Anshuman Satpathy
Washington University in St. Louis
13 Papers
Anshuman Satpathy is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Adsorption & Chemistry. The author has an hindex of 1, co-authored 2 publications.
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Papers
Cr(VI)Adsorption on Engineered Iron Oxide Nanoparticles:Exploring Complexation Processes and Water Chemistry
TL;DR: The affinity of Cr(VI) adsorption to 8 nm surface-functionalized superparamagnetic magnetite nanoparticles was determined for surface coatings with amine and carboxyl functional groups, confirming the importance of the overall water composition on the performance of novel engineered nanomaterials for water treatment applications.
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Reduction of U(VI) on Chemically Reduced Montmorillonite and Surface Complexation Modeling of Adsorbed U(IV).
TL;DR: In this paper , the authors investigated the extent of reduction of U(VI) by Fe(II)-bearing montmorillonite at different pH values and sodium concentrations using X-ray absorption spectroscopy and chemical extractions.
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Intercomparison and Refinement of Surface Complexation Models for U(VI) Adsorption onto Goethite Based on a Metadata Analysis.
TL;DR: In this paper, the authors conducted an intercomparison and refinement of the surface complexation models (SCMs) based on a metadata analysis and developed a series of models with different levels of complexity following a systematic roadmap.
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Ligand-Induced U Mobilization from Chemogenic Uraninite and Biogenic Noncrystalline U(IV) under Anoxic Conditions
Kyle Chardi,Anshuman Satpathy,Walter D. C. Schenkeveld,Naresh Kumar,V. Noël,Stephan M. Kraemer,Daniel E. Giammar +6 more
TL;DR: In this article , a set of structurally diverse organic ligands were shown to enhance the dissolution of crystalline uraninite (UO2) for a wide range of ligand concentrations under anoxic conditions at pH 7.0.
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A new real-time maximum power point tracking scheme for PV-BASED microgrid STABILITY using online DEEP ridge extreme learning machine algorithm
Anshuman Satpathy,Niranjan Nayak,Naeem Hannon,N.H. Nik Ali +3 more
TL;DR: A novel real-time MPPT scheme for PV-based microgrid stability is proposed, utilizing a deep representation-based Ridge Regression Extreme Learning Machine algorithm for accurate control reference calculation and stability improvement at the point of common coupling.
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