Nitrogen-Doped Carbon Nanoparticles by Flame Synthesis as Anode Material for Rechargeable Lithium-Ion Batteries

Bhattacharjya, Dhrubajyoti,Park, Hyean-Yeol,Kim, Min-Sik,Choi, Hyuck-Soo,Inamdar, Shaukatali N.,Yu, Jong-Sung American Chemical Society 2014 Langmuir Vol.30 No.1

<P>Nitrogen-doped turbostratic carbon nanoparticles (NPs) are prepared using fast single-step flame synthesis by directly burning acetonitrile in air atmosphere and investigated as an anode material for lithium-ion batteries. The as-prepared N-doped carbon NPs show excellent Li-ion stoarage properties with initial discharge capacity of 596 mA h g<SUP>–1</SUP>, which is 17% more than that shown by the corresponding undoped carbon NPs synthesized by identical process with acetone as carbon precursor and also much higher than that of commercial graphite anode. Further analysis shows that the charge–discharge process of N-doped carbon is highly stable and reversible not only at high current density but also over 100 cycles, retaining 71% of initial discharge capacity. Electrochemical impedance spectroscopy also shows that N-doped carbon has better conductivity for charge and ions than that of undoped carbon. The high specific capacity and very stable cyclic performance are attributed to large number of turbostratic defects and N and associated increased O content in the flame-synthesized N-doped carbon. To the best of our knowledge, this is the first report which demonstrates single-step, direct flame synthesis of N-doped turbostratic carbon NPs and their application as a potential anode material with high capacity and superior battery performance. The method is extremely simple, low cost, energy efficient, very effective, and can be easily scaled up for large scale production.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/langd5/2014/langd5.2014.30.issue-1/la403366e/production/images/medium/la-2013-03366e_0006.gif'></P>

High capacity and exceptional cycling stability of ternary metal sulfide nanorods as Li ion battery anodes.

Bhattacharjya, Dhrubajyoti,Sinhamahapatra, Apurba,Ko, Jae-Jung,Yu, Jong-Sung The Royal Society of Chemistry 2015 Chemical communications Vol.51 No.69

<P>Ternary spinel NiCo2S4 nanorods are tested for the first time as anode electrodes for Li ion batteries. When the electrode is fabricated using the carboxymethyl cellulose-polyacryl amide composite binder, it is found to restrict or suppress the formation of a polymeric gel passivation layer. As a result, the electrode not only delivers excellent specific capacity, but also an outstanding rate and cyclic stability with almost no decay up to 100 charge-discharge cycles.</P>

Graphene Nanoplatelets with Selectively Functionalized Edges as Electrode Material for Electrochemical Energy Storage

Bhattacharjya, Dhrubajyoti,Jeon, In-Yup,Park, Hyean-Yeol,Panja, Tandra,Baek, Jong-Beom,Yu, Jong-Sung American Chemical Society 2015 Langmuir Vol.31 No.20

<P>In recent years, graphene-based materials have been in the forefront as electrode material for electrochemical energy generation and storage. Despite this prevalent interest, synthesis procedures have not attained three important efficiency requirements, that is, cost, energy, and eco-friendliness. In this regard, in the present work, graphene nanoplatelets with selectively functionalized edges (XGnPs) are prepared through a simple, eco-friendly and efficient method, which involves ball milling of graphite in the presence of hydrogen (H-2), bromine (Br-2), and iodine (I-2). The resultant HGnP, BrGnP, and IGnP reveal significant exfoliation of graphite layers, as evidenced by high BET surface area of 414, 595, and 772 m(2) g(-1), respectively, in addition to incorporation of H, Br, and I along with other oxygen-containing functional groups at the graphitic edges. The BrGnP and IGnP are also found to contain 4.12 and 2.20 at % of Br and I, respectively in the graphene framework. When tested as supercapacitor electrode, all XGnPs show excellent electrochemical performance in terms of specific capacitance and durability at high current density and long-term operation. Among XGnPs, IGnP delivers superior performance of 172 F g(-1) at 1 A g(-1) compared with 150 F g(-1) for BrGnP and 75 F g(-1) for HGnP because the large surface area and high surface functionality in the IGnP give rise to the outstanding capacitive performance. Moreover, all XGnPs show excellent retention of capacitance at high current density of 10 A g(-1) and for long-term operation up to 1000 charge-discharge cycles.</P>

