A green synthesis of PEI@nano-SiO2 adsorbent from coal fly ash: Selective and efficient CO2 adsorption from biogas

2021 ◽  
Author(s):  
Xuehua Shen ◽  
Feng Yan ◽  
Chunyan Li ◽  
Zhen Zhang ◽  
Zuotai Zhang
Keyword(s):  
Renewable Energy ◽  
Fly Ash ◽  
Natural Gas ◽  
Green Synthesis ◽  
Co2 Adsorption ◽  
Coal Fly Ash ◽  
Power Grid ◽  
Nano Sio2

As an alternative renewable energy, the upgraded biogas by separating CH4 and CO2 can be used to replace the natural gas in automobile energy and power grid. Solid amine adsorbent...

Study of the parameters of zeolites synthesis from coal fly ash in order to optimize their CO2 adsorption

Fuel ◽  
2020 ◽  
Vol 276 ◽  
pp. 118041 ◽  
Author(s):  
Gabriele Verrecchia ◽  
Lorenzo Cafiero ◽  
Benedetta de Caprariis ◽  
Alessandro Dell'Era ◽  
Ida Pettiti ◽  
...  
Keyword(s):  
Fly Ash ◽  
Co2 Adsorption ◽  
Coal Fly Ash

scholarly journals Recovery of Rare Earth Elements and Yitrium from non-Magnetic Coal Fly Ash using Acetic Acid Solution

2020 ◽  
Vol 42 (1) ◽  
pp. 35
Author(s):  
Hotden Manurung ◽  
Widya Rosita ◽  
I Made Bendiyasa ◽  
Agus Prasetya ◽  
Ferian Anggara ◽  
...  
Keyword(s):  
Acetic Acid ◽  
Renewable Energy ◽  
Fly Ash ◽  
Coal Fly Ash ◽  
Acetic Acid Solution ◽  
Operating Conditions ◽  
Renewable Energy Resources ◽  
Alternative Source ◽  
Military Health ◽  
Promising Alternative

The increasing need of REY has been observed in industries such as catalyst industry, metallurgy, military, health and renewable energy resources. REY such as Ce, Nd, Y, and Eu has a prominent evidence to improve material properties such as high electropositive, good conductivity and renewable energy. Due to this increasing need of REY, exploration of alternative source has been conducted. One of the promising alternative sources is coal fly ash. The conventional method to recover REY from coal fly ash using inorganic acids is harmful to the environment. Thus, the exploration of REY extraction from coal fly ash using organic acid has been proposed in this study. The leaching agent was acetic acid applied for all operating condition. Regarding to the mineralization of REY in the form of siliceous minerals (non-magnetic coal fly ash). Silicate digestion was conducted using sodium hydroxide 8 M with solid-to-liquid of 25% to decompose the siliceous mineral. Further, the REY bound siliceous mineral will change to REY(OH)3. Temperature as one of the operating conditions was varied. The maximum recovery of leaching 20.58 %, 43.53 %, 17.38%, 40.96 %, 18.45 % and 32.74 % were achieved for Ce, Dy, La, Nd, Y and Yb respectively at temperature of 90 0C pH 1.74 and 120 minutes. For some metals, increasing the temperature higher than 70 0C does not provide any significant effect for REY recovery such as La and Ce.

Green synthesis of mesoporous γ-Al2O3 from coal fly ash with simultaneous on-site utilization of CO2

2018 ◽  
