven by high-mobility conductive oxide.

Silicon microring modulator plays a critical role in energy-efficient optical interconnect and optical computing owing to its ultra-compact footprint and capability for on-chip wavelength-division multiplexing. However, existing silicon microring modulators usually require more than 2 V of driving voltage (Vpp), which is limited by both material properties and device structures. Here, we present a metal-oxide-semiconductor capacitor microring modulator through heterogeneous integration between silicon photonics and titanium-doped indium oxide, which is a high-mobility transparent conductive oxide (TCO) with a strong plasma dispersion effect. The device is co-fabricated by Intel's photonics fab and our in-house TCO patterning processes, which exhibits a high modulation efficiency of 117 pm/V and consequently can be driven by a very low Vpp of 0.8 V. At a 11 GHz modulation bandwidth where the modulator is limited by the RC bandwidth, we obtained 25 Gb/s clear eye diagrams with energy efficiency of 53 fJ/bit.

Dynamic indoor free-space optical communication enabled by beam steering and beam shaping.

Indoor free-space optical communication (FSO) provides orders of magnitude larger usable bandwidth compared to radio-frequency links but suffers from an intrinsic trade-off between areal coverage and received power. In this paper, we report a dynamic indoor FSO system enabled by a line-of-sight optical link featuring advanced beam control capabilities. The optical link herein utilizes a passive target acquisition scheme by combining a beam steering and beam shaping transmitter with a receiver adorned with a ring-shaped retroreflector. When controlled by an efficient beam scanning algorithm, the transmitter is capable of locating the receiver with millimeter-scale accuracy over a distance of 3 m with a full viewing angle of ±11.25∘ in the vertical direction and ±18.75∘ in the horizontal direction within 1.162±0.005s, regardless of the receiver's positions. We also demonstrate 1 Gbit/s data rate with bit error rates below 4×10-7 using an 850 nm laser diode with only 2 mW of output power.

Limit-Defying µ-Total Analysis System: Achieving Part-Per-Quadrillion Sensitivity on a Hierarchical Optofluidic SERS Sensor.

Optofluidic sensors have accelerated the growth of smart sensor platforms with improved sensitivity, reliability, and innovation. In this article, we report the integration of a surface-enhanced Raman scattering (SERS) material consisting of silver nanoparticle-decorated diatomaceous earth (AgNPs-DE) with a flow-through microfluidic device, building up a hierarchical structured micro-total analysis system (µ-TAS) capable of achieving part-per-quadrillion (ppq)-level sensitivity. By the synergic integration of millimeter-scale microfluidic devices and porous laboratory filter paper with a micrometer-sized crosslinked cellulosic network that carries SERS-active AgNPs-DE, which possesses submicron to nanometer regimes of photonic crystals and plasmonic nanostructures, we achieved enhanced mass-transfer efficiency and unprecedented detection sensitivity. In our experiment, fentanyl as the testing analyte at different concentrations was measured using a portable Raman spectrometer. The limit of detection (LOD) was estimated to be 10 ppq from a small detection volume of 10 mL with an ultrafast time of sensing (TOS) of 3 min. To attain comparable signals, the traditional soaking method took more than 90 min to detect 10 part-per-trillion fentanyl from a 10 mL sample. Compared with existing SERS sensing results of fentanyl, the limit-defying µ-TAS reduced the LOD-TOS product by almost 4 orders of magnitude, which represents a new stage of ultrafast sensing of extremely low concentration analytes.

Rapid, convenient, and ultrasensitive point-of-care sensing of histamine from fish: A Portable chromatographic platform based on derivatization reaction.

Food poisoning caused by histamine ingestion is one of the prevalent allergies associated with fish consumption in the world. Reliable detection of histamine from fish by a portable platform was of urgent importance to food safety. A portable technology for on-site monitoring of histamine in tuna was established through combined azo-derivatized thin-layer chromatography (TLC) with surface-enhanced Raman scattering (SERS) spectroscopy. The real tuna meat sample was directly applied onto the portable sensor for the separation of histamine and azo-derivatizing of histamine was reacted on the TLC plate. The colorless histamine was visualized by azo-derivatization after spraying Pauly reagent onto the diatomite TLC plate. The molecule information and concentration of the histamine was measured and calculated by SERS spectra. Diatomite TLC plate was capable of separating histamine with 1.32 × 10-7 M of Au colloid for the SERS enhancement. Accordingly, the limit of detection of histamine from mixture sample could achieve 2.8 × 10-4 ppm. These results indicated that the portable azo-derivatized TLC-SERS sensor not only visualizes the histamine but also improves the intensity of the Raman spectra. The azo-derivatized TLC-SERS sensor could be applied for rapid, convenient, and ultrasensitive point-of-care sensing of histamine in fish.

