A novel ultrafast reflective grating-imaging technique has been developed to measure ambipolar carrier diffusion in GaAs/AlAs quantum wells and bulk GaAs. By integrating a transmission grating and an imaging system into the traditional pump–probe setup, this technique can acquire carrier diffusion properties conveniently and accurately. The fitted results of the diffusion coefficient and diffusion length in bulk GaAs agree well with the literature values obtained by other techniques. The diffusion coefficient and diffusion length of GaAs/AlAs quantum wells are found to increase with the well layer thickness, which suggests that interface roughness scattering dominates carrier diffusion in GaAs/AlAs quantum wells. With the advantages of simple operation, sensitive detection, rapid and nondestructive measurement, and extensive applicability, the ultrafast reflective grating-imaging technique has great potential in experimental study of carrier diffusion in various materials.
Brain function can be best studied by simultaneous measurements and modulation of the multifaceted signaling at the cellular scale. Extensive efforts have been made to develop multifunctional neural probes, typically involving highly specialized fabrication processes. Here, we report a novel multifunctional neural probe platform realized by applying ultra-thin nanoelectronic coating (NEC) on the surfaces of conventional microscale devices such as optical fibers and micropipettes. We fabricated the NECs by planar photolithography techniques using a substrate-less and multi-layer design, which host arrays of individually addressed electrodes with an overall thickness below 1 µm. Guided by an analytic model and taking advantage of the surface tension, we precisely aligned and coated the NEC devices on the surfaces of these conventional micro-probes, and enabled electrical recording capabilities on par with the state-of-the-art neural electrodes. We further demonstrated optogenetic stimulation and controlled drug infusion with simultaneous, spatially resolved neural recording in a rodent model. This study provides a low-cost, versatile approach to construct multifunctional neural probes that can be applied to both fundamental and translational neuroscience.
Members of the Geobacteraceae family are ubiquitous metal reducers that utilize conductive ‘nanowires’ to reduce Mn(IV) and Fe(III) oxides in anaerobic sediments. However, it is not currently known if and to what extent the Mn(IV) and Fe(III) oxides in soil grains and low permeability sediments that are sequestered in pore spaces too small for cell passage can be reduced by long-range extracellular electron transport via Geobacter nanowires, and what mechanisms control this reduction. We developed a microfluidic reactor that physically separates Geobacter sulfurreducens from the Mn(IV) mineral birnessite by a 1.4 μm thick wall containing <200 nm pores. Using optical microscopy and Raman spectroscopy, we show that birnessite can be reduced up to 15 μm away from cell bodies, similar to the reported length of Geobacter nanowires. Reduction across the nanoporous wall required reducing conditions, provided by Escherichia coli, and an exogenous supply of riboflavin. Our results discount electron shuttling by dissolved flavins, and instead support their role as bound redox cofactors in electron transport from nanowires to metal oxides. We also show that upon addition of a soluble electron shuttle (i.e., AQDS), reduction extends beyond the reported nanowire length up to 40 μm into a layer of birnessite.
Fibrosis and hence capsule formation around the glaucoma implants are the main reasons for glaucoma implant failure. To address these issues, we designed a microfluidic meshwork and tested its biocompatibility in a rabbit eye model. The amount of fibrosis elicited by the microfluidic meshwork was compared to the amount elicited by the plate of conventional glaucoma drainage device
All-optical switches have been considered as a promising solution to overcome the fundamental speed limit of the current electronic switches. However, the lack of a suitable third-order nonlinear material greatly hinders the development of this technology. Here we report the observation of ultrahigh third-order nonlinearity about 0.45 cm2/GW in graphene oxide thin films at the telecommunication wavelength region, which is four orders of magnitude higher than that of single crystalline silicon. Besides, graphene oxide is water soluble and thus easy to process due to the existence of oxygen containing groups. These unique properties can potentially significantly advance the performance of all-optical switches.
