Studies on tuning surface electronic properties of hydrogenated diamond by oxygen functionalization

Ultra-wide bandgap and the absence of shallow dopants are the major challenges in realizing diamond based electronics. However, the surface functionalization offers an excellent alternative to tune electronic structure of diamonds. Herein, we report on tuning the surface electronic properties of hydrogenated polycrystalline diamond films through oxygen functionalization. The hydrogenated diamond (HD) surface transforms from hydrophobic to hydrophilic nature and the sheet resistance increases from ~ 8 kohms/sq. to over 10 Gohms/sq. with progressive ozonation. The conductive atomic force microscopic (c-AFM) studies reveal preferential higher current conduction on selective grain interiors (GIs) than that of grain boundaries confirming the surface charge transfer doping on these HDs. In addition, the local current conduction is also found to be much higher on (111) planes as compared to (100) planes on pristine and marginally O-terminated HD. However, there is no current flow on the fully O-terminated diamond (OD) surface. Further, X-ray photoelectron spectroscopic (XPS) studies reveal a redshift in binding energy (BE) of C1s on pristine and marginally O-terminated HD surfaces indicating surface band bending whilst the BE shifts to higher energy for OD. Moreover, XPS analysis also corroborate c-AFM study for the possible charge transfer doping mechanism on the diamond films which results in high current conduction on GIs of pristine and partially O-terminated HDs.Comment: 24 pages, 6 figures, 1 tabl

Thermogravimetry-evolved gas analysis-mass spectrometry system for materials research

Thermal analysis is a widely used analytical technique for materials research. However, thermal analysis with simultaneous evolved gas analysis describes the thermal event more precisely and completely. Among various gas analytical techniques, mass spectrometry has many advantages. Hence, an ultra high vacuum (UHV) compatible mass spectrometry based evolved gas analysis (EGA-MS) system has been developed. This system consists of a measurement chamber housing a mass spectrometer, spinning rotor gauge and vacuum gauges coupled to a high vacuum, high temperature reaction chamber. A commercial thermogravimetric analyser (TGA: TG + DTA) is interfaced to it. Additional mass flow based gas/vapour delivery system and calibration gas inlets have been added to make it a versatile TGA-EGA-MS facility. This system which gives complete information on weight change, heat change, nature and content of evolved gases is being used for (i) temperature programmed decomposition (TPD), (ii) synthesis of nanocrystalline materials, (iii) gas-solid interactions and (iv) analysis of gas mixtures. The TPD of various inorganic oxyanion solids are studied and reaction intermediates/products are analysed off-line. The dynamic operating conditions are found to yield nanocrystalline products in many cases. This paper essentially describes design features involved in coupling the existing EGA-MS system to TGA, associated fluid handling systems, the system calibration procedures and results on temperature programmed decomposition. In addition, synthesis of a few nanocrystalline oxides by vacuum thermal decomposition, gas analysis and potential use of this facility as controlled atmosphere exposure facility for studying gas-solid interactions are also described

Surface nitridation of Ti and Cr in ammonia atmosphere

Surface nitridation of pure Ti and Cr was carried out by exposing them to ammonia atmosphere at optimum temperatures in a thermogravimetric analyzer-mass spectrometer (TGA-MS) system. The nitrided specimens were characterized by PXRD, GIXRD, SPM, surface and cross sectional SEM and Microhardness tester

Isoprenoid Pathway Optimization for Taxol Precursor Overproduction in Escherichia coli

Author Manuscript February 6, 2011Taxol (paclitaxel) is a potent anticancer drug first isolated from the Taxus brevifolia Pacific yew tree. Currently, cost-efficient production of Taxol and its analogs remains limited. Here, we report a multivariate-modular approach to metabolic-pathway engineering that succeeded in increasing titers of taxadiene—the first committed Taxol intermediate—approximately 1 gram per liter (~15,000-fold) in an engineered Escherichia coli strain. Our approach partitioned the taxadiene metabolic pathway into two modules: a native upstream methylerythritol-phosphate (MEP) pathway forming isopentenyl pyrophosphate and a heterologous downstream terpenoid–forming pathway. Systematic multivariate search identified conditions that optimally balance the two pathway modules so as to maximize the taxadiene production with minimal accumulation of indole, which is an inhibitory compound found here. We also engineered the next step in Taxol biosynthesis, a P450-mediated 5α-oxidation of taxadiene to taxadien-5α-ol. More broadly, the modular pathway engineering approach helped to unlock the potential of the MEP pathway for the engineered production of terpenoid natural products

Counter-current chromatography for the separation of terpenoids: A comprehensive review with respect to the solvent systems employed

Copyright @ 2014 The Authors.This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Natural products extracts are commonly highly complex mixtures of active compounds and consequently their purification becomes a particularly challenging task. The development of a purification protocol to extract a single active component from the many hundreds that are often present in the mixture is something that can take months or even years to achieve, thus it is important for the natural product chemist to have, at their disposal, a broad range of diverse purification techniques. Counter-current chromatography (CCC) is one such separation technique utilising two immiscible phases, one as the stationary phase (retained in a spinning coil by centrifugal forces) and the second as the mobile phase. The method benefits from a number of advantages when compared with the more traditional liquid-solid separation methods, such as no irreversible adsorption, total recovery of the injected sample, minimal tailing of peaks, low risk of sample denaturation, the ability to accept particulates, and a low solvent consumption. The selection of an appropriate two-phase solvent system is critical to the running of CCC since this is both the mobile and the stationary phase of the system. However, this is also by far the most time consuming aspect of the technique and the one that most inhibits its general take-up. In recent years, numerous natural product purifications have been published using CCC from almost every country across the globe. Many of these papers are devoted to terpenoids-one of the most diverse groups. Naturally occurring terpenoids provide opportunities to discover new drugs but many of them are available at very low levels in nature and a huge number of them still remain unexplored. The collective knowledge on performing successful CCC separations of terpenoids has been gathered and reviewed by the authors, in order to create a comprehensive document that will be of great assistance in performing future purifications. © 2014 The Author(s)

ART: A machine learning Automated Recommendation Tool for synthetic biology

Biology has changed radically in the last two decades, transitioning from a descriptive science into a design science. Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, and fatty acids. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing