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SSRN 2024年

作者： Shen, Long-Chen Liu, Yan Liu, Zi Zhang, Yumeng Wang, Zhikang Guo, Yuming Rossjohn, Jamie Song, Jiangning Yu, Dong-Jun School of Computer Science and Engineering Nanjing University of Science and Technology 200 Xiaolingwei Nanjing210094 China Department of Computer Science Yangzhou University Yangzhou225100 China School of Information Enginnering Jingdezhen Ceramic University Jingdezhen333403 China Monash Biomedicine Discovery Institute Department of Biochemistry and Molecular Biology Monash University MelbourneVIC3800 Australia Monash Data Futures Institute Monash University MelbourneVIC3800 Australia School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai200240 China Department of Epidemiology and Preventive Medicine Xiangya Hospital China Infection and Immunity Program Netherlands

Accurate prediction of major histocompatibility complex (MHC)-peptide binding affinity can improve our understanding of cellular immune responses and guide personalized immunotherapies. Nevertheless, the existing deep learning-based approaches for predicting MHC-II peptide interactions fall short of satisfactory performance and offer restricted model interpretability. In this study, we propose a novel deep neural network, termed ConBoTNet, to address the above issues by introducing the designed supervised contrastive learning and bottleneck transformer extractors. Specifically, the supervised contrastive learning pre-training enhances the model’s representative and generalizable capabilities on MHC-II peptides by pulling positive pairs closer and pushing negative pairs further in the feature space, while the bottleneck transformer module focuses on MHC-II peptide interactions to precisely identify binding cores and anchor positions in an unsupervised manner. Extensive experiments on benchmark datasets under 5-fold cross-validation, leave-one-molecule-out validation, independent testing, and binding core prediction settings highlighted the superiority of our proposed ConBoTNet over current state-of-the-art methods. Data distribution analysis in the latent feature space demonstrated that supervised contrastive learning can aggregate MHC-II-peptide samples with similar affinity labels and learn common features of similar affinity. Additionally, we interpreted the trained neural network by associating the attention weights with peptides and innovatively find both well-established and potential peptide motifs. This work not only introduces an innovative tool for accurately predicting MHC-II peptide affinity, but also provides new insights into a new paradigm for modeling essential biological interactions, advancing data-driven discovery in biomedicine. © 2024, The Authors. All rights reserved.

关键词： Peptides

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Levan Nanoparticles with Intrinsic Cd44-Targeting Ability for Tumor-Targeted Drug Delivery

SSRN

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SSRN 2022年

作者： Lee, Jin Sil Park, Eunyoung Oh, Hyeryeon Choi, Won Il Koo, Heebeom Center for Bio-Healthcare Materials Bio-Convergence Materials R&D Division Korea Institute of Ceramic Engineering and Technology 202 Osongsaengmyeong 1-ro Osong-eup Heungdeok-gu Chungbuk Cheongju28160 Korea Republic of School of Materials Science and Engineering Gwangju Institute of Science and Technology Cheomdan-gwagiro 123 Buk-gu Gwangju61005 Korea Republic of Department of Medical Life Sciences Department of Biomedicine & Health Sciences Catholic Photomedicine Research Institute College of Medicine The Catholic University of Korea 222 Banpo-daero Seocho-gu Seoul06591 Korea Republic of

The major limitations of existing anticancer therapeutics include short half-life, non-specificity, and severe side effects. To address these limitations, many nanoparticles with active targeting ability have been developed;however, obtaining FDA approval has been difficult due to the complicated fabrication procedures, low reproducibility, and hard mass production, particularly during functionalization of nanoparticles with targeting moieties. In this study, we developed levan nanoparticles by a simple one-pot nanoprecipitation for specific delivery of anticancer drugs. Levan, a polysaccharide from plants, has an intrinsic binding affinity to CD44 receptors on cancer cells and amphiphilicity. Therefore, the resulting nanoparticle is based on self-assembly and has an active targeting ability without any chemical modification. The paclitaxel-loaded levan nanoparticle (PTX@LevNP) showed a monodispersed size with spherical morphology in an aqueous condition. It demonstrated a sustained release of PTX and long-term stability over 4 weeks in physiological conditions. Remarkably, the competitive inhibition effect with hyaluronic acid showed that LevNP could significantly bind CD44 receptors on cancer cells. The anticancer activity of PTX@LevNP was highly improved in CD44-positive cells (SCC7 cells) compared to CD44-negative cells (NIH3T3 cells). In SCC7 tumor-bearing mice, the LevNP could deliver the anticancer drugs to tumor tissue about 3.7 times higher than that of free drugs, resulting in improved anticancer therapeutic efficacy. This new strategy holds great potential to produce nanoparticles for clinical trials for the effective treatment of CD44-overexpressing cancers without complicated fabrication procedures. © 2022, The Authors. All rights reserved.

