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2023 AIChE Annual Meeting

作者： Chen, Feng-Yang Wu, Zhen-Yu Gupta, Srishti Rivera, Daniel J. Lambeets, Sten V. Pecaut, Stephanie Kim, Jung Yoon Timothy Zhu, Peng Finfrock, Y. Zou Meira, Debora Motta King, Graham Gao, Guanhui Xu, Wenqian Cullen, David A. Zhou, Hua Han, Yimo Perea, Daniel E. Muhich, Christopher L. Wang, Haotian Department of Chemical and Biomolecular Engineering Rice University HoustonTX United States School for Engineering of Matter Transport & Energy Chemical Engineering Program Arizona State University TempeAZ United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory RichlandWA United States Structural Biology Center X-ray Science Division Argonne National Laboratory LemontIL United States Canadian Light Source SaskatoonSK Canada Electron Microscope Center Department of Materials Science and NanoEngineering Rice University HoustonTX United States Advanced Photon Source Argonne National Laboratory LemontIL United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States Environmental Molecular Sciences Laboratory Earth and Biological Sciences Directorate Pacific Northwest National Laboratory RichlandWA United States School for Engineering of Matter Transport & Energy Materials Science & Engineering Program Arizona State University TempeAZ United States Department of Chemistry Rice University HoustonTX United States

Electrochemically converting nitrate ions, a widely distributed nitrogen source in industrial wastewater and polluted groundwater, into ammonia represents a sustainable route for both wastewater treatment and ammonia generation. However, it is currently hindered by low catalytic activities, especially under low nitrate concentrations. Here we report a high-performance Ru-dispersed Cu nanowire catalyst that delivers an industrial-relevant nitrate reduction current of 1 A cm-2 while maintaining a high NH3 Faradaic efficiency of 93%. More importantly, this high nitrate-reduction catalytic activity enables over a 99% nitrate conversion into ammonia, from an industrial wastewater level of 2, 000 ppm to a drinkable water level 4Cl and liquid NH3 solution products, which suggests a practical approach to convert wastewater nitrate into valuable ammonia products. Density functional theory calculations reveal that the highly dispersed Ru atoms provide active nitrate reduction sites and the surrounding Cu sites can suppress the main side reaction, the hydrogen evolution reaction. © The Author(s), under exclusive licence to Springer Nature Limited 2022.

关键词： Ammonia

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Dynamics of active liquid interfaces

arXiv

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arXiv 2022年

作者： Adkins, Raymond Kolvin, Itamar You, Zhihong Witthaus, Sven Marchetti, M. Cristina Dogic, Zvonimir Department of Physics University of California at Santa Barbara Santa BarbaraCA93106 United States Graduate program in Biomolecular Science and Engineering University of California at Santa Barbara Santa BarbaraCA93106 United States

Controlling interfaces of phase separating fluid mixtures is key to creating diverse functional soft materials. Traditionally, this is accomplished with surface-modifying chemical agents. Using experiment and theory, we study how mechanical activity shapes soft interfaces that separate an active and a passive fluid. Chaotic flows in the active fluid give rise to giant interfacial fluctuations and non-inertial propagating active waves. At high activities, stresses disrupt interface continuity and drive droplet generation, producing an emulsion-like active state comprised of finite-sized droplets. When in contact with a solid boundary, active interfaces exhibit non-equilibrium wetting transitions, wherein the fluid climbs the wall against gravity. These results demonstrate the promise of mechanically driven interfaces for creating a new class of soft active matter. © 2022, CC BY.