On-chip wavelength division multiplexing filters using extremely efficient gate-driven silicon microring resonator array.

Silicon microring resonators (Si-MRRs) play essential roles in on-chip wavelength division multiplexing (WDM) systems due to their ultra-compact size and low energy consumption. However, the resonant wavelength of Si-MRRs is very sensitive to temperature fluctuations and fabrication process variation. Typically, each Si-MRR in the WDM system requires precise wavelength control by free carrier injection using PIN diodes or thermal heaters that consume high power. This work experimentally demonstrates gate-tuning on-chip WDM filters for the first time with large wavelength coverage for the entire channel spacing using a Si-MRR array driven by high mobility titanium-doped indium oxide (ITiO) gates. The integrated Si-MRRs achieve unprecedented wavelength tunability up to 589 pm/V, or VπL of 0.050 V cm with a high-quality factor of 5200. The on-chip WDM filters, which consist of four cascaded ITiO-driven Si-MRRs, can be continuously tuned across the 1543-1548 nm wavelength range by gate biases with near-zero power consumption.

Quantitative Sensing of Domoic Acid from Shellfish Using Biological Photonic Crystal Enhanced SERS Substrates.

Frequent monitoring of sea food, especially shellfish samples, for the presence of biotoxins serves not only as a valuable strategy to mitigate adulteration associated health risks, but could also be used to develop predictive models to understand algal explosion and toxin trends. Periodic toxin assessment is often restricted due to poor sensitivity, multifarious cleaning/extraction protocols and high operational costs of conventional detection methods. Through this work, a simplistic approach to quantitatively assess the presence of a representative marine neurotoxin, Domoic acid (DA), from spiked water and crab meat samples is presented. DA sensing was performed based on surface-enhanced Raman scattering (SERS) using silver nanoparticle enriched diatomaceous earth­a biological photonic crystal material in nature. Distinctive optical features of the quasi-ordered pore patterns in diatom skeleton with sporadic yet uniform functionalization of silver nanoparticles act as excellent SERS substrates with improved DA signals. Different concentrations of DA were tested on the substrates with the lowest detectable concentration being 1 ppm that falls well below the regulatory DA levels in seafood (>20 ppm). All the measurements were rapid and were performed within a measurement time of 1 min. Utilizing the measurement results, a standard calibration curve between SERS signal intensity and DA concentration was developed. The calibration curve was later utilized to predict the DA concentration from spiked Dungeness crab meat samples. SERS based quantitative assessment was further complemented with principal component analysis and partial least square regression studies. The tested methodology aims to bring forth a sensitive yet simple, economical and an extraction free routine to assess biotoxin presence in sea food samples onsite.

Ultra-compact hybrid silicon:chalcogenide waveguide temperature sensor.

We demonstrate a real-time, reusable, and reversible integrated optical sensor for temperature monitoring within harsh environments. The sensor architecture combines the phase change property of chalcogenide glasses (ChG) with the high-density integration advantages of high index silicon waveguides. To demonstrate sensor feasibility, ChG composition Ge40S60, which is characterized by a sharp phase transition from amorphous to crystalline phase around 415 °C, is deposited over a 50 µm section of a single mode optical waveguide. The phase transition changes the behavior of Ge40S60 from a low loss to high loss material, thus significantly affecting the hybrid waveguide loss around the phase transition temperature. A transmission power drop of over 40dB in the crystalline phase compared to the amorphous phase is experimentally measured. Moreover, we recover the amorphous phase through the application of an electrical pulse, thus showing the reversible nature of our compact temperature sensor. Through integrating multiple compositions of ChG with well-defined phases transition temperatures over a silicon waveguide array, it is possible to determine, in real-time, the temperature evolution within a harsh environment, such as within a nuclear reactor cladding.

Near infrared spectroscopy quantification based on Bi-LSTM and transfer learning for new scenarios.