关键词： Diseases

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Iron carbonyl polymer microspheres for simultaneously high-speed adsorption and desorption of dye-emulsified micelles with frequency manipulation under an alternating electric field

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Chemical engineering Journal 2023年 469卷

作者： Wang, Yu-Xiang Chang, Chi-Jung Lu, Chien-Hsing Chen, Jem-Kun Department of Materials Science and Engineering Taiwan Building Technology Center National Taiwan University of Science and Technology 43 Sec. 4 Keelung Road Taipei10607 Taiwan Department of Chemical Engineering Feng Chia University 100 Wenhwa Road Seatwen Taichung40724 Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung Taiwan Institute of Biomedical Sciences Ph.D. Program in Translational Medicine and Rong-Hsing Research Center for Translational Medicine National Chung-Hsing University Taichung940227 Taiwan

Developing a versatile methodology for high-speed water purification is critical for environmental and water source protection. Traditional adsorption and desorption were determined based on the concentration gradients. Herein, a versatile methodology is reported based on the simple application of an alternating electric field (AEF) on a system including dye-emulsified micelles (DEM) and adsorbents that simultaneously exhibit high-speed adsorption and desorption of DEM by frequency manipulation. Iron carbonyl polymers are incorporated into polystyrene microspheres (PMs) to generate iron carbonyl polystyrene microspheres (ICPMs) as adsorbents, which can vary the affinity with DEM and dielectric properties simultaneously. Both the DEM and microspheres were polarized under the AEF and generated electric dipole moments that could rapidly assemble the DEM and microspheres. Compared with the adsorption through the concentration gradient, the adsorption rate of DEM was enhanced significantly in the presence of an AEF of 20 V at 150 kHz of frequency because of the effect of particle assembly. At 1000 kHz of frequency, the alternative high-speed change between electrostatic attraction and repulsion hindered the adsorption of the dyes, which could also enhance the desorption rate. The ICPMs could be recycled 10 times within 20 min with frequency manipulation in the presence of AEF. This versatile methodology could provide novel insights into the development of high-speed water purification techniques. © 2023 Elsevier B.V.

关键词： Polystyrenes

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Room-temperature surface multiferroicity in Y2NiMnO6 nanorods

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Physical Review B 2022年第23期105卷 235429-235429页

作者： Shubhankar Mishra Amritendu Roy Aditi Sahoo Biswarup Satpati Anirban Roychowdhury P. K. Mohanty Chandan Kumar Ghosh Dipten Bhattacharya School of Materials Science and Nanotechnology Jadavpur University Kolkata 700032 India School of Minerals Metallurgical and Materials Engineering Indian Institute of Technology Bhubaneswar 752050 India Advanced Materials and Chemical Characterization Division CSIR–Central Glass and Ceramic Research Institute Kolkata 700032 India Saha Institute of Nuclear Physics A CI of Homi Bhabha National Institute 1/AF Salt Lake Kolkata 700064 India Department of Physics Krishnath College Berhampore 742101 West Bengal India Department of Physical Sciences IISER Kolkata Mohanpur West Bengal 741246 India