关键词： Emulsification

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Lignocellulose aerogel and amorphous silica nanoparticles from rice husks

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Journal of Leather science and engineering 2021年第1期3卷 11-17页

作者： Zichao Wei Andrew T.Smith William R.T.Tait Jingjing Liu Hao Ding Hui Wang Weixing Wang Luyi Sun Polymer Program Institute of Materials ScienceUniversity of ConnecticutStorrsCT 06269USA Department of Chemical&Biomolecular Engineering University of ConnecticutStorrsCT 06269USA College of Materials Science and Engineering South China University of TechnologyGuangzhou 510640GuangdongChina Key Laboratory of Enhanced Heat Transfer and Energy Conservation of the Ministry of Education School of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510640GuangdongChina Department of Biomedical Engineering University of ConnecticutStorrsCT 06269USA

Rice Husks(RHs)are one of the most abundant sources of biomass in the world due to rice *** and silica are two of the main components of RHs,which allow RHs to be applied in different *** can be partially dissolved in 1-butyl-3-methylimidazolium chloride(BMIMCl),which is a simple way of competing with the traditional extraction methods that suffer from high chemical consumption.A lignocellulose freeze gel is obtained via a cyclic liquid nitrogen freeze-thaw(NFT)***-functional self-assembled lignocellulose aerogel is obtained after CO_(2) supercritical *** on the aerogel’s special properties,two routes are developed for practical *** one hand,the aerogel is coated to exhibit a superhydrophobic property that can be applied as an absorbent for oil *** the other hand,a carbon aerogel is synthesized via a pyrolysis process,resulting in a porous amorphous *** residue after partially dissolving lignocellulose in BMIMCl is further calcined to obtain amorphous silica nanoparticles,achieving a comprehensive application of RHs.

关键词： Rice husks Lignocellulose Carbon aerogel Silica

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Effect of Different Manufacturing Methods on Polyamide Reverse-Osmosis Membranes for Desalination: Insights from Molecular Dynamics Simulations

SSRN

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SSRN 2022年

作者： He, Jinlong McCutcheon, Jeffrey R. Li, Ying Department of Mechanical Engineering University of Connecticut StorrsCT06269 United States Department of Chemical & Biomolecular Engineering Center for Environmental Sciences and Engineering University of Connecticut StorrsCT06269 United States Polymer Program Institute of Materials Science University of Connecticut StorrsCT06269 United States

The industry-leading polyamide (PA) reverse osmosis (RO) membranes can be manufactured via molecular layer-by-layer (mLBL) deposition, interfacial polymerization (IP), and 3D-printing technique. However, the influence of different manufacturing methods on PA membrane’s properties is far from understood. In this study, we present the high-pressure transport behavior of water and salt ions for PA membranes formed with IP, mLBL, and 3D-printing through non-equilibrium molecular dynamics simulations. Studies show that membranes fabricated with 3D-printing have similar performances to those manufactured using mLBL, quantified by water permeability, rejection of salt ions, structural integrity, and porosity features. However, the membranes formed with IP exhibit faster water transport, lower rejection, worse structural integrity, and more inhomogeneous network pores than those constructed using mLBL and 3D-printing. The unconnected water-accessible space governs water transport for PA membranes formed with mLBL and 3D-printing, which offers the impermanent open-closed pores that enable water to jump through PA membranes. In contrast, the permeated water-enterable space plays a prominent role in water movement across the PA membrane formed with IP, providing a continuous transport channel at high pressure. Importantly, we observe the more significant compaction features at high pressure for PA membranes formed with IP than mLBL and 3D-printing. © 2022, The Authors. All rights reserved.

关键词： Polymerization

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Challenges for and Pathways toward Li-MetalBased All-Solid-State Batteries

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ACS ENERGY LETTERS 2021年第4期6卷 1399-1404页

