This study presents a smart guidewire developed to measure the pressure inside blood vessels during minimally invasive surgery. The use of pressure sensor guidewires enables the medical doctor to make a judgement of t...
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Low-carbon Nb/V microalloyed steels are extensively used for pipeline construction due to a good combination of mechanical properties and weldability. Austenite/ferrite transformation and grain size evolution during c...
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Volumetric muscle loss(VML)frequently results from traumatic incidents and can lead to severe functional *** have been widely employed for VML tissue regeneration,which are unfortunately ineffective because of the lac...
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Volumetric muscle loss(VML)frequently results from traumatic incidents and can lead to severe functional *** have been widely employed for VML tissue regeneration,which are unfortunately ineffective because of the lack of intimate contact with injured tissue for structural and mechanical *** hydrogels allow for strong tissue connections for wound ***,conventional adhesive hydrogels exhibit poor tissue adhesion in moist,bleeding wounds due to the hydration layer at the tissue–hydrogel interfaces,resulting in insufficient *** this study,we developed a novel,biocompatible,wet tissue adhesive powder hydrogel consisting of dextran-aldehyde(dex-ald)and gelatin for the regeneration of *** powder absorbs the interfacial tissue fluid and buffer solution on the tissue,spontaneously forms a hydrogel,and strongly adheres to the tissue via various molecular interactions,including the Schiff base *** particular,the powder composition with a 1:4 ratio of dex-ald to gelatin exhibited optimal characteristics with an appropriate gelation time(258 s),strong tissue adhesion(14.5 kPa),and ***-ald/gelatin powder hydrogels presented strong adhesion to various organs and excellent hemostasis compared to other wet hydrogels and fibrin glue.A mouse VML injury model revealed that the dex-ald/gelatin powder hydrogel significantly improved muscle regeneration,reduced fibrosis,enhanced vascularization,and decreased ***,our wet-adhesive powder hydrogel can serve as an effective platform for repairing various tissues,including the heart,muscle,and nerve tissues.
Using laser powder bed fusion additive manufacturing (L-PBF AM), a series of 10 sample walls were made, sectioned into fatigue specimens, and tested using high cycle fatigue (HCF) testing with a stress ratio of 0.1 at...
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Accurate and efficient prediction of polymer properties is of great significance in polymer ***,expensive and time-consuming experiments or simulations are required to evaluate polymer ***,Transformer models,equipped ...
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Accurate and efficient prediction of polymer properties is of great significance in polymer ***,expensive and time-consuming experiments or simulations are required to evaluate polymer ***,Transformer models,equipped with self-attention mechanisms,have exhibited superior performance in natural language ***,such methods have not been investigated in polymer ***,we report TransPolymer,a Transformer-based language model for polymer property *** proposed polymer tokenizer with chemical awareness enables learning representations from polymer *** experiments on ten polymer property prediction benchmarks demonstrate the superior performance of ***,we show that TransPolymer benefits from pretraining on large unlabeled dataset via Masked Language *** results further manifest the important role of self-attention in modeling polymer *** highlight this model as a promising computational tool for promoting rational polymer design and understanding structure-property relationships from a data science view.
The potential of ocean energy as a renewable source is widely acknowledged. Ocean currents energy is one of the ocean energies, which is harnessed by using hydrokinetic turbines (HKTs). Despite continuous efforts on t...
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Additive manufacturing(AM)of ceramic matrix composites(CMCs)has enabled the production of highly customized,geometrically complex and functionalized parts with significantly improved properties and functionality,compa...
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Additive manufacturing(AM)of ceramic matrix composites(CMCs)has enabled the production of highly customized,geometrically complex and functionalized parts with significantly improved properties and functionality,compared to single-phase ceramic *** also opens up a new way to shape damage-tolerant ceramic composites with co-continuous phase reinforcement inspired by natural ***,a large variety of AM techniques has been successfully applied to fabricate CMCs,but variable properties have been obtained so *** article provides a comprehensive review on the AM of ceramic matrix composites through a systematic evaluation of the capabilities and limitations of each AM technique,with an emphasis on reported results regarding the properties and potentials of AM man-ufactured ceramic matrix composites.
GH4169 joints manufactured by Linear Friction Welding(LFW)are subjected to tensile test and stair-case method to evaluate the High Cycle Fatigue(HCF)performance at 650℃.The yield and ultimate tensile strengths are 58...
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GH4169 joints manufactured by Linear Friction Welding(LFW)are subjected to tensile test and stair-case method to evaluate the High Cycle Fatigue(HCF)performance at 650℃.The yield and ultimate tensile strengths are 582 MPa and 820 MPa,*** HCF strength of joint reaches 400 MPa,which is slightly lower than that of Base Metal(BM),indicating reliable quality of this type of *** microstructure observation results show that all cracks initiate at the inside of specimens and transfer into deeper region with decrease of external stress,and the crack initiation site is related with microhardness of *** Electron Backscattered Diffraction(EBSD)results of the observed regions with different distances to fracture show that plastic deformation plays a key role in HCF,and the Schmid factor of most grains near fracture exceeds *** addition,the generation of twins plays a vital role in strain concentration release and coordinating plastic deformation among grains.
Machine learning is an emerging tool in the field of materials chemistry for uncovering a principle from large ***,we focus on the spherical precipitation behavior of polymers and computationally extract a hidden tren...
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Machine learning is an emerging tool in the field of materials chemistry for uncovering a principle from large ***,we focus on the spherical precipitation behavior of polymers and computationally extract a hidden trend that is orthogonal to the availability bias in the chemical *** constructing a dataset,four polymers were precipitated from 416 solvent/nonsolvent combinations,and the morphology of the resulting precipitates were *** dataset was subjected to computational investigations consisting of principal component analysis and machine learning based on random forest model and support vector ***,we eliminated the effect of the availability bias and found a linear combination of Hansen parameters to be the most suitable variable for predicting precipitation *** predicted appropriate solvents are those with low hydrogen bonding capability,low polarity,and small molecular ***,we found that the capability for spherical precipitation is orthogonal to the availability bias and forms an extraordinary axis in Hansen space,which is the origin of the conventional difficulty in identifying the *** extraordinary axis points toward a void region,indicating the potential value of synthesizing novel solvents located therein.
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