We report observation of surface-defect-induced room-temperature multiferroicity—surface ferromagnetism (MS at 50 kOe ≈0.005 emu/g), ferroelectricity (PR≈2nC/cm2), and significantly large magnetoelectric coupling (decrease in PR by ≈80% under ≈15 kOe field)—in nanorods (diameter ≈100 nm) of double perovskite Y2NiMnO6 compound. In bulk form, this system exhibits multiferroicity only below its magnetic transition temperature TN≈ 70 K. On the other hand, the oxygen vacancies, formed at the surface region (thickness ≈10 nm) of the nanorods, yield long-range magnetic order as well as ferroelectricity via Dzyloshinskii-Moriya exchange coupling interactions with strong Rashba spin-orbit coupling. Sharp drop in PR under magnetic field indicates strong cross coupling between magnetism and ferroelectricity as well. Observation of room-temperature magnetoelectric coupling in nanoscale for a compound which, in bulk form, exhibits multiferroicity only below 70 K underscores an alternative pathway for inducing magnetoelectric multiferroicity via surface defects and, thus, in line with magnetoelectric property observed, for example, in domain walls or boundaries or interfaces of heteroepitaxially grown thin films which do not exhibit such features in their bulk.

关键词： Surface & interfacial phenomena Ferroelectrics Multiferroics Nanorods Magnetic force microscopy Monte Carlo methods

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Meta-optic Accelerators for Object Classifiers

arXiv

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arXiv 2022年

作者： Zheng, Hanyu Liu, Quan Zhou, You Kravchenko, Ivan I. Huo, Yuankai Valentine, Jason Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37212 United States Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37212 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37212 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision making when computation resources are limited. Here, we demonstrate a meta-optic based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems resulting in a robust classifier that achieves 95% accurate classification of handwriting digits and 94% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine-vision and artificial intelligence. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy utilization

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Addressing challenges for operating electrochemical solar fuels technologies under variable and diurnal conditions

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Frontiers in Energy Research 2024年 12卷

作者： Yap, Kyra M. K. Lee, Sol A. Kistler, Tobias A. Collins, Darci K. Warren, Emily L. Atwater, Harry A. Jaramillo, Thomas F. Xiang, Chengxiang Nielander, Adam C. Department of Chemical Engineering Stanford University StanfordCA United States SUNCAT Center for Interface Science and Catalysis SLAC National Accelerator Laboratory Menlo ParkCA United States Department of Applied Physics and Materials Science California Institute of Technology PasadenaCA United States Chemical Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA United States Chemistry and Nanoscience Center National Renewable Energy Laboratory GoldenCO United States Advanced Energy Systems Graduate Program Colorado School of Mines GoldenCO United States

The outdoor operation of electrochemical solar fuels devices must contend with challenges presented by the cycles of solar irradiance, temperature, and other meteorological factors. Herein, we discuss challenges associated with these fluctuations presented over three timescales, including the effects of diurnal cycling over the course of many days, a single diurnal cycle over the course of hours, and meteorological phenomena that cause fluctuations on the order of seconds to minutes. We also highlight both reaction-independent and reaction-specific effects of variable conditions for the hydrogen evolution reaction and CO2 reduction reaction. We identify key areas of research for advancing the outdoor operation of solar fuels technology and highlight the need for metrics and benchmarks to enable the comparison of diurnal studies across systems and geographical locations. Copyright © 2024 Yap, Lee, Kistler, Collins, Warren, Atwater, Jaramillo, Xiang and Nielander.

关键词： Hydrogen fuels

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Photoluminescence of oxygen vacancy-rich nano-TiO2 photocatalyst for methylene blue color degradation

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materials science and engineering: B 2025年 320卷

作者： Simanjuntak, Mayer Made Joni, I. Faizal, Ferry Gultom, Noto Susanto Kuo, Dong-Hau Panatarani, Camellia Department of Physics Faculty of Mathematic and Natural Sciences Universitas Padjadjaran Jl. Raya Bandung-Sumedang KM 21 Jatinangor Sumedang45363 Indonesia Study Program of Biotechnology Faculty of Graduate School Universitas Padjadjaran Jl. Dipati Ukur No.35 Coblong Bandung40132 Indonesia Functional Nano Powder University Center of Excellence Universitas Padjadjaran Jl. Raya Bandung-Sumedang KM 21 Jatinangor Sumedang45363 Indonesia Department of Materials Science and Engineering National Taiwan University of Science and Technology No.43 Sec. 4 Keelung Road Taipei10607 Taiwan