作者： Albertus, Paul Anandan, Venkataramani Ban, Chunmei Balsara, Nitash Belharouak, Ilias Buettner-Garrett, Josh Chen, Zonghai Daniel, Claus Doeff, Marca Dudney, Nancy J. Dunn, Bruce Harris, Stephen J. Herle, Subramanya Herbert, Eric Kalnaus, Sergiy Libera, Joesph A. Lu, Dongping Martin, Steve McCloskey, Bryan D. McDowell, Matthew T. Meng, Y. Shirley Nanda, Jagjit Sakamoto, Jeff Self, Ethan C. Tepavcevic, Sanja Wachsman, Eric Wang, Chunsheng Westover, Andrew S. Xiao, Jie Yersak, Thomas Department of Chemical and Biomolecular Engineering University of Maryland College Park Maryland 20742 United States Ford Motor Company Dearborn Michigan 48121 United States Mechanical Engineering Department University of Colorado Boulder Colorado 80309 United States Department of Chemical and Biomolecular Engineering and Lawrence Berkeley National Laboratory Materials Sciences Division University of California Berkeley California 94720 United States Energy and Transportation Science Division Oak Ridge National Laboratory Oak Ridge Tennessee 37831 United States Solid Power Inc. Louisville Colorado 80027 United States Chemical Sciences and Engineering Division Argonne National Laboratory 9700 South Cass Avenue Argonne Illinois 60439 United States Lawrence Berkeley National Laboratory Energy Storage and Distributed Resources Division University of California Berkeley California 94720 United States Department of Materials Science and Engineering University of California Los Angeles California 90095 United States Applied Materials Inc. 3225 Oakmead Village Drive B12_2F6 Santa Clara California 95054 United States Department of Materials Science and Engineering Michigan Technological University Houghton Michigan 49931 United States Energy and Environmental Directorate Pacific Northwest National Laboratory Richland Washington 99352 United States Department of Materials Science & Engineering Iowa State University of Science & Technology Ames Iowa 50011 United States Woodruff School of Mechanical Engineering and School of Materials Science and Engineering Georgia Institute of Technology Atlanta Georgia 30332 United States Department of NanoEngineering and Materials Science and Engineering Program University of California San Diego La Jolla California 92093 United States Department of Materials Science and Engineering and Department of Mechanical Engineering University of Michigan Ann Arbor Michigan 48109 United States Chemical and Materials Systems Laborat

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Nanoslot-Induced Ultrastrong Phonon-Photon and Phonon-Phonon Coupling in Hybrid Organic-Inorganic Perovskites 16

Nanoslot-Induced Ultrastrong Phonon-Photon and Phonon-Phonon...

引用

16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Kim, Dasom Hou, Jin Lee, Geon Agrawal, Ayush Kim, Sunghwan Zhang, Hao Bao, Di Baydin, Andrey Wu, Wenjing Tay, Fuyang Huang, Shengxi Hagenmüller, Daivd Chia, Elbert E. M. Kim, Dai-Sik Seo, Minah Mohite, Aditya D. Kono, Junichiro Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Sensor System Research Center Korea Institute of Science and Technology Seoul02792 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Department of Chemical and Biomolecular Engineering Rice University HoustonTX77005 United States Ulsan44919 Korea Republic of Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Smalley-Curl Institute Rice University HoustonTX77005 United States Université de Strasbourg Cnrs Strasbourg67000 France KU-KIST Graduate School of Converging Science and Technology Korea University Seoul02841 Korea Republic of Department of Physics and Astronomy Rice University HoustonTX77005 United States

Methods for harnessing vibrational states are desired for phonon-based technologies. We realized ultrastrong coupling of two phonon modes in perovskite materials induced by ultrastrong coupling with a common photonic ... 详细信息

ISBN: (纸本)9798350372076

关键词： Organic-inorganic materials

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Cyclodextrin-Modified Layered Double Hydroxide Thin-Film Nanocomposite Desalination Membrane for Boron Removal

SSRN

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SSRN 2023年

作者： Ee, Liang Ying Zhao, Qipeng Gao, Jie Lim, Chit Kai Xue, Kai Chin, Sze Yuet Li, Sam Fong Yau Chung, Tai-Shung Chen, Shing Bor Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore 4 Engineering Drive 4 Singapore117585 Singapore Department of Chemistry College of Humanities and Sciences National University of Singapore 3 Science Drive 3 Singapore117543 Singapore Chemical Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Centre of High Field NMR Spectroscopy and Imaging School of Physical and Mathematical Sciences College of Science Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore NUS Environmental Research Institute National University of Singapore T-Lab Building 5A Engineering Drive 1 Singapore117411 Singapore Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei106335 Taiwan

