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RISS 인기검색어
- 검색키워드
- 저자 : Rachuri, Sudarsan (검색결과 3 건)
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Rachuri, Yadagiri,Kurisingal, Jintu Francis,Chitumalla, Ramesh Kumar,Vuppala, Srimai,Gu, Yunjang,Jang, Joonkyung,Choe, Youngson,Suresh, Eringathodi,Park, Dae-Won American Chemical Society 2019 Inorganic Chemistry Vol.58 No.17
<P>We synthesized two new adenine-based Zn(II)/Cd(II) metal-organic frameworks (MOFs), namely, [Zn<SUB>2</SUB>(H<SUB>2</SUB>O)(stdb)<SUB>2</SUB>(5H-Ade)(9H-Ade)<SUB>2</SUB>]<SUB><I>n</I></SUB> (PNU-21) and [Cd<SUB>2</SUB>(Hstdb)(stdb)(8H-Ade)(Ade)]<SUB><I>n</I></SUB> (PNU-22), containing auxiliary dicarboxylate ligand (stdb = 4,4′-stilbenedicarboxylate). Both MOFs were characterized by multiple analytical techniques such as single-crystal X-ray diffraction (SXRD), powder X-ray diffraction, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, thermogravimetric analysis, scanning electron microscopy, as well as temperature program desorption and Brunauer-Emmett-Teller measurements. Both MOFs were structurally robust and possessed unsaturated Lewis acidic metal centers [Zn(II) and Cd(II)] and free basic N atoms of adenine molecules. They were used as heterogeneous catalysts for the fixation of CO<SUB>2</SUB> into five-membered cyclic carbonates. Significant conversion of epichlorohydrin (ECH) was attained at a low CO<SUB>2</SUB> pressure (0.4 MPa) and moderate catalyst (0.6 mol %)/cocatalyst (0.3 mol %) amounts, with over 99% selectivity toward the ECH carbonate. They showed comparable or even higher catalytic activity than other previously reported MOFs. Because of high thermal stability and robust architecture of PNU-21/PNU-22, both catalysts could be reused with simple separation up to five successive cycles without any considerable loss of their catalytic activity. Densely populated acidic and basic sites in both Zn(II)/Cd(II) MOFs facilitated the conversion of ECH to ECH carbonate in high yields. The reaction mechanism of the cycloaddition reaction between ECH and CO<SUB>2</SUB> is described by possible intermediates, transition states, and pathways, from the density functional theory calculation in correlation with the SXRD structure of PNU-21.</P><P>Adenine-based two Zn(II)/Cd(II) metal−organic frameworks were synthesized and characterized by various analytical techniques including SXRD. Both MOFs were utilized as potential catalysts for the syntheses of cyclic carbonates from CO<SUB>2</SUB> and epoxides. The mechanistic aspects of cycloaddition reaction of CO<SUB>2</SUB> and ECH were studied systematically by DFT.</P> [FIG OMISSION]</BR>
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An energy-efficient process planning system using machine-monitoring data: A data analytics approach
Shin, Seung-Jun,Woo, Jungyub,Rachuri, Sudarsan,Seo, Wonchul Elsevier 2019 Computer aided design Vol.110 No.-
<P><B>Abstract</B></P> <P>This paper presents a system development of incorporating Computer-Aided Process Planning (CAPP) with energy-efficient machining based on a hybrid approach to take advantage of Generative Process Planning (GPP) and Variant Process Planning (VPP) and compensate for the drawbacks of both GPP and VPP. The GPP decides process plans without human assistance through decision-making algorithms in computers but lacks in ensuring the models’ robustness for different machining conditions. The VPP adopts group technology by reusing existing plans through the identification and classification of part family but does not support predictive and optimum decision-making. The developed Energy-Efficient Process Planning System (EEPPS) builds upon data analytics to efficiently process the machine-monitoring data collected from real machine tool’s operations and to develop energy prediction and optimization models based on historical machine-monitoring data. Particularly, those energy prediction and optimization models allow process planners to anticipate the energy consumed during executing a numerical control program and optimize process parameters at the level of machining features for minimizing energy use. This paper also presents a prototype implementation to show the feasibility of the proposed EEPPS.</P>
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Shin, S.J.,Woo, J.,Rachuri, S. Butterworth-Heinemann, Ltd 2017 Journal of cleaner production Vol.161 No.-
Energy consumption is a major sustainability focus in the metal cutting industry. As a result, process planning is increasingly concerned with reducing energy consumption in machine tools. The relevant literature has been categorized into two research areas. The first includes energy prediction models, which characterize the relationships between cutting parameters - the main outputs of process planning - and energy consumption. The second involves energy-consumption optimization, which uses the prediction models to find the cutting parameters that minimize energy use. However, previous energy prediction models are limited to predict energy for tool paths coded in a Numerical Control (NC) program. Previous energy optimization methods typically do not use online optimization, which enables fast optimization decision-making for supporting on-demand process planning and real-time machine control. This paper presents a component-based energy-modeling methodology to implement the online optimization needed for real-time control. Models that can predict energy up to the tool path-level at specific machining configurations are called component-models in this paper. These component-models are created using historical data that includes process plans, NC programs, and machine-monitoring data. The online optimization is implemented using a dynamic composition of component-models together with a divide-and-conquer technique. The feasibility and effectiveness of our methodology has been demonstrated in a milling-machine example.
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