Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture DOI Creative Commons
Xiangzhou Yuan, Manu Suvarna, Juin Yau Lim

и другие.

Environmental Science & Technology, Год журнала: 2024, Номер 58(15), С. 6628 - 6636

Опубликована: Март 18, 2024

Biomass waste-derived engineered biochar for CO2 capture presents a viable route climate change mitigation and sustainable waste management. However, optimally synthesizing them enhanced performance is time- labor-intensive. To address these issues, we devise an active learning strategy to guide expedite their synthesis with improved adsorption capacities. Our framework learns from experimental data recommends optimal parameters, aiming maximize the narrow micropore volume of biochar, which exhibits linear correlation its capacity. We experimentally validate predictions, are iteratively leveraged subsequent model training revalidation, thereby establishing closed loop. Over three cycles, synthesized 16 property-specific samples such that uptake nearly doubled by final round. demonstrate data-driven workflow accelerate development high-performance broader applications as functional material.

Язык: Английский

Prediction of Soil Heavy Metal Immobilization by Biochar Using Machine Learning DOI Creative Commons
Kumuduni Niroshika Palansooriya, Jie Li, Pavani Dulanja Dissanayake

и другие.

Environmental Science & Technology, Год журнала: 2022, Номер 56(7), С. 4187 - 4198

Опубликована: Март 15, 2022

Biochar application is a promising strategy for the remediation of contaminated soil, while ensuring sustainable waste management. heavy metal (HM)-contaminated soil primarily depends on properties biochar, and HM. The optimum conditions HM immobilization in biochar-amended soils are site-specific vary among studies. Therefore, generalized approach to predict efficiency required. This study employs machine learning (ML) approaches biochar soils. nitrogen content (0.3–25.9%) rate (0.5–10%) were two most significant features affecting immobilization. Causal analysis showed that empirical categories efficiency, order importance, > experimental properties. this presents new insights into effects can help determine enhanced

Язык: Английский

Процитировано

301
Artificial intelligence for waste management in smart cities: a review DOI Creative Commons

Bingbing Fang,

Jiacheng Yu,

Zhonghao Chen

и другие.

Environmental Chemistry Letters, Год журнала: 2023, Номер 21(4), С. 1959 - 1989

Опубликована: Май 9, 2023

Abstract The rising amount of waste generated worldwide is inducing issues pollution, management, and recycling, calling for new strategies to improve the ecosystem, such as use artificial intelligence. Here, we review application intelligence in waste-to-energy, smart bins, waste-sorting robots, generation models, monitoring tracking, plastic pyrolysis, distinguishing fossil modern materials, logistics, disposal, illegal dumping, resource recovery, cities, process efficiency, cost savings, improving public health. Using logistics can reduce transportation distance by up 36.8%, savings 13.35%, time 28.22%. Artificial allows identifying sorting with an accuracy ranging from 72.8 99.95%. combined chemical analysis improves carbon emission estimation, energy conversion. We also explain how efficiency be increased costs reduced management systems cities.

Язык: Английский

Процитировано

221
Critical impacts of pyrolysis conditions and activation methods on application-oriented production of wood waste-derived biochar DOI
Mingjing He, Zibo Xu, Yuqing Sun

и другие.

Bioresource Technology, Год журнала: 2021, Номер 341, С. 125811 - 125811

Опубликована: Авг. 20, 2021

Язык: Английский

Процитировано

180
Functional Carbon from Nature: Biomass‐Derived Carbon Materials and the Recent Progress of Their Applications DOI Creative Commons

Hongzhe He,

Ruoqun Zhang,

Pengcheng Zhang

и другие.

Advanced Science, Год журнала: 2023, Номер 10(16)

Опубликована: Март 29, 2023

Abstract Biomass is considered as a promising source to fabricate functional carbon materials for its sustainability, low cost, and high content. Biomass‐derived‐carbon (BCMs) have been thriving research field. Novel structures, diverse synthesis methods, versatile applications of BCMs reported. However, there has no recent review the numerous studies different aspects BCMs‐related research. Therefore, this paper presents comprehensive that summarizes progress related Herein, typical types biomass used prepare are introduced. Variable structures summarized performance properties closely their structures. Representative strategies, including both merits drawbacks reviewed comprehensively. Moreover, influence synthetic conditions on structure as‐prepared products discussed, providing important information rational design fabrication process BCMs. Recent in based morphologies physicochemical Finally, remaining challenges BCMs, highlighted. Overall, provides valuable overview current knowledge it outlines directions future development

Язык: Английский

Процитировано

175
Impact of Surface Functional Groups and Their Introduction Methods on the Mechanisms of CO2 Adsorption on Porous Carbonaceous Adsorbents DOI Creative Commons

Ben Petrovic,

Mikhail Gorbounov, Salman Masoudi Soltani

и другие.