The elimination of small and potentially toxic boron species in water is always a significant challenge for conventional membrane technologies. In this study, facile intercalation and functionalization of β-cyclodextrin (CD) onto layered double hydroxides (LDHs) have resulted in the formation of accessible hydroxyl functional groups and anions that exhibit strong sorption with boron. Through meticulous molecular design and optimization, the modified LDH possessing the maximum boron adsorption capacity of 96.1 mg g-1 was employed to fabricate a polyamide-based thin-film nanocomposite (TFN) membrane with a loading of 0.10 wt.%. This resultant membrane displayed a high salt rejection and water permeance of 99.4 % and 2.68 LMH bar-1 for brackish water, respectively, which can be attributed to the increased interlayer spacing of 1.67 nm and the thinner selective layer. The innovative TFN membrane also achieved a high boron rejection of 82.3 % against brackish water containing 2,000 mg L-1 NaCl and 15 mg L-1 B at pH 8. This pioneering study provides valuable insights into the design of brackish water reverse osmosis (BWRO) membranes, through the synergistic use of macrocyclic molecules and inorganic layered nanomaterials, that could potentially revolutionize water reuse and boron removal applications. © 2023, The Authors. All rights reserved.

关键词： Sodium chloride

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Machine-learned molecular surface and its application to implicit solvent simulations

arXiv

引用

arXiv 2021年

作者： Wei, Haixin Zhao, Zekai Luo, Ray Departments of Materials Science and Engineering Molecular Biology and Biochemistry Chemical and Biomolecular Engineering and Biomedical Engineering Graduate Program in Chemical and Materials Physics University of California IrvineCA92697 United States

Implicit solvent models, such as Poisson-Boltzmann models, play important roles in computational studies of biomolecules. A vital step in almost all implicit solvent models is to determine the solvent-solute interface, and the solvent excluded surface (SES) is the most widely used interface definition in these models. However, classical algorithms used for computing SES are geometry-based, thus neither suitable for parallel implementations nor convenient for obtaining surface derivatives. To address the limitations, we explored a machine learning strategy to obtain a level-set formulation for the SES. The training process was conducted in three steps, eventually leading to a model with over 95% agreement with the classical SES. Visualization of tested molecular surfaces shows that the machine-learned SES overlaps with the classical SES on almost all situations. We also implemented the machine-learned SES into the Amber/PBSA program to study its performance on reaction field energy calculation. The analysis shows that the two sets of reaction field energies are highly consistent with 1% deviation on average. Given its level-set formulation, we expect the machine-learned SES to be applied in molecular simulations that require either surface derivatives or high efficiency on parallel computing platforms. © 2021, CC BY.

关键词： Solvents

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Artificial Intelligence in Cancer Immunotherapy: Navigating Challenges and Unlocking Opportunities

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engineering 2025年第1期44卷 12-16页

作者： Xiang, Wei Yu, Lu Chen, Xiaoyuan Herold, Marco J. Australian Centre for Artificial Intelligence in Medical Innovation La Trobe University MelbourneVIC3086 Australia School of Computing Engineering and Mathematical Sciences La Trobe University MelbourneVIC3086 Australia Department of Diagnostic Radiology Yong Loo Lin School of Medicine National University of Singapore Singapore119074 Singapore Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore Singapore117575 Singapore Department of Biomedical Engineering College of Design and Engineering National University of Singapore Singapore117575 Singapore Department of Pharmacy and Pharmaceutical Sciences Faculty of Science National University of Singapore Singapore117544 Singapore Clinical Imaging Research Centre Centre for Translational Medicine Yong Loo Lin School of Medicine National University of Singapore Singapore117599 Singapore Nanomedicine Translational Research Program Yong Loo Lin School of Medicine National University of Singapore Singapore117597 Singapore Yong Loo Lin School of Medicine National University of Singapore Singapore138667 Singapore Singapore138673 Singapore Olivia Newton-John Cancer Research Institute HeidelbergVIC3084 Australia School of Cancer Medicine La Trobe University MelbourneVIC3086 Australia The Walter and Eliza Hall Institute of Medical Research ParkvilleVIC3052 Australia Department of Medical Biology University of Melbourne ParkvilleVIC3010 Australia