Wastewater containing synthetic dyes poses a critical environmental hazard, necessitating the development of effective treatment techniques. Despite its promise as a photocatalyst, TiO2′s inability to efficiently absorb visible light limits its practical use. To overcome this limitation, oxygen vacancy (OV) engineering was carried out in TiO2 through solvothermal at temperatures of 150°C, 180°C, and 210°C. Comprehensive analyses confirmed a temperature-induced increase in crystallinity and OV concentration. Furthermore, photoluminescence analysis revealed mid-gap states that improve visible light absorption. Notably, the T150 sample achieved 93.43% degradation of methylene blue within 3 h under sunlight, outperforming commercial TiO2. The superior performance was attributed to a reduced bandgap energy, enhanced charge carrier separation, and increased generation of reactive oxygen species, all facilitated by an optimal concentration of OV. This study clarifies the interaction between photoluminescence and photocatalytic activity, highlighting OV engineering as a highly effective strategy for developing advanced TiO2-based materials for wastewater treatment. © 2025 Elsevier B.V.

关键词： Photocatalytic activity

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Diamine Surface Passivation and Post-Annealing Enhance Performance of Silicon-Perovskite Tandem Solar Cells

arXiv

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arXiv 2024年

作者： Taddei, Margherita Contreras, Hannah Doan, Hai-Nam McCarthy, Declan P. Seo, Seongrok Westbrook, Robert J.E. Graham, Daniel J. Datta, Kunal Carroy, Perrine Muñoz, Delfina Correa-Baena, Juan-Pablo Barlow, Stephen Marder, Seth R. Smith, Joel A. Snaith, Henry J. Ginger, David S. Department of Chemistry University of Washington SeattleWA98195 United States Department of Physics University of Oxford OxfordOX1 3PU United Kingdom Institute of Materials Science Technical University of Munich München85748 Germany Department of Chemistry University of Colorado-Boulder BoulderCO80309 United States Department of Bioengineering University of Washington SeattleWA98195 United States School of Materials Science and Engineering Georgia Institute of Technology North Ave NW AtlantaGA30332 United States Université Grenoble Alpes CEA Liten Campus Ines Le Bourget du Lac73375 France Renewable and Sustainable Energy Institute University of Colorado-Boulder BoulderCO80309 United States Department of Chemical and Biological Engineering and Materials Science Program University of Colorado-Boulder BoulderCO80309 United States Physical Sciences Division Physical and Computational Sciences Directorate Pacific Northwest National Laboratory RichlandWA99352 United States

We show that the use of 1,3-diaminopropane (DAP) as a chemical modifier at the perovskite/electron-transport layer (ETL) interface enhances the power conversion efficiency (PCE) of 1.7 eV bandgap FACs mixed-halide perovskite single-junction cells, primarily by boosting the open-circuit voltage (VOC) from 1.06 V to 1.15 V. Adding a post-processing annealing step after C60 evaporation, further improves the fill factor (FF) by 20% from the control to the DAP + post-annealing devices. Using hyperspectral photoluminescence microscopy, we demonstrate that annealing helps improve compositional homogeneity at the top and bottom interfaces of the solar cell, which prevents detrimental bandgap pinning in the devices and improves C60 adhesion. Using time-of-flight secondary ion mass spectrometry, we show that DAP reacts with formamidinium present near the surface of the perovskite lattice to form a larger molecular cation, 1,4,5,6-tetrahydropyrimidinium (THP) that remains at the interface. Combining the use of DAP and the annealing of C60 interface, we fabricate Si-perovskite tandems with PCE of 25.29%, compared to 23.26% for control devices. Our study underscores the critical role of chemical reactivity and thermal post-processing of the C60/Lewis-base passivator interface in minimizing device losses and advancing solar-cell performance of wide-bandgap mixed-cation mixed-halide perovskite for tandem application. © 2024, CC BY.