Carbon Capture Science & Technology, Год журнала: 2022, Номер 3, С. 100045 - 100045

Опубликована: Март 26, 2022

The utilisation of solid adsorbents for the selective removal CO2 from major emission points is an attractive method post-combustion carbon capture due to inherent potential retrofit and cost-effectiveness. Although focus in scientific community often centred on extremely novel, high-performance costly material development, exploitation carbonaceous another avenue research proving be promising. This even more pronounced when considering abundance various waste streams. production adsorbents, however, requires significant post-treatments enhance both textural physico-chemical properties adsorbent, as such, incorporation surface functionalities unavoidable can lead improvements associated adsorption. review aims critically assess routes modification implications these may have functional groups. Subsequently, adsorption mechanisms surface-modified porous carbons are discussed depth with consideration influence introduced functionalities. concludes a detailed section current modelling approaches such application artificial intelligence, Monte Carlo, Density Functional Theory simulations this realm research.

Язык: Английский

Процитировано

118
Recent advancements and challenges in emerging applications of biochar-based catalysts DOI Creative Commons
Xiangzhou Yuan, Yang Cao, Jie Li

и другие.

Biotechnology Advances, Год журнала: 2023, Номер 67, С. 108181 - 108181

Опубликована: Июнь 1, 2023

The sustainable utilization of biochar produced from biomass waste could substantially promote the development carbon neutrality and a circular economy. Due to their cost-effectiveness, multiple functionalities, tailorable porous structure, thermal stability, biochar-based catalysts play vital role in biorefineries environmental protection, contributing positive, planet-level impact. This review provides an overview emerging synthesis routes for multifunctional catalysts. It discusses recent advances biorefinery pollutant degradation air, soil, water, providing deeper more comprehensive information catalysts, such as physicochemical properties surface chemistry. catalytic performance deactivation mechanisms under different systems were critically reviewed, new insights into developing efficient practical large-scale use various applications. Machine learning (ML)-based predictions inverse design have addressed innovation with high-performance applications, ML efficiently predicts biochar, interprets underlying complicated relationships, guides synthesis. Finally, benefit economic feasibility assessments are proposed science-based guidelines industries policymakers. With concerted effort, upgrading protection reduce pollution, increase energy safety, achieve management, all which beneficial attaining several United Nations Sustainable Development Goals (UN SDGs) Environmental, Social Governance (ESG).

Язык: Английский

Процитировано

102
A generalized machine learning framework to predict the space-time yield of methanol from thermocatalytic CO2 hydrogenation DOI Creative Commons
Manu Suvarna, Thaylan Pinheiro Araújo, Javier Pérez‐Ramírez

и другие.

Applied Catalysis B Environment and Energy, Год журнала: 2022, Номер 315, С. 121530 - 121530

Опубликована: Май 25, 2022

Язык: Английский

Процитировано

96
Enhancing Biochar-Based Nonradical Persulfate Activation Using Data-Driven Techniques DOI
Rupeng Wang, Shiyu Zhang, Honglin Chen

и другие.

Environmental Science & Technology, Год журнала: 2023, Номер 57(9), С. 4050 - 4059

Опубликована: Фев. 21, 2023

Converting biomass into biochar (BC) as a functional biocatalyst to accelerate persulfate activation for water remediation has attracted much attention. However, due the complex structure of BC and difficulty in identifying intrinsic active sites, it is essential understand link between various properties corresponding mechanisms promoting nonradicals. Machine learning (ML) recently demonstrated significant potential material design property enhancement help tackle this problem. Herein, ML techniques were applied guide rational targeted acceleration nonradical pathways. The results showed high specific surface area, O% values can significantly enhance contribution. Furthermore, two features be regulated by simultaneously tuning temperatures precursors efficient directed degradation. Finally, nonradical-enhanced BCs with different sites prepared based on results. This work serves proof concept applying synthesis tailored activation, thereby revealing remarkable capability accelerating bio-based catalyst development.

Язык: Английский

Процитировано

90
Nitrogen-doped porous carbons from polyacrylonitrile fiber as effective CO2 adsorbents DOI

Changdan Ma,

Jiali Bai,

Xin Hu

и другие.

Journal of Environmental Sciences, Год журнала: 2022, Номер 125, С. 533 - 543

Опубликована: Март 20, 2022

Язык: Английский

Процитировано

88
Sustainability-inspired upcycling of waste polyethylene terephthalate plastic into porous carbon for CO2 capture DOI Creative Commons
Xiangzhou Yuan, Nallapaneni Manoj Kumar, Boris Brigljević

и другие.

Green Chemistry, Год журнала: 2022, Номер 24(4), С. 1494 - 1504

Опубликована: Янв. 1, 2022

Industrial-scale upcycling of waste polyethylene terephthalate (PET) plastic into porous carbon globally for CO 2 capture was verified as a multifunctional alternative to conventional absorption and management technologies.

Язык: Английский

Процитировано

85