Impacts of different biochar types on hydrogen production promotion during fermentative co-digestion of food wastes and dewatered sewage sludge

Wang, Gaojun; Li, Qian; Dzakpasu, Mawuli; Gao, Xin; Yuwen, Chaosui; Wang, Xiaochang C.

doi:10.1016/j.wasman.2018.08.042

Cited by 62 publications

(13 citation statements)

References 32 publications

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“…In that case, the program generates the digraph with a statistical representation of experimental paths taken by 19 articles (doc instances) to generate biochar with that particular surface area range. CNA applied on this digraph (i.e., a modified depth-first search algorithm to find the heaviest and longest path) indicates that the following processing was sequentially performed after the pyrolysis in these 19 doc instances: “pyrolysis” → “activation” → “drying” → “ashing” → “washing” → “filtration.” This resulting experimental path indicates that biochar is activated and cleaned after the pyrolysis, which is very consistent considering possible experimental routes capable of increasing the surface area of CFMs. − …”

Section: Discussionsupporting

confidence: 79%

Machine Learning and Natural Language Processing Enable a Data-Oriented Experimental Design Approach for Producing Biochar and Hydrochar from Biomass

et al. 2022

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Carbon functional materials (CFMs) such as biochar and hydrochar can be obtained from hundreds of biomass precursors varying from urban sludge to agriculture wastes. They can be produced through tens of synthesis methods and postsynthesis processing steps tuned at specific conditions (e.g., temperature, time, and chemical concentrations). To achieve a “rational design” platform for a system with a high dimensional parameter space such as CFMs, we processed 10,975 scientific articles (from years 2000 to 2020) related to the subject with automatic reading–interpreting–extracting computational routines (namely, the a.RIX engine). The a.RIX engine automatically recognized more than a hundred precursors, among which wheat straw, rice husk, and rice straw were the most studied for CFM synthesis and application in agriculture (e.g., as an amendment), as fuel (energy generation), and as an adsorbent. Parameters related to the CFMs’ synthesis conditions, such as carbonization temperature and time, and parameters related to CFMs’ properties, such as surface area and heavy metals adsorption capacity, can also be extracted from the articles. Correlations between the CFM precursors and synthesis conditions indicated very little statistical difference between the carbonization temperature and time used for the CFMs’ synthesis from different precursors. Essentially, precursors are carbonized at temperatures varying from 100 to 900 °C for 30 min to 6 h using pyrolysis, hydrothermal carbonization, and gasification. When focusing the analysis on just CFMs produced by pyrolysis (biochar), we observed that peanut shells can produce materials with higher surface areas than other precursors (P < 0.05). When performing correlations between biochar synthesis conditions and their properties, general trends can be confirmed: (i) the higher the carbonization temperature, the lower the H/C and O/C ratios, and (ii) the increase in the surface area can be achieved by preserving a high aromatic degree (low H/C ratio) and a low oxidation level (low O/C ratio). However, a deeper understanding of the relation between CFM synthesis/postsynthesis methods and the resulting properties can only be achieved using clustering algorithms (e.g., k-means) and complex network analysis. The a.RIX engine groups articles describing optimized synthesis conditions and CFM properties (e.g., low carbonization temperature, low carbonization time, and large surface area and adsorption capacity) and automatically recognizes the synthesis/postsynthesis steps used for these groups. The program efficiently recognized that precursors such as peanut shells can be converted into highly porous biochar by using experimental routes such as “pyrolysis” → “activation” → “drying” → “ashing” → “washing” → “filtration.” With this approach, we show that a noncomputational review of scientific articles for materials with a huge parameter space such as CFMs is largely obsolete. Finally, taken together, the results provide a powerful platform for data-oriented experimental design of CF...

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Section: Discussionsupporting

confidence: 79%

Machine Learning and Natural Language Processing Enable a Data-Oriented Experimental Design Approach for Producing Biochar and Hydrochar from Biomass

et al. 2022

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“…This may be due to the fact that the biochar as additive has large specific area, which serves as a medium for syntrophic VFA-utilizing methanogens to metabolism and promotes rapid utilization of acetate to biogas. 57 …”

Section: Resultsmentioning

confidence: 99%

“…This may be due to the fact that the biochar as additive has large specic area, which serves as a medium for syntrophic VFA-utilizing methanogens to metabolism and promotes rapid utilization of acetate to biogas. 57 As an important rate-limiting step for methanogenesis, syntrophic metabolism of propionate is relatively slow due to the conversion of propionate to acetate and hydrogen being thermodynamically unfavorable (propionate + 3H 2 O ¼ acetate + HCO 3…”

Section: Effect Of Biochar On Ph and Vfasmentioning

confidence: 99%

Impacts of different biochar types on the anaerobic digestion of sewage sludge

Zhang

Wang

et al. 2019

RSC Adv.

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“…Neither biochar nor wood vinegar supplementation successfully reduced CH 4 production or had beneficial effects on fermentation parameters, effectively denying the initial hypotheses. It has been well documented that biochar particle size, electrical conductivity, adsorptive potential, and ability to manipulate biofilms all differ with biomass source and processing methodologies ( Hansen et al, 2012 ; Leng et al, 2013 ; Yu et al, 2015 ; McFarlane et al, 2017 ; Wang et al, 2018 ). Two recent publications suggest acidic carbon-rich biochar has a higher redox potential, and therefore electron-donating capacity, with potential to manipulate microbial populations ( Cruz Viggi et al, 2017 ; Huang et al, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Dose response of biochar and wood vinegar on in vitro batch culture ruminal fermentation using contrasting feed substrates

O'Reilly

Huo

Meale

et al. 2021

Translational Animal Science

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Within Australia, approximately 6.4% of total greenhouse gas emissions are from animal methane (CH4) derived from enteric fermentation. Mitigation of ruminant CH4 is a key concept in support of sustainable agriculture production; dietary manipulations a viable strategy to lower CH4 release during enteric fermentation. In order to determine the effects of dose response of biochar and wood vinegar supplementation on fermentation parameters and CH4 production, this study utilized in vitro batch culture incubations. It is hypothesized the addition of either biochar or wood vinegar will successfully reduce enteric CH4 emissions without negative modification of other fermentation parameters. Three feed substrates (vegetable mixed ration, maize silage and winter pasture) were separated into treatments containing either biochar at 0%, 0.5%, 1%, 2% and 4% DM replacing substrate (w/w basis), or wood vinegar at 0%, 0.25%, 0.5%, 1% and 2% into incubation media volume (v/v). At 6, 12 and 24 hours after inoculation, total gas volume and methane (CH4 %) were measured. Volatile fatty acids (VFA) concentrations, media pH and in vitro dry matter digestibility were measured at 24h. Biochar at various dosages had no effect (P > 0.05) on fermentation characteristics other than decreased in vitro dry matter digestibility (IVDMD; P = 0.01) at 2 and 4% (DM basis) inclusion. Similar to biochar, dose response of wood vinegar had no effect on in vitro fermentation characteristics. However, feed substrate had major effects on all fermentation parameters (P = 0.01) where winter pasture > vegetable mixed ration > maize silage for all recorded fermentation characteristics. Biochar and wood vinegar supplementation were ineffectual in mitigating CH4 production or modifying fermentation characteristics, thus rejecting the initial hypothesis. These results suggest the use of biochar is not an effective tool for methane mitigation in ruminant livestock and infers that studies previously reporting success must better define the systemic mechanisms responsible for the reduction in CH4.

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Impacts of different biochar types on hydrogen production promotion during fermentative co-digestion of food wastes and dewatered sewage sludge

Cited by 62 publications

References 32 publications

Machine Learning and Natural Language Processing Enable a Data-Oriented Experimental Design Approach for Producing Biochar and Hydrochar from Biomass

Machine Learning and Natural Language Processing Enable a Data-Oriented Experimental Design Approach for Producing Biochar and Hydrochar from Biomass

Impacts of different biochar types on the anaerobic digestion of sewage sludge

Dose response of biochar and wood vinegar on in vitro batch culture ruminal fermentation using contrasting feed substrates

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