Search Results - "Le, Tu C"

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  1. 1

    Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery by Mai, Haoxin, Le, Tu C., Chen, Dehong, Winkler, David A., Caruso, Rachel A.

    Published in Chemical reviews (24-08-2022)
    “…Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to…”
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    Journal Article
  2. 2

    Discovery and Optimization of Materials Using Evolutionary Approaches by Le, Tu C, Winkler, David A

    Published in Chemical reviews (25-05-2016)
    “…Materials science is undergoing a revolution, generating valuable new materials such as flexible solar panels, biomaterials and printable tissues, new…”
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  3. 3

    Synthesis of Layered Lead-Free Perovskite Nanocrystals with Precise Size and Shape Control and Their Photocatalytic Activity by Mai, Haoxin, Li, Xuying, Lu, Junlin, Wen, Xiaoming, Le, Tu C., Russo, Salvy P., Chen, Dehong, Caruso, Rachel A.

    Published in Journal of the American Chemical Society (09-08-2023)
    “…Halide perovskites have attracted enormous attention due to their potential applications in optoelectronics and photocatalysis. However, concerns over their…”
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  4. 4

    Quantitative design rules for protein-resistant surface coatings using machine learning by Le, Tu C., Penna, Matthew, Winkler, David A., Yarovsky, Irene

    Published in Scientific reports (22-01-2019)
    “…Preventing biological contamination (biofouling) is key to successful development of novel surface and nanoparticle-based technologies in the manufacturing…”
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  5. 5

    Fabrication of Zein‐Based Fibrous Scaffolds for Biomedical Applications—A Review by Rahman, Mustafijur, Dip, Tanvir Mahady, Haase, Tina, Truong, Yen Bach, Le, Tu C., Houshyar, Shadi

    Published in Macromolecular materials and engineering (01-12-2023)
    “…Zein, which accounts for around 80% of the total protein composition in corn, is a biocompatible and biodegradable substance derived from renewable sources…”
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  6. 6

    Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy by Nguyen, Hoang T, Nguyen, Kate T Q, Le, Tu C, Zhang, Guomin

    Published in Molecules (Basel, Switzerland) (15-02-2021)
    “…The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial…”
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  7. 7

    Aqueous Solubility Prediction: Do Crystal Lattice Interactions Help? by Salahinejad, Maryam, Le, Tu C, Winkler, David A

    Published in Molecular pharmaceutics (01-07-2013)
    “…Aqueous solubility is a very important physical property of small molecule drugs and drug candidates but also one of the most difficult to predict accurately…”
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  8. 8

    Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture by Mai, Haoxin, Le, Tu C., Chen, Dehong, Winkler, David A., Caruso, Rachel A.

    Published in Advanced science (01-12-2022)
    “…Addressing climate change challenges by reducing greenhouse gas levels requires innovative adsorbent materials for clean energy applications. Recent progress…”
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  9. 9

    Accelerating the prediction of CO2 capture at low partial pressures in metal-organic frameworks using new machine learning descriptors by Orhan, Ibrahim B., Le, Tu C., Babarao, Ravichandar, Thornton, Aaron W.

    Published in Communications chemistry (03-10-2023)
    “…Metal-Organic frameworks (MOFs) have been considered for various gas storage and separation applications. Theoretically, there are an infinite number of MOFs…”
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  10. 10

    Use of metamodels for rapid discovery of narrow bandgap oxide photocatalysts by Mai, Haoxin, Le, Tu C., Hisatomi, Takashi, Chen, Dehong, Domen, Kazunari, Winkler, David A., Caruso, Rachel A.

