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141
Capturing the Transient Microstructure of a Physically Assembled Gel Subjected to Temperature and Large Deformation
Published 2021“…Here, we report the real-time change in the structure of physically assembled triblock copolymer gels that consist of 10 and 20 wt % of poly(styrene)–poly(isoprene)–poly(styrene) [PS–PI–PS] triblock copolymer in mineral oil (i) during the gelation process with decreasing temperature, (ii) subjected to large oscillatory deformation, and (iii) during the stress-relaxation process after the application of a step strain. …”
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142
Capturing the Transient Microstructure of a Physically Assembled Gel Subjected to Temperature and Large Deformation
Published 2021“…Here, we report the real-time change in the structure of physically assembled triblock copolymer gels that consist of 10 and 20 wt % of poly(styrene)–poly(isoprene)–poly(styrene) [PS–PI–PS] triblock copolymer in mineral oil (i) during the gelation process with decreasing temperature, (ii) subjected to large oscillatory deformation, and (iii) during the stress-relaxation process after the application of a step strain. …”
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143
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Triple B←N Lewis Pair-Functionalized Triazatruxenes with Large Stokes Shifts
Published 2023“…The introduction of B←N Lewis pairs not only results in a large decrease in the HOMO–LUMO gap but also lowers the LUMO to −3.00 eV. …”
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<b>Warming alters plankton body-size distributions in a large field experiment</b>
Published 2024“…We found a nonlinear decrease in the overall mean body size of zooplankton with warming, with a 57% reduction at +8°C. …”
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149
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Competitive Arsenate and Phosphate Adsorption on Ferrihydrite as Described by the CD-MUSIC Model
Published 2022“…The solubility and bioavailability of arsenic in the environment are to a large extent governed by adsorption reactions with iron (hydr)oxides, the extent of which is affected by competitive interactions with other ions, for example, phosphate. …”
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A novel RNN architecture to improve the precision of ship trajectory predictions
Published 2025“…However, this model can be time-consuming and can only represent a single vessel track. To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”
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