Cancer continues to be a major cause of global mortality rates, with conventional treatments such as chemotherapy and radiotherapy exhibiting inconsistent efficacy, high costs, and considerable side effects. Over the past decade, a promising alternative has emerged: cancer immunotherapy, which leverages the body’s immune system to identify and eradicate cancer cells. Significant progress has been made in several novel immunotherapies, including immune checkpoint inhibitors (ICIs), chimeric antigen receptor T-cell therapies, and personalized therapeutic cancer vaccines. However, the heterogeneity and complexity of cancer types still pose enormous challenges. The efficient use of large numbers of medical datasets is essential for overcoming these obstacles. Without artificial intelligence (AI), linking translational and clinical data to derive meaningful insights would remain an insurmountable task. Recently, single-cell RNA sequencing cell typing (scGPT), a pretrained generative model utilizing a database of more than 33 million cells, is developed to accurately extract important biological insights concerning cellular biology. A personalized learning workflow is also proposed as a simple and effective pipeline to discover neoantigens for cancer immunotherapy.

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Superionic surface Li-ion transport in carbonaceous materials

arXiv

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arXiv 2024年

作者： Zhou, Jianbin Wang, Shen Wu, Chaoshan Qi, Ji Wan, Hongli Lai, Shen Feng, Shijie Ko, Tsz Wai Liang, Zhaohui Zhou, Ke Harpak, Nimrod Solan, Nick Liu, Mengchen Hui, Zeyu Ai, Paulina J. Griffith, Kent Wang, Chunsheng Ong, Shyue Ping Yao, Yan Liu, Ping Department of Nanoengineering University of California San Diego La Jolla CA United States Materials Science and Engineering Program Texas Center for Superconductivity The University of Houston University of Houston HoustonTX United States Department of Chemical and Biomolecular Engineering University of Maryland College ParkMD United States Department of Chemistry and Biochemistry University of California San Diego La Jolla CA92093 United States The Bishop's School La Jolla CA92037 United States

Unlike Li-ion transport in the bulk of carbonaceous materials, little is known about Li-ion diffusion on their surface. In this study, we have discovered an ultra-fast Li-ion transport phenomenon on the surface of carbonaceous materials, particularly when they have limited Li insertion capacity along with a high surface area. This is exemplified by a carbon black, Ketjen Black (KB). An ionic conductivity of 18.1 mS cm-1 at room temperature is observed, far exceeding most solid-state ion conductors. Theoretical calculations reveal a low diffusion barrier for the surface Li species. The species is also identified as Li*, which features a partial positive charge. As a result, lithiated KB functions effectively as an interlayer between Li and solid-state electrolytes (SSE) to mitigate dendrite growth and cell shorting. This function is found to be electrolyte agnostic, effective for both sulfide and halide SSEs. Further, lithiated KB can act as a high-performance mixed ion/electron conductor that is thermodynamically stable at potentials near Li metal. A graphite anode mixed with KB instead of a solid electrolyte demonstrates full utilization with a capacity retention of ~85% over 300 cycles. The discovery of this surface-mediated ultra-fast Li-ion transport mechanism provides new directions for the design of solid-state ion conductors and solid-state batteries. Copyright © 2024, The Authors. All rights reserved.

关键词： Solid electrolytes

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