CRC HANDBOOK of THERMOPHYSICAL and THERMOCHEMICAL DATA

Lide, David R.; Kehiaian, Henry V.

doi:10.1201/9781003067719

Cited by 378 publications

(498 citation statements)

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“…(10) to the configurations of zone A of Figure 17. The evaporation temperature of Mg is approximately 1090℃ [27]. Therefore, we note that the temperatures obtained in Table 4 enable the evaporation of the Mg of alloy AlSi7Mg0.6; this confirms the observation made by Mauduit et al [8] where they noted a loss of approximately 25% in the Mg mass after production.…”

Section: Thermal Analysis and Cooling Speedsupporting

confidence: 89%

Influence of the Manufacturing Parameters in Selective Laser Melting on Properties of Aluminum Alloy AlSi7Mg0.6 (A357)

Mauduit¹,

Gransac²,

Pillot³

2021

ACSM

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Various selective laser melting (SLM) configurations (8 in all) were tested on aluminum alloy AlSi7Mg0.6 by making single tracks on parallelepipeds specimens. We used an energy balance as a means of connecting the machine parameters (power, speed, etc.) of the 8 configurations to the morphology (geometry) of the single tracks. On this basis, we correlated the width, depth and especially the section area of the melt pool (single track) to the linear energy density. We were also able to assess the absorption coefficient of the aluminum alloy AlSi7Mg0.6 as a function of the temperature. The study was then focused on the microstructure and the possible impacts on the material properties including on the mechanical characteristics and the anisotropy observed in literature based on the build direction. Evidence suggests that the Hall-Petch relation can be used to explain this anisotropy. The thermal analysis highlighted two laser operating modes: the keyhole mode and the conduction mode. These modes have also been described via the morphology of the single tracks. Finally, a comparison between Rosenthal’s theoretical model (in the case of the conduction mode) and actual conditions was proposed by the obtained geometry of the single tracks as well as the cooling speeds calculated and measured using the dendrite arm spacing (DAS). The maximum temperatures achieved were also assessed by Rosenthal’s theoretical model which made it possible to explain the evaporation of some chemical elements during the manufacturing of the aluminum alloy through SLM.

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Section: Thermal Analysis and Cooling Speedsupporting

confidence: 89%

Influence of the Manufacturing Parameters in Selective Laser Melting on Properties of Aluminum Alloy AlSi7Mg0.6 (A357)

Mauduit¹,

Gransac²,

Pillot³

2021

ACSM

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“…28 Our calculated results show that the lattice constant is 3.92 Å for the bulk Pd, which is in good agreement with the experimental value of 3.89 Å. 29 A mesh of 2 × 2 × 1 Monkhorst–Pack special k-point grid was used for the integrations of the Brillouin zone. The electron wave functions were expanded by a plane-wave basis set with a cut-off energy of 400 eV.…”

Section: Computational Detailssupporting

confidence: 77%

Theoretical study of the oxidation of formic acid on a PtPd(111) surface

Wang

2019

Progress in Reaction Kinetics and Mechanism

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By performing density functional theory calculations, the adsorption configurations of formic acid and possible reaction pathway for HCOOH oxidation on PtPd(111) surface are located. Results show that CO 2 is preferentially formed as the main product of the catalytic oxidation of formic acid. The formation of CO on the pure Pd surface could not possibly occur during formic acid decomposition on the PtPd(111) surface owing to the high reaction barrier. Therefore, no poisoning of catalyst would occur on the PtPd(111) surface. Our results indicate that the significantly increased catalytic activity of bimetallic PtPd catalyst towards HCOOH oxidation should be attributed to the reduction in poisoning by CO.

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“…The bar chart of mean AACs among different sets of peptides is given in Figure 2 . Amino acids are categorized into five groups by their chemical properties [ 30 ]. It is illustrated that the acidic amino acids of non-AMPs, including aspartic acid (D) and glutamic acid (E), are more than those of AMPs.…”

Section: Resultsmentioning

confidence: 99%

Identifying anti-coronavirus peptides by incorporating different negative datasets and imbalanced learning strategies

Pang

Wang

Jhong

et al. 2021

Briefings in Bioinformatics

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As the current worldwide outbreaks of the SARS-CoV-2, it is urgently needed to develop effective therapeutic agents for inhibiting the pathogens or treating the related diseases. Antimicrobial peptides (AMP) with functional activity against coronavirus could be a considerable solution, yet there is no research for identifying anti-coronavirus (anti-CoV) peptides with the computational approach. In this study, we first investigated the physiochemical and compositional properties of the collected anti-CoV peptides by comparing against three other negative sets: antivirus peptides without anti-CoV function (antivirus), regular AMP without antivirus functions (non-AVP) and peptides without antimicrobial functions (non-AMP). Then, we established classifiers for identifying anti-CoV peptides between different negative sets based on random forest. Imbalanced learning strategies were adopted due to the severe class-imbalance within the datasets. The geometric mean of the sensitivity and specificity (GMean) under the identification from antivirus, non-AVP and non-AMP reaches 83.07%, 85.51% and 98.82%, respectively. Then, to pursue identifying anti-CoV peptides from broad-spectrum peptides, we designed a double-stages classifier based on the collected datasets. In the first stage, the classifier characterizes AMPs from regular peptides. It achieves an area under the receiver operating curve (AUCROC) value of 97.31%. The second stage is to identify the anti-CoV peptides between the combined negatives of other AMPs. Here, the GMean of evaluation on the independent test set is 79.42%. The proposed approach is considered as an applicable scheme for assisting the development of novel anti-CoV peptides. The datasets and source codes used in this study are available at https://github.com/poncey/PreAntiCoV.

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CRC HANDBOOK of THERMOPHYSICAL and THERMOCHEMICAL DATA

Cited by 378 publications

References 0 publications

Influence of the Manufacturing Parameters in Selective Laser Melting on Properties of Aluminum Alloy AlSi7Mg0.6 (A357)

Influence of the Manufacturing Parameters in Selective Laser Melting on Properties of Aluminum Alloy AlSi7Mg0.6 (A357)

Theoretical study of the oxidation of formic acid on a PtPd(111) surface

Identifying anti-coronavirus peptides by incorporating different negative datasets and imbalanced learning strategies

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