419 research outputs found
Molecular Mechanisms and Design of Hydrogen-Bonded Materials for Thermal Applications
Heat transfer at the nanoscale plays an important role in determining the reliability and performance of many innovative advanced materials technologies such as nanoelectronics, semiconductor, biomedical devices, polymers, and composites. Extensive efforts have been made to design materials with extraordinary thermal properties. However, fundamental understanding of heat transfer in many of these materials is still not lacking, because the thermal transport processes are governed by several factors including molecular morphology and chemical bonding. Among these factors, the atomic bonding between two dissimilar materials or within single materials is of particular interest due to its ubiquity and importance in physical processes. This work will focus on the demonstration and fundamental understanding of nanoscale thermal transport enhanced by incorporating hydrogen bonds in materials design.
Molecular dynamics is performed for studying heat transfer processes in two typical hydrogen-bonded materials: (1) protein secondary structures, and (2) electrode/electrolyte composites in lithium ion batteries. Theoretical calculation and analysis show that heat transfer can be tuned in a wide range by modifying the hydrogen bonds. Results will not only provide new physical insights, but will also guide the rational design of materials for desired thermal properties towards many applications
The Practice of Artificial Intelligence Technology in Mechanical Design and Manufacturing and its Automation
With the rapid development of science and technology, artificial intelligence technology has made remarkable achievements in all
walks of life. In the field of mechanical design and manufacturing, artificial intelligence not only brings disruptive changes to the traditional
manufacturing methods, but also provides new possibilities for automated production. This paper will deeply explore the practice of artificial
intelligence technology in mechanical design, manufacturing and its automation, in order to provide a useful reference for the future development of the industry
Electronic structures of organic molecule encapsulated BN nanotubes under transverse electric field
The electronic structures of boron nitride nanotubes (BNNTs) doped by
different organic molecules under a transverse electric field were investigated
via first-principles calculations. The external field reduces the energy gap of
BNNT, thus makes the molecular bands closer to the BNNT band edges and enhances
the charge transfers between BNNT and molecules. The effects of the electric
field direction on the band structure are negligible. The electric field
shielding effect of BNNT to the inside organic molecules is discussed. Organic
molecule doping strongly modifies the optical property of BNNT, and the
absorption edge is red-shifted under static transverse electric field.Comment: accepted by JC
A first principles study on organic molecules encapsulated BN nanotubes
The electronic structures of boron nitride nanotubes (BNNTs) doped by organic
molecules are investigated with density functional theory. Electrophilic
molecule introduces acceptor states in the wide gap of BNNT close to the
valence band edge, which makes the doped system a -type semiconductor.
However, with typical nucleophilic organic molecules encapsulation, only deep
occupied molecular states but no shallow donor states are observed. There is a
significant electron transfer from BNNT to electrophilic molecule, while the
charge transfer between nucleophilic molecule and BNNT is neglectable. When
both electrophilic and nucleophilic molecules are encapsulated in the same
BNNT, large charge transfer between the two kinds of molecules occurs. The
resulted small energy gap can strongly modify the transport and optical
properties of the system
Masked Vision and Language Pre-training with Unimodal and Multimodal Contrastive Losses for Medical Visual Question Answering
Medical visual question answering (VQA) is a challenging task that requires
answering clinical questions of a given medical image, by taking consider of
both visual and language information. However, due to the small scale of
training data for medical VQA, pre-training fine-tuning paradigms have been a
commonly used solution to improve model generalization performance. In this
paper, we present a novel self-supervised approach that learns unimodal and
multimodal feature representations of input images and text using medical image
caption datasets, by leveraging both unimodal and multimodal contrastive
losses, along with masked language modeling and image text matching as
pretraining objectives. The pre-trained model is then transferred to downstream
medical VQA tasks. The proposed approach achieves state-of-the-art (SOTA)
performance on three publicly available medical VQA datasets with significant
accuracy improvements of 2.2%, 14.7%, and 1.7% respectively. Besides, we
conduct a comprehensive analysis to validate the effectiveness of different
components of the approach and study different pre-training settings. Our codes
and models are available at https://github.com/pengfeiliHEU/MUMC.Comment: accepted by MICCAI202
Measurement report: The promotion of low-level jet and thermal-effect on development of deep convective boundary layer at the southern edge of the Taklimakan Desert
A vigorous development process of the deep convective boundary layer (CBL) was observed at the southern edge of the Taklimakan Desert on 6 June, 2022. Based on coherent Doppler wind lidar and ERA5 data, the formation mechanism of the deep CBL exceeding 5 km was well analyzed, which was mainly promoted by the low-level jet (LLJ) and thermal-effect. The LLJ has made sufficient momentum, energy and material preparations for the development of the deep CBL. Firstly, the cold downhill airflow of the Tibet Plateau leading to LLJ weakens the height and intensity of the temperature inversion layer, which reduces the energy demand for the broken of the IL. Secondly, the LLJ not only supplements the material and energy in the residual layer, but also suppresses the exchange with the lower atmosphere. In addition, the LLJ provides a driving force for the development of the deep CBL. In terms of thermal factors, the Tibet Plateau sensible heat driven air-pump and cold front transit provide additional impetus for the development of the deep CBL. Finally, the formation of deep CBL was catalyzed by the extreme thermal effects of the underlying surface, such as the furnace effect and the atmospheric superadiabatic expansion process. The study of the development of the deep CBL is important for revealing the land-air exchange process of momentum, energy, and material between the Taklimakan Desert and the Tibetan Plateau
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