Predicting cost-effective carbon fiber precursors: Unraveling the functionalities of oxygen and nitrogen-containing groups during carbonization from ReaxFF simulations

Mao, Qian; Rajabpour, Siavash; Kowalik, Małgorzata; Duin, Adri C. T. van

doi:10.1016/j.carbon.2019.12.008

Cited by 63 publications

(38 citation statements)

References 75 publications

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“…This choice is justified by the technological importance of graphitizable carbon in catalytic, sensing, and electrochemical applications, as well as the expectation that carbonaceous materials exhibit a rich and only partially explored phase diagram in this low-density régime. This is justified by the wide variety of experimental results and the number of experimental phases discovered but still only partially unveiled. ,,,,,,,,− ,,,,,,,, …”

Section: Methodsmentioning

confidence: 99%

Diverse Phases of Carbonaceous Materials from Stochastic Simulations

et al. 2021

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Amorphous carbon systems are emerging to have unparalleled properties at multiple length scales, making them the preferred choice for creating advanced materials in many sectors, but the lack of long-range order makes it difficult to establish structure/property relationships. We propose an original computational approach to predict the morphology of carbonaceous materials for arbitrary densities that we apply here to graphitic phases at low densities from 1.15 to 0.16 g/cm3, including glassy carbon. This approach, dynamic reactive massaging of the potential energy surface (DynReaxMas), uses the ReaxFF reactive force field in a simulation protocol that combines potential energy surface (PES) transformations with global optimization within a multidescriptor representation. DynReaxMas enables the simulation of materials synthesis at temperatures close to experiment to correctly capture the interplay of activated vs entropic processes and the resulting phase morphology. We then show that DynReaxMas efficiently and semiautomatically produces atomistic configurations that span wide relevant regions of the PES at modest computational costs. Indeed, we find a variety of distinct phases at the same density, and we illustrate the evolution of competing phases as a function of density ranging from uniform vs bimodal distributions of pore sizes at higher and intermediate density (1.15 g/cm3 and 0.50 g/cm3) to agglomerated vs sparse morphologies, further partitioned into boxed vs hollow fibrillar morphologies, at lower density (0.16 g/cm3). Our observations of diverse phases at the same density agree with experiment. Some of our identified phases provide descriptors consistent with available experimental data on local density, pore sizes, and HRTEM images, showing that DynReaxMas provides a systematic classification of the complex field of amorphous carbonaceous materials that can provide 3D structures to interpret experimental observations.

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Section: Methodsmentioning

confidence: 99%

Diverse Phases of Carbonaceous Materials from Stochastic Simulations

et al. 2021

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“…In particular, HHVs higher than 18 MJ Kg −1 were obtained for mixtures with the incorporation of Lc from 0% to 50% at the temperatures of 275 • C and 300 • C. Similar conclusions were drawn by Chen et al [22] for biochars produced from sawdust, wheat straw, pine, and microalgae. In general, the biochars with better fuel properties were those subjected to a torrefaction process at temperatures above 275 • C and residence time above 45 min, which shows that nitro-gen elimination and deoxygenation reactions played a major effect on the biochar final properties [50].…”

Section: Biocharsmentioning

confidence: 94%

Optimization of Biochar Production by Co-Torrefaction of Microalgae and Lignocellulosic Biomass Using Response Surface Methodology

Viegas

Nobre²,

Correia

et al. 2021

Energies

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Co-torrefaction of microalgae and lignocellulosic biomass was evaluated as a method to process microalgae sludge produced from various effluents and to obtain biochars with suitable properties for energy or material valorization. The influence of four independent variables on biochar yield and properties was evaluated by a set of experiments defined by response surface methodology (RSM). The biochars were characterized for proximate and ultimate composition, HHV, and methylene blue adsorption capacity. HHV of the biochars was positively correlated with carbonization temperature, residence time, and lignocellulosic biomass content in the feed. Co-torrefaction conditions that led to a higher yield of biochar (76.5%) with good calorific value (17.4 MJ Kg−1) were 250 °C, 60 min of residence time, 5% feed moisture, and 50% lignocellulosic biomass. The energy efficiency of the process was higher for lower temperatures (92.6%) but decreased abruptly with the increase of the moisture content of the feed mixture (16.9 to 57.3% for 70% moisture). Biochars produced using algal biomass grown in contaminated effluents presented high ash content and low calorific value. Dye removal efficiency by the produced biochars was tested, reaching 95% methylene blue adsorption capacity for the biochars produced with the least severe torrefaction conditions.

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“…The mechanical properties of CNFs with and without the graphitic skin layer are investigated in this study using large-scale molecular dynamics (MD) simulations. This computational technique has been successfully applied to analysis of chemical reactions leading to the formation of carbon fiber microstructure from molecular precursors [25][26][27][28][29][30][31][32], oxidation of carbon fibers [33], as well as the elementary processes involved in mechanical deformation of carbon fibers [27,28,[34][35][36][37]. The high computational cost of MD simulations, however, prevents application of this technique for direct evaluation of the mechanical properties of fibers with heterogeneous microstructure, such as the ones of core-skin carbon fibers.…”

Section: Generation Of the Model Carbon Nanofibersmentioning

confidence: 99%

“…The tensile testing simulations are performed with a more computationally expensive [43] ReaxFF interatomic potential [29,44,45], which provides a more realistic, as compared to the AIREBO-M potential, description of the bond rearrangement and scission during the irreversible (plastic) deformation and fracture (see Supplementary Information for additional discussion of problems preventing the use of AIREBO-M in the simulations of fracture of carbon nanofibers). The ReaxFF force field used in this paper is parameterized for C/H/O/N chemistry [29] and has been successfully applied to simulation of different steps in the carbon fiber formation [28][29][30][31].…”

Section: Generation Of the Model Carbon Nanofibersmentioning

confidence: 99%

Computational study of the effect of core–skin structure on the mechanical properties of carbon nanofibers

Joshi

Zhigilei

2021

J Mater Sci

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The effect of the core-skin structure on the mechanical properties of carbon nanofibers is investigated in large-scale molecular dynamics simulations of tensile deformation of carbon nanofibers with the core-skin and homogeneous structures. Contrary to an established notion of the deleterious effect of the skin layer on the strength of carbon fibers, the presence of a high-quality skin layer is found to increase both the Young's modulus and tensile strength of the nanofiber. A detailed analysis of the fracture process indicates that the nanofiber strengthening is related to the ability of skin layer to suppress crack nucleation at the core-skin interface. The computational predictions suggest that the design of new approaches to carbon fiber manufacturing and processing leading to the generation of a high-quality skin layer while avoiding the introduction of structural defects at the core-skin interface may yield a significant enhancement of the mechanical properties of carbon fibers.

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Predicting cost-effective carbon fiber precursors: Unraveling the functionalities of oxygen and nitrogen-containing groups during carbonization from ReaxFF simulations

Cited by 63 publications

References 75 publications

Diverse Phases of Carbonaceous Materials from Stochastic Simulations

Diverse Phases of Carbonaceous Materials from Stochastic Simulations

Optimization of Biochar Production by Co-Torrefaction of Microalgae and Lignocellulosic Biomass Using Response Surface Methodology

Computational study of the effect of core–skin structure on the mechanical properties of carbon nanofibers

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