This study proposed a deep transfer learning methodology based on an improved Bi-directional Long Short-Term Memory (Bi-LSTM) network for the first time to address the near infrared spectroscopy (NIR) model transfer issue between samples. We tested its effectiveness on two datasets of manure and polyglutamic acid (γ-PGA) solution, respectively. First, the optimal primary Bi-LSTM networks for cattle manure and the first batch of γ-PGA were developed by ablation experiments and both proved to outperform one-dimensional convolutional neural network (1D-CNN), Partial Least Square (PLS) and Extreme Learning Machine (ELM) models. Then, two types of transfer learning approaches were carried out to determine model transferability to non-homologous samples. For poultry manure and the second batch of γ-PGA, the obtained predicting results verified that the second approach of fine-tuning Bi-LSTM layers and re-training FC layers transcended the first approach of fixing Bi-LSTM layers and only re-training FC layers by reducing the RMSEPtarget of 23.4275% and 50.7343%, respectively. Finally, comparisons with fine-tuning 1D-CNN and other traditional model transfer methods further identified the superiority of the proposed methodology with exceeding accuracy and smaller variation, which decreased RMSEPtarget of poultry manure and the second batch of γ-PGA of 7.2832% and 48.1256%, 67.1117% and 80.6924% when compared to that acquired by fine-tuning 1D-CNN, Tradaboost-ELM and CCA-PLS which were the best of five traditional methods, respectively. The study demonstrates the potential of the Fine-tuning-Bi-LSTM enabled NIR technology to be used as a simple, cost effective and reliable detection tool for a wide range of applications under various new scenarios.

Ultra-Sensitive, Rapid and On-Site Sensing Harmful Ingredients Used in Aquaculture with Magnetic Fluid SERS.

The integration of surface-enhanced Raman scattering (SERS) spectroscopy with magnetic fluid provides significant utility in point-of-care (POC) testing applications. Bifunctional magnetic-plasmonic composites have been widely employed as SERS substrates. In this study, a simple and cost-effective approach was developed to synthesize magnetic-plasmonic SERS substrates by decorating silver nanoparticles onto magnetic Fe3O4 nanoparticles (AgMNPs), which function both as SERS-active substrates and magnetic fluid particles. The strong magnetic responsivity from AgMNPs can isolate, concentrate, and detect target analytes from the irregular surface of fish skin rapidly. We fabricate a microfluid chip with three sample reservoirs that confine AgMNPs into ever smaller volumes under an applied magnetic field, which enhances the SERS signal and improves the detection limit by two orders of magnitude. The magnetic fluid POC sensor successfully detected malachite green from fish with excellent selectivity and high sensitivity down to the picomolar level. This work achieves a label-free, non-destructive optical sensing approach with promising potential for the detection of various harmful ingredients in food or the environment.

Multiplex Sensing of Complex Mixtures by Machine Vision Analysis of TLC-SERS Images.

Thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) has demonstrated tremendous potentials as a new analytical chemistry tool to detect a wide range of substances from real-world samples. However, it still faces significant challenges of multiplex sensing from complex mixtures due to the imperfect separation by TLC and the resulting interference of SERS detection. In this article, we propose a multiplex sensing method of complex mixtures by machine vision analysis of the scanning image of the TLC-SERS results. Briefly, various pure substances in solution and the complex mixture solution are separated by TLC followed by one-dimensional SERS scanning of the entire TLC plate, which generates TLC-SERS images of all target substances along the chromatography path. After that, a machine vision method is employed to extract the template images from the TLC-SERS images of pure substance solutions. Finally, we apply a feature point matching strategy based on the Winner-take-all principle, which matches the template image of each pure substance with the mixture image to confirm the existence and derive the position of each target substance in the TLC plate, respectively. Our experimental results based on the mixture solution of five different substances show that the proposed machine vision analysis is highly selective, sensitive and does not require artificial analysis of the SERS spectra. Therefore, we envision that the proposed machine vision analysis of the TLC-SERS imaging is an objective, accurate, and efficient method for multiplex sensing of trace level of target substances from complex mixtures.

Plasmonic color filter array based visible light spectroscopy.

Compared with traditional Fabry-Perot optical filters, plasmonic color filters could greatly remedy the complexity and reduce the cost of manufacturing. In this paper we present end-to-end demonstration of visible light spectroscopy based on highly selective plasmonic color filter array based on resonant grating structure. The spectra of 6 assorted samples were measured using an array of 20 narrowband color filters and detected signals were used to reconstruct original spectra by using new unmixing algorithm and by solving least squares problem with smoothing regularization. The original spectra were reconstructed with less than 0.137 root mean squared error. This works shows promise towards fully integrating plasmonic color filter array in imagers used in hyperspectral cameras.

Sub-Part-Per-Billion Level Sensing of Fentanyl Residues from Wastewater Using Portable Surface-Enhanced Raman Scattering Sensing.

Detection of illicit drug residues from wastewater provides a new route toward community-level assessment of drug abuse that is critical to public health. However, traditional chemistry analytical tools such as high-performance liquid chromatography in tandem with mass spectrometry (HPLC-MS) cannot meet the large-scale testing requirement in terms of cost, promptness, and convenience of use. In this article, we demonstrated ultra-sensitive and portable surface-enhanced Raman scattering sensing (SERS) of fentanyl, a synthetic opioid, from sewage water and achieved quantitative analysis through principal component analysis and partial least-squares regression. The SERS substrates adopted in this application were synthesized by in situ growth of silver nanoparticles on diatomaceous earth films, which show ultra-high sensitivity down to 10 parts per trillion in artificially contaminated tap water in the lab using a commercial portable Raman spectrometer. Based on training data from artificially contaminated tap water, we predicted the fentanyl concentration in the sewage water from a wastewater treatment plant to be 0.8 parts per billion (ppb). As a comparison, the HPLC-MS confirmed the fentanyl concentration was below 1 ppb but failed to provide a specific value of the concentration since the concentration was too low. In addition, we further proved the validity of our SERS sensing technique by comparing SERS results from multiple sewage water treatment plants, and the results are consistent with the public health data from our local health authority. Such SERS sensing technique with ultra-high sensitivity down to sub-ppb level proved its feasibility for point-of-care detection of illicit drugs from sewage water, which is crucial to assess public health.

Fabrication and Application of SERS-Active Cellulose Fibers Regenerated from Waste Resource.

The flexible SERS substrate were prepared base on regenerated cellulose fibers, in which the Au nanoparticles were controllably assembled on fiber through electrostatic interaction. The cellulose fiber was regenerated from waste paper through the dry-jet wet spinning method, an eco-friendly and convenient approach by using ionic liquid. The Au NPs could be controllably distributed on the surface of fiber by adjusting the conditions during the process of assembling. Finite-difference time-domain theoretical simulations verified the intense local electromagnetic fields of plasmonic composites. The flexible SERS fibers show excellent SERS sensitivity and adsorption capability. A typical Raman probe molecule, 4-Mercaptobenzoicacid (4-MBA), was used to verify the SERS cellulose fibers, the sensitivity could achieve to 10-9 M. The flexible SERS fibers were successfully used for identifying dimetridazole (DMZ) from aqueous solution. Furthermore, the flexible SERS fibers were used for detecting DMZ from the surface of fish by simply swabbing process. It is clear that the fabricated plasmonic composite can be applied for the identifying toxins and chemicals.

Simultaneous colorimetric and surface-enhanced Raman scattering detection of melamine from milk.

We present a dual-mode readout sensing mechanism that can effectively distinguish true and false-positive signals of melamine in milk by combining colorimetric analysis and surface-enhanced Raman scattering (SERS) spectroscopy. The colorimetry analysis takes advantage of color change of plasmonic nanoparticles upon the presence of melamine. We discovered that Ag colloids with 20 nm diameter was suitable for both colorimetric and SERS methods. However, the colorimetric method may present false-positive signals with the presence of interfering compounds. SERS spectroscopy can overcome this limitation and directly obtain signature spectra from the same plasmonic NPs used for the colorimetric assay without any modification. Melamine/s-triazine can be reliably differentiated by probing the SERS spectra based on surface-selection rules. The limit of detection of sensing melamine from milk by this method could reached to 0.05 ppm. Therefore, the combination of colorimetric and SERS method not only allows for rapid preliminary screening of melamine by naked eyes, but also greatly reduces false-positive signals by surface selection rules in SERS.

Plasmonic cellulose textile fiber from waste paper for BPA sensing by SERS.

Flexible plasmonic Surface-enhanced Raman scattering (SERS) substrates were fabricated using cellulose textile fibers, in which the textile fibers were recycled from waste paper in an eco-friendly way. The Glycidyltrimethylammonium chloride (GTAC) with positive charges was grafted onto the surface of the cellulose textile fibers through cationization. Plasmonic silver nanoparticles (Ag NPs) with negative charges were decorated onto the cellulose textile fibers via electrostatic interactions. After cationization, the variation range of the diameter of the cellulose textile fibers was significantly increased because part of the cellulose was dissolved under alkaline condition, leading to more 'hot spots' for SERS during the shrinking process. The cellulose textile fiber-Ag NPs nanocomposite was employed for monitoring bisphenol A (BPA) in water and soft drink by SERS and the sensitivity of BPA detection achieved 50 ppb. The recovery values of BPA in soda water samples were from 96% to 105%. These results illustrate that the cellulose textile fiber-Ag NPs nanocomposite can be used as flexible, high sensitivity SERS substrates for detecting harmful ingredients in food or environment.

