Light-driven molecular motors may be useful for nanotechnology applications. The possibility of building such a motor based on the tolane framework is explored here. In the ground electronic state of tolane, the barrier to internal rotation is comparable to room temperature thermal energies, k(B)T. The barrier increases substantially in the excited state, causing the molecule to planarize after absorption of a photon. This tendency to planarize may be converted into unidirectional rotational motion by placing chiral substituents on the phenyl rings. A potential advantage of this class of motors is that they may undergo rapid, nanosecond scale rotation. Computational design of appropriate substituents was done using semiempirical quantum chemical methods, SAM1 for the ground electronic state coupled to INDO for the excitation energy. The torsional surfaces of the best candidate were then generated using ab initio DFT methods, which confirm that the molecule should undergo unidirectional rotation upon photoexcitation. The results provide a proof of principle for this class of motors; however, two aspects of the final candidate are nonideal. First, although the design goal was to use steric interactions between substituents to induce the rotation, decomposition of the interaction energy suggests attractive interactions play a role. Solvent interactions may interfere with these attractive interactions. Second, TDDFT calculations suggest that interactions between excited states lower the rotational driving force in the excited state.
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J Med Internet Res
January 2025
School of Business, Innovation and Sustainability, Halmstad University, Halmstad, Sweden.
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Department of Computer Science, Khalifa University, Abu Dhabi, UAE.
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Management School, Harbin University of Commerce, Harbin, Heilongjiang, China.
Road traffic congestion on the cold chain logistics not only increase the cost and time, but also creates certain negative impact on the national carbon emissions. To fully utilize the traffic resources, this study has classified urban road traffic congestion and defined the various vehicle delivery speeds with dynamic congestion levels. Simultaneously, it has developed the cold chain products replenishment strategy by considering delivery route, multi-depot condition and even vehicle types, aiming to minimize the total cost and carbon emissions, and maximizing the cold chain products freshness.
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Robotics and Internet-of-Things Laboratory, Prince Sultan University, Riyadh, Saudi Arabia.
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