    Published in iScience (24-09-2021)
    “…New photocatalysts are traditionally identified through trial-and-error methods. Machine learning has shown considerable promise for improving the efficiency…”
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  11. 11

    Quantum Chemistry–Machine Learning Approach for Predicting Properties of Lewis Acid–Lewis Base Adducts by Huynh, Hieu, Kelly, Thomas J., Vu, Linh, Hoang, Tung, Nguyen, Phuc An, Le, Tu C., Jarvis, Emily A., Phan, Hung

    Published in ACS omega (30-05-2023)
    “…Synthetic design allowing predictive control of charge transfer and other optoelectronic properties of Lewis acid adducts remains elusive. This challenge must…”
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  12. 12

    Toward Cell Membrane Biomimetic Lipidic Cubic Phases: A High-Throughput Exploration of Lipid Compositional Space by Sarkar, Sampa, Tran, Nhiem, Rashid, Md Harunur, Le, Tu C, Yarovsky, Irene, Conn, Charlotte E, Drummond, Calum J

    Published in ACS applied bio materials (22-01-2019)
    “…The bicontinuous lipidic cubic phase (LCP), which is based on the fundamental structure of the lipid bilayer, is increasingly used in a range of applications…”
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  13. 13

    Prediction of O 2 /N 2 Selectivity in Metal-Organic Frameworks via High-Throughput Computational Screening and Machine Learning by Orhan, Ibrahim B, Daglar, Hilal, Keskin, Seda, Le, Tu C, Babarao, Ravichandar

    Published in ACS applied materials & interfaces (12-01-2022)
    “…Machine learning (ML), which is becoming an increasingly popular tool in various scientific fields, also shows the potential to aid in the screening of…”
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  14. 14

    Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR by Winkler, David A., Le, Tu C.

    Published in Molecular informatics (01-01-2017)
    “…Neural networks have generated valuable Quantitative Structure‐Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and…”
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  16. 16

    Modeling the Influence of Fatty Acid Incorporation on Mesophase Formation in Amphiphilic Therapeutic Delivery Systems by Le, By Tu C, Tran, Nhiem, Mulet, Xavier, Winkler, David A

    Published in Molecular pharmaceutics (07-03-2016)
    “…Dispersed amphiphile-fatty acid systems are of great interest in drug delivery and gene therapies because of their potential for triggered release of their…”
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  17. 17

    Manipulating the Ordered Nanostructure of Self-Assembled Monoolein and Phytantriol Nanoparticles with Unsaturated Fatty Acids by Tran, Nhiem, Mulet, Xavier, Hawley, Adrian M, Fong, Celesta, Zhai, Jiali, Le, Tu C, Ratcliffe, Julian, Drummond, Calum J

    Published in Langmuir (27-02-2018)
    “…Mesophase structures of self-assembled lyotropic liquid crystalline nanoparticles are important factors that directly influence their ability to encapsulate…”
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  18. 18

    Janus particles: recent advances in the biomedical applications by Le, Tu C, Zhai, Jiali, Chiu, Wei-Hsun, Tran, Phong A, Tran, Nhiem

    Published in International journal of nanomedicine (01-08-2019)
    “…Janus particles, which are named after the two-faced Roman god Janus, have two distinct sides with different surface features, structures, and compositions…”
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  19. 19

    An Experimental and Computational Approach to the Development of ZnO Nanoparticles that are Safe by Design by Le, Tu C., Yin, Hong, Chen, Rui, Chen, Yandong, Zhao, Lin, Casey, Philip S., Chen, Chunying, Winkler, David A.

    “…Zinc oxide nanoparticles have found wide application due to their unique optoelectronic and photocatalytic characteristics. However, their safety aspects…”
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  20. 20

    Rational Atom Substitution to Obtain Efficient, Lead‐Free Photocatalytic Perovskites Assisted by Machine Learning and DFT Calculations by Li, Xuying, Mai, Haoxin, Lu, Junlin, Wen, Xiaoming, Le, Tu C., Russo, Salvy P., Winkler, David A., Chen, Dehong, Caruso, Rachel A.

    Published in Angewandte Chemie International Edition (21-12-2023)
    “…Inorganic lead‐free halide perovskites, devoid of toxic or rare elements, have garnered considerable attention as photocatalysts for pollution control, CO2…”
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