Fast and controllable reduction of graphene oxide by low-cost CO₂ laser for supercapacitor application

Bhattacharjya, Dhrubajyoti,Kim, Chang-Hyeon,Kim, Jae-Hyun,You, In-Kyu,In, Jung Bin,Lee, Seung-Mo Elsevier 2018 APPLIED SURFACE SCIENCE - Vol.462 No.-

<P><B>Abstract</B></P> <P>Direct reduction of graphene oxide has been regarded as the economically viable route for large-scale synthesis of graphene. However, the currently known methods suffer from either poor reduction efficiency or involve multi-step and energy-intensive reduction processes. Here, we demonstrate a remarkably fast, single step as well as highly efficient reduction technique to produce high-quality multilayer graphene film using a compact and low-cost CO<SUB>2</SUB> laser pyrolysis. Thanks to the intrinsically high absorptivity of graphene oxide in the near- and mid-infrared regions, the irradiation of CO<SUB>2</SUB> laser generates instantaneous and strong localized heating on it and thus burst apart the oxygen functional groups from the graphene oxide layers. The extent of reduction in the synthesized multilayer graphene films can be fruitfully controlled by variation of laser processing parameters such as laser intensity, scanning speed and shifting pitch. To prove the worth of this method, the graphene films were used as the binder-free and self-standing electrode for symmetric supercapacitor cell. The electrochemical performance data shows that specific capacitance and cyclic stability has a contrasting relation with the reduction efficiency. We believe that this CO<SUB>2</SUB> laser-based reduction method could guarantee a high outturn of multilayer graphene and its composites for innumerable applications.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Instantaneous reduction of graphene oxide is achieved by using inexpensive CO<SUB>2</SUB> laser. </LI> <LI> The extent of reduction is controlled by changing the laser processing parameters. </LI> <LI> Very high carbon to hetero atom ratio is achieved in the synthesized graphene in this method. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>Low-cost CO<SUB>2</SUB> laser allows incomparably fast and efficient reduction of graphene oxide film to produce high quality multilayer graphene.</P> <P>[DISPLAY OMISSION]</P>

Robust optimization of reinforced concrete folded plate and shell roof structure incorporating parameter uncertainty

Soumya Bhattacharjya,Subhasis Chakraborti,Subhashis Das 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.56 No.5

There is a growing trend of considering uncertainty in optimization process since last few decades. In this regard, Robust Design Optimization (RDO) scheme has gained increasing momentum because of its virtue of improving performance of structure by minimizing the variation of performance and ensuring necessary safety and feasibility of constraint under uncertainty. In the present study, RDO of reinforced concrete folded plate and shell structure has been carried out incorporating uncertainty in the relevant parameters by Monte Carlo Simulation. Folded plate and shell structures are among the new generation popular structures often used in aesthetically appealing constructions. However, RDO study of such important structures is observed to be scarce. The optimization problem is formulated as cost minimization problem subjected to the force and displacements constraints considering dead, live and wind load. Then, the RDO is framed by simultaneously optimizing the expected value and the variation of the performance function using weighted sum approach. The robustness in constraint is ensured by adding suitable penalty term and through a target reliability index. The RDO problem is solved by Sequential Quadratic Programming. Subsequently, the results of the RDO are compared with conventional deterministic design approach. The parametric study implies that robust designs can be achieved by sacrificing only small increment in initial cost, but at the same time, considerable quality and guarantee of the structural behaviour can be ensured by the RDO solutions.

