Enabling Low-dose Liquid-phase TEM with Advanced Signal Processing, Machine Learning, and Molecular Simulation

Smith, John W.; Chen, Qian

doi:10.1017/s1431927621004906

Cited by 7 publications

(12 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When speaking, the vocal organ will produce a certain inertial movement. Within a period of time (generally 10 ms ∼ 30 ms), the speech signal can be regarded as approximately unchanged, so this speech signal can be treated as a stable signal [17,18].…”

Section: Speech Recognition Function Designmentioning

confidence: 99%

Design of Intelligent Speech Translation System Based on Deep Learning

Tan

2022

Mobile Information Systems

View full text Add to dashboard Cite

In order to solve the problem of low translation accuracy caused by complex sentence parameters in traditional machine translation systems, a method based on deep learning was proposed. First, MCU SPCE061A is used to study the problem of complex digital signal. The training data in the synchronous translation server support the translation services of a large number of users, and the translation results were displayed through the session interface of the user terminal. The PMDL model is used to detect the keyword signal, record the PCM audio data, and slice the collected pulse code modulation signal, so as to wake up the artificial intelligence voice service. Then, this study establishes a speech recognition process that accurately outputs the speech-related semantics. In this paper, a manual interactive synchronous translation program is designed with the input text as the search criterion, and the set is trimmed to obtain the best translation effect. The experimental results show that the sentence translation accuracy of the system is 0.9 ∼ 1.0. It is proved that the method based on deep learning solves the problem of low accuracy of the traditional translation system.

show abstract

Section: Speech Recognition Function Designmentioning

confidence: 99%

Design of Intelligent Speech Translation System Based on Deep Learning

Tan

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…Although these studies have achieved remarkable advances, there are still several challenges (Figure 10). [165][166][167][168][169][170][171][172][173] The electron beam effect is a primary challenge. A high electron beam dose rate changes the solution chemistry and produces positive charges on the SiN x surface.…”

Section: Summary Challenges and Future Opportunitiesmentioning

confidence: 99%

Section: Co 2 Electrochemical Reduction (Co 2 Rr)mentioning

confidence: 99%

“…[175] The low-dose-optimized TEM technique also reduces the accumulated electron dose and optimizes the imaging conditions. [170,176] Hence, the electron beam effect's detection, modeling, and quantification should be pursued in future works. [177] Another primary challenge is high spatial, temporal, and energy resolution.…”

Section: Summary Challenges and Future Opportunitiesmentioning

confidence: 99%

“…The Artificial intelligence-enabled approach performs autonomous and objective data analysis for in situ liquid phase TEM. [30,170,[205][206][207] In a word, in situ liquid phase TEM with advanced multifunctional liquid cells, comprehensive detectors, and spectroscopic techniques, among others, provided multiangle insights on growth and reaction mechanisms of metal oxide nanostructures for material science and energy conversion.…”

Section: Summary Challenges and Future Opportunitiesmentioning

confidence: 99%

See 2 more Smart Citations

Observing the Evolution of Metal Oxides in Liquids

Kang,

Zhang,

Guo

et al. 2023

Small

View full text Add to dashboard Cite

Metal oxides with diverse compositions and structures have garnered considerable interest from researchers in various reactions, which benefits from transmission electron microscopy (TEM) in determining their morphologies, phase, structural and chemical information. Recent breakthroughs have made liquid‐phase TEM a promising imaging platform for tracking the dynamic structure, morphology, and composition evolution of metal oxides in solution under work conditions. Herein, this review introduces the recent advances in liquid cells, especially closed liquid cell chips. Subsequently, the recent progress including particle growth, phase transformation, self‐assembly, core–shell nanostructure growth, and chemical etching are introduced. With the late technical advances in TEM and liquid cells, liquid‐phase TEM is used to characterize many fundamental processes of metal oxides for CO2 reduction and water‐splitting reactions. Finally, the outlook and challenges in this research field are discussed. It is believed this compilation inspires and stimulates more efforts in developing and utilizing in situ liquid‐phase TEM for metal oxides at the atomic scale for different applications.

show abstract

In-situ liquid-phase transmission electron microscopy for two-dimensional energy materials

Zhang,

Xiao,

2024

Sci. China Chem.

View full text Add to dashboard Cite

Enabling Low-dose Liquid-phase TEM with Advanced Signal Processing, Machine Learning, and Molecular Simulation

Cited by 7 publications

References 6 publications

Design of Intelligent Speech Translation System Based on Deep Learning

Design of Intelligent Speech Translation System Based on Deep Learning

Observing the Evolution of Metal Oxides in Liquids

In-situ liquid-phase transmission electron microscopy for two-dimensional energy materials

Contact Info

Product

Resources

About