Quantitative TLC-SERS detection of histamine in seafood with support vector machine analysis.

Scombroid fish poisoning caused by histamine intoxication is one of the most prevalent allergies associated with seafood consumption in the United States. Typical symptoms range from mild itching up to fatal cardiovascular collapse seen in anaphylaxis. In this paper, we demonstrate rapid, sensitive, and quantitative detection of histamine in both artificially spoiled tuna solution and real spoiled tuna samples using thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) sensing methods, enabled by machine learning analysis based on support vector regression (SVR) after feature extraction with principal component analysis (PCA). The TLC plates used herein, which were made from commercial food-grade diatomaceous earth, served simultaneously as the stationary phase to separate histamine from the blended tuna meat and as ultra-sensitive SERS substrates to enhance the detection limit. Using a simple drop cast method to dispense gold colloidal nanoparticles onto the diatomaceous earth plate, we were able to directly detect histamine concentration in artificially spoiled tuna solution down to 10 ppm. Based on the TLC-SERS spectral data of real tuna samples spoiled at room temperature for 0 to 48 hours, we used the PCA-SVR quantitative model to achieve superior predictive performance exceling traditional partial least squares regression (PLSR) method. This work proves that diatomaceous earth based TLC-SERS technique combined with machine-learning analysis is a cost-effective, reliable, and accurate approach for on-site detection and quantification of seafood allergen to enhance food safety.

Photonic Crystal-Enhanced Fluorescence Imaging Immunoassay for Cardiovascular Disease Biomarker Screening with Machine Learning Analysis.

When myocardial walls experience stress due to cardiovascular diseases, like heart failure, hormone N-terminal pro-B-type natriuretic peptide (NT-proBNP) is secreted into the blood. Early detection of NT-proBNP can assist diagnosis of heart failure and enable early medical intervention. A simple, cost-effective detection technique such as the widely used fluorescence imaging immunoassay is yet to be developed to detect clinically relevant levels of NT-proBNP. In this work, we demonstrate photonic crystal-enhanced fluorescence imaging immunoassay using diatom biosilica, which is capable of detecting low levels of NT-proBNP in solution with the concentration range of 0~100 pg/mL. By analyzing the fluorescence images in the spatial and spatial frequency domain with principle component analysis (PCA) and partial least squares regression (PLSR) algorithms, we create a predictive model that achieves great linearity with a validation R2 value of 0.86 and a predictive root mean square error of 14.47, allowing for good analyte quantification. To demonstrate the potential of the fluorescence immunoassay biosensor for clinical usage, we conducted qualitative screening of high and low concentrations of NT-proBNP in human plasma. A more advanced machine learning algorithm, the support vector machine classification, was paired with the PCA and trained by 160 fluorescence images. In the 40 testing images, we achieved excellent specificity of 93%, as well as decent accuracy and sensitivity of 78% and 65% respectively. Therefore, the photonic crystal-enhanced fluorescence imaging immunoassay reported in this article is feasible to screen clinically relevant levels of NT-proBNP in body fluid and evaluate the risk of heart failure.

Tetrahydrocannabinol Sensing in Complex Biofluid with Portable Raman Spectrometer Using Diatomaceous SERS Substrates.

Using thin-layer chromatography in tandem with surface-enhanced Raman spectroscopy (TLC-SERS) and tetrahydrocannabinol (THC) sensing in complex biological fluids is successfully conducted with a portable Raman spectrometer. Both THC and THC metabolites are detected from the biofluid of marijuana-users as biomarkers for identifying cannabis exposure. In this article, ultra-sensitive SERS substrates based on diatomaceous earth integrated with gold nanoparticles (Au NPs) were employed to detect trace levels of cannabis biomarkers in saliva. Strong characteristic THC and THC metabolite SERS peaks at 1601 and 1681 cm-1 were obtained despite the moderate interference of biological molecules native to saliva. Urine samples were also analyzed, but they required TLC separation of THC from the urine sample to eliminate the strong influence of urea and other organic molecules. TLC separation of THC from the urine was performed by porous microfluidic channel devices using diatomaceous earth as the stationary phase. The experimental results showed clear separation between urea and THC, and strong THC SERS characteristic peaks. Principal component analysis (PCA) was used to analyze the SERS spectra collected from various THC samples. The spectra in the principal component space were well clustered for each sample type and share very similar scores in the main principal component (PC1), which can serve as the benchmark for THC sensing from complex SERS spectra. Therefore, we proved that portable Raman spectrometers can enable an on-site sensing capability using diatomaceous SERS substrates to detect THC in real biological solutions. This portable THC sensing technology will play pivotal roles in forensic analysis, medical diagnosis, and public health.

Trace Detection of Tetrahydrocannabinol in Body Fluid via Surface-Enhanced Raman Scattering and Principal Component Analysis.

Tetrahydrocannabinol (THC) is the main active component in marijuana and the rapid detection of THC in human body fluid plays a critical role in forensic analysis and public health. Surface-enhanced Raman scattering (SERS) sensing has been increasingly used to detect illicit drugs; however, only limited SERS sensing results of THC in methanol solution have been reported, while its presence in body fluids, such as saliva or plasma, has yet to be investigated. In this article, we demonstrate the trace detection of THC in human plasma and saliva solution using a SERS-active substrate formed by in situ growth of silver nanoparticles (Ag NPs) on diatom frustules. THC at extremely low concentration of 1 pM in plasma and purified saliva solutions were adequately distinguished with good reproducibility. The SERS peak at 1603 cm-1 with standard deviation of 3.4 cm-1 was used for the evaluation of THC concentration in a methanol solution. Our SERS measurement also shows that this signature peak experiences a noticeable wavenumber shift and a slightly wider variation in the plasma and saliva solution. Additionally, we observed that THC in plasma or saliva samples produces a strong SERS peak at 1621 cm-1 due to the stretching mode of O-C═O, which is related to the metabolic change of THC structures in body fluid. To conduct a quantitative analysis, principal component analysis (PCA) was applied to analyze the SERS spectra of 1 pM THC in methanol solution, plasma, and purified saliva samples. The maximum variability of the first three principal components was achieved at 71%, which clearly denotes the impact of different biological background signals. Similarly, the SERS spectra of THC in raw saliva solution under various metabolic times were studied using PCA and 98% of the variability is accounted for in the first three principal components. The clear separation of samples measured at different THC resident times can provide time-dependent information on the THC metabolic process in body fluids. A linear regression model was used to estimate the metabolic rate of THC in raw saliva and the predicted metabolic time in the testing data set matched well with the training data set. In summary, the hybrid plasmonic-biosilica SERS substrate can achieve ultrasensitive, near-quantitative detection of trace levels of THC in complex body fluids, which can potentially transform forensic sensing techniques to detect marijuana abuse.

Highly-porous diatom biosilica stationary phase for thin-layer chromatography.

This study showed that a nanostructured, highly-porous stationary phase composed of randomly-deposited biosilica frustules isolated from living cells of diatom Pinnularia sp. significantly improved the conventional thin-layer chromatography (TLC) based separation of the triphenylmethane dyes malachite green and fast green relative to silica gel by two mobile phases (9:1:1 v/v 1-butanol:ethanol:water, 5:1:2 v/v 1-butanol:acetic acid:water). Although both stationary phases were composed of amorphous silica rich in silanol groups with particle size of 10-12 µm, diatom biosilica frustules were highly porous, hollow shells with surface structure dominated by 200 nm pore arrays. Diatom biosilica significantly improved the mobility of both malachite green and fast green, enabling the resolution of these analytes. The diatom biosilica layer had a high void fraction of 96% but reduced the flow velocity and permeability constant by a factor of two relative to silica gel. TLC performance was enhanced, as evidenced by ten-fold reduction in theoretical plate height for both analytes using the 1-butanol:acetic acid:water mobile phase, and an increased difference in retention time between malachite green and fast green (ΔRf = 0.26) using the 1-butanol:ethanol:water mobile phase. Analysis of plate height vs. solvent front position by the modified van Deemter equation suggested that dispersive mass transfer was reduced, leading to improved analyte resolution, and that surface of the frustule decreased boundary layer resistance, leading to increased analyte flux. Overall, the basis for improved chromatographic performance is believed to be the unique nano- and microstructure of the diatom biosilica frustule.