Performance of an Artificial Neural Network Model for Simulating Saltwater Intrusion Process in Coastal Aquifers when Training with Noisy Data

Rajib Kumar Bhattacharjya,Bithin Datta,Mysore G. Satish 대한토목학회 2009 KSCE JOURNAL OF CIVIL ENGINEERING Vol.13 No.3

This paper evaluates the performance of an Artificial Neural Networks (ANN) model for approximating density depended saltwater intrusion process in coastal aquifer when the ANN model is trained with noisy training data. The data required for training, testing and validation of the ANN model are generated using a numerical simulation model. The simulated data, consisting of corresponding sets of input and output patterns are used for training a multilayer perception using back-propagation algorithm. The trained ANN predicts the concentration at specified observation locations at different time steps. The performance of the ANN model is evaluated using an illustrative study area. These evaluation results show the efficient predicting capabilities of an ANN model when trained with noisy data. A comparative study is also carried out for finding the better transfer function of the artificial neuron and better training algorithms available in Matlab for training the ANN model. This paper evaluates the performance of an Artificial Neural Networks (ANN) model for approximating density depended saltwater intrusion process in coastal aquifer when the ANN model is trained with noisy training data. The data required for training, testing and validation of the ANN model are generated using a numerical simulation model. The simulated data, consisting of corresponding sets of input and output patterns are used for training a multilayer perception using back-propagation algorithm. The trained ANN predicts the concentration at specified observation locations at different time steps. The performance of the ANN model is evaluated using an illustrative study area. These evaluation results show the efficient predicting capabilities of an ANN model when trained with noisy data. A comparative study is also carried out for finding the better transfer function of the artificial neuron and better training algorithms available in Matlab for training the ANN model.

Nitrogen and phosphorus co-doped cubic ordered mesoporous carbon as a supercapacitor electrode material with extraordinary cyclic stability

Panja, T.,Bhattacharjya, D.,Yu, J. S. Royal Society of Chemistry 2015 Journal of materials chemistry. A, Materials for e Vol.3 No.35

Facile Synthesis of Hexagonal NiCo2O4 Nanoplates as High-Performance Anode Material for Li-Ion Batteries

Sudeshna Chaudhari,Dhrubajyoti Bhattacharjya,유종성 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.9

Ternary spinal NiCo2O4 nanostructure holds great promise as high-performance anode material for next generation Li-ion batteries because of its higher electrical conductivity and electrochemical activity. In this work, two-dimensional hexagonal NiCo2O4 nanoplates are synthesized by a simple and cost-effective template-free method through co-precipitation decomposition route using sodium hydroxide as the precipitant followed by annealing in air at 400 °C for 2 h. Various characterization methods prove that hexagonal NiCo2O4 nanoplates are successfully synthesized by this process and have high amount of mesopores on its surface. The electrochemical study of these hexagonal NiCo2O4 nanoplates as Li-ion battery anode shows that the highly mesoporous nanoplate morphology plays an important role in cycling stability and rate capability. As a result, the hexagonal NiCo2O4 exhibits a high reversible charge capacity of 918 mAh/g at a current density of 60 mA/g (0.06 C) with excellent capacity retention of 92% up to 50 charge–discharge cycles.

Highly efficient metal-free phosphorus-doped platelet ordered mesoporous carbon for electrocatalytic oxygen reduction

Yang, D.S.,Bhattacharjya, D.,Song, M.Y.,Yu, J.S. Pergamon Press ; Elsevier Science Ltd 2014 Carbon Vol.67 No.-

Platinum-free electrocatalysts especially, various heteroatom-doped carbon nanostructures have attracted particular attraction as plausible solution for commercializing fuel cell technology. In this direction, novel phosphorus-doped platelet ordered mesoporous carbon (P-pOMC) is developed for the first time as metal-free electrocatalyst for alkaline oxygen reduction reaction. The P-pOMC is synthesized by nanocasting method using platelet ordered mesoporous silica as template. Various characterizations reveal that the P-pOMC materials have covalently bound P atoms with carbon framework for facilitation of oxygen reduction reaction (ORR) and also have very high surface area with uniform distribution of short mesoporous channels for unhindered mass transfer. Combination of P doping and excellent surface properties empowers the newly-developed P-pOMC catalyst to show high ORR activity nearly equal to that of state of the art Pt catalyst along with superior long-term stability and excellent methanol tolerance.

Functionalized Agarose Self-Healing Ionogels Suitable for Supercapacitors

Trivedi, Tushar J.,Bhattacharjya, Dhrubajyoti,Yu, Jong-Sung,Kumar, Arvind Wiley Blackwell (John Wiley Sons) 2015 CHEM SUS CHEM Vol.8 No.19