Well-defined palladium–gold nanoparticles (PdAuNPs) with randomly alloyed structures and broadly tunable compositions were studied in catalytic nitrite (NO2–) reduction. The catalysts were synthesized using a microwave-assisted polyol coreduction method. PdxAu100–xNPs with systematically varied compositions (x = 18–83) were supported on amorphous silica (SiO2) and studied as model catalysts for aqueous NO2– reduction in a batch reactor, using H2 as the electron donor. The reactions followed pseudo-first-order kinetics for ≥80% NO2– conversion. The PdxAu100–xNP-SiO2 catalysts showed a volcano-like correlation between NO2– reduction activity and x; the highest activity was observed for Pd53Au47, with an associated first-order rate constant of 5.12 L min–1 gmetal–1. Alloy NPs with greater proportions of Au were found to reduce the loss in catalytic activity due to sulfide fouling. Density functional theory calculations indicate that this is because Au weakens sulfur binding at PdAuNP surfaces due to atomic ensemble, electronic, and strain effects and thus reduces sulfur poisoning. The environmental relevance of the most active supported catalyst was evaluated by subjecting it to five cycles of catalytic NO2– reduction. The catalytic activity decreased over multiple cycles, but analysis of the postreaction PdxAu100–xNP-SiO2 materials using complementary techniques indicated that there were no significant structural changes. Most importantly, we show that PdxAu100–xNP-SiO2 alloys are significantly more active NO2– reduction catalysts in comparison to pure Pd catalysts.
Aromatic molecules with pi electrons are commonly involved in chemical and biological recognitions. For example, nucleobases play central roles in DNA/RNA structure and their interactions with proteins. The delocalization of the pi electrons is responsible for the high polarizability of aromatic molecules. In this work, the AMOEBA force field has been developed and applied to 5 regular nucleobases and 12 aromatic molecules. The permanent electrostatic energy is expressed as atomic multipole interactions between atom pairs, and many-body polarization is accounted for by mutually induced atomic dipoles. We have systematically investigated aromatic ring stacking and aromatic-water interactions for nucleobases and aromatic molecules, as well as base-base hydrogen-bonding pair interactions, all at various distances and orientations. van der Waals parameters were determined by comparison to the quantum mechanical interaction energy of these dimers and fine-tuned using condensed phase simulation. By comparing to quantum mechanical calculations, we show that the resulting classical potential is able to accurately describe molecular polarizability, molecular vibrational frequency, and dimer interaction energy of these aromatic systems. Condensed phase properties, including hydration free energy, liquid density, and heat of vaporization, are also in good overall agreement with experimental values. The structures of benzene liquid phase and benzene-water solution were also investigated by simulation and compared with experimental and PDB structure derived statistical results.
Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.
Physical, chemical, and biological interactions between groundwater and sedimentary rock directly control the fundamental subsurface properties such as porosity, permeability, and flow. This is true for a variety of subsurface scenarios, ranging from shallow groundwater aquifers to deeply buried hydrocarbon reservoirs. Microfluidic flow cells are now commonly being used to study these processes at the pore scale in simplified pore structures meant to mimic subsurface reservoirs. However, these micromodels are typically fabricated from glass, silicon, or polydimethylsiloxane (PDMS), and are therefore incapable of replicating the geochemical reactivity and complex three-dimensional pore networks present in subsurface lithologies. To address these limitations, we developed a new microfluidic experimental test bed, herein called the Real Rock-Microfluidic Flow Cell (RR-MFC). A porous 500 μm-thick real rock sample of the Clair Group sandstone from a subsurface hydrocarbon reservoir of the North Sea was prepared and mounted inside a PDMS microfluidic channel, creating a dynamic flow-through experimental platform for real-time tracking of subsurface reactive transport. Transmitted and reflected microscopy, cathodoluminescence microscopy, Raman spectroscopy, and confocal laser microscopy techniques were used to (1) determine the mineralogy, geochemistry, and pore networks within the sandstone inserted in the RR-MFC, (2) analyze non-reactive tracer breakthrough in two- and (depth-limited) three-dimensions, and (3) characterize multiphase flow. The RR-MFC is the first microfluidic experimental platform that allows direct visualization of flow and transport in the pore space of a real subsurface reservoir rock sample, and holds potential to advance our understandings of reactive transport and other subsurface processes relevant to pollutant transport and cleanup in groundwater, as well as energy recovery.