关键词： Perovskite

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Pioneering bone regeneration: A review of cutting-edge scaffolds in tissue engineering

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Bioprinting 2024年 43卷

作者： Alex, Y. Vincent, Sumi Divakaran, Nidhin Uthappa, U.T. Srinivasan, Parthasarathy Mubarak, Suhail Al-Harthi, Mamdouh Ahmed Dhamodharan, Duraisami School for Advanced Research in Petrochemicals: Laboratory for Advanced Research in Polymeric Materials (LARPM) Central Institute of Petrochemicals Engineering and Technology (CIPET) Bhubaneswar 751024 India Mechanical Engineering Program Physical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Mechanics of Composites for Energy and Mobility Laboratory King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia College of Chemistry and Environmental Engineering Shenzhen University Shenzhen 518055 China Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Tamil Nadu Chennai 601103 India Research Institute of Humanities and Social Sciences University of Sharjah Sharjah 27272 United Arab Emirates Interdisciplinary Research Center for Refining and Advanced Chemicals King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Department of Chemical Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

Bone tissue engineering (BTE) is aims to develop advanced strategies to regenerate damaged or diseased bone, through the integration of principles from cellular biology, biomaterials science, and engineering. The vital aspect of these studies includes the design and fabrication of scaffolds that support cell adhesion, proliferation, and differentiation, ultimately promoting the formation of new bone tissue. Recent developments in scaffold materials have focused on organic, inorganic, and composite biomaterials. Each of these showcasing unique and distinct advantages in terms of biocompatibility, biodegradability, and mechanical strength. Polymers, such as poly (lactic-co-glycolic acid) (PLGA), provide flexibility and degradation profiles, which are conducive to tissue integration. While ceramics, including hydroxyapatite (HA) and β-tricalcium phosphate (β-TCP), offer mechanical properties similar to native bone. The fusion of organic and inorganic components in composites has yielded scaffolds with enhanced functionality, such as improved osteo-conductivity and controlled degradation rates. Advanced fabrication techniques, particularly electrospinning and 3D printing, have revolutionized scaffold design by enabling precise control over pore size, porosity, and surface architecture, critical parameters for mimicking the extracellular matrix (ECM) of bone. These structural characteristics directly influence cellular behaviors such as migration, proliferation, and differentiation, which are crucial for successful bone regeneration. This review critically evaluates the recent advances in biomaterials for scaffold fabrication, with a focus on optimizing the interplay between material properties and scaffold architecture to improve therapeutic outcomes in bone regeneration. The findings underscore the importance of material selection and scaffold design in BTE and provide actionable insights for both researchers and clinicians in the development of next-generation scaffol

关键词： Biomaterials Bone scaffold design Ideal scaffold Polymer Scaffold Tissue engineering

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Emulating Complex Synapses Using Interlinked Proton Conductors

arXiv

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arXiv 2024年

作者： Zhang, Lifu Li, Ji-An Hu, Yang Jiang, Jie Lai, Rongjie Benna, Marcus K. Shi, Jian Department of Materials Science and Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Neurosciences Graduate Program University of California San Diego La Jolla CA92093 United States Department of Mathematics Purdue University West LafayetteIN47907 United States Department of Neurobiology School of Biological Sciences University of California at San Diego La Jolla CA92093 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States

In terms of energy efficiency and computational speed, neuromorphic electronics based on non-volatile memory devices is expected to be one of most promising hardware candidates for future artificial intelligence (AI). However, catastrophic forgetting, networks rapidly overwriting previously learned weights when learning new tasks, remains as a pivotal hurdle in either digital or analog AI chips for unleashing the true power of brain-like computing. To address catastrophic forgetting in the context of online memory storage, a complex synapse model (the Benna-Fusi model) has been proposed recently[1], whose synaptic weight and internal variables evolve following a diffusion dynamics. In this work, by designing a proton transistor with a series of charge-diffusion-controlled storage components, we have experimentally realized the Benna-Fusi artificial complex synapse. The memory consolidation from coupled storage components is revealed by both numerical simulations and experimental observations. Different memory timescales for the complex synapse are engineered by the diffusion length of charge carriers, the capacity and number of coupled storage components. The advantage of the demonstrated complex synapse in both memory capacity and memory consolidation is revealed by neural network simulations of face familiarity detection. Our experimental realization of the complex synapse suggests a promising approach to enhance memory capacity and to enable continual learning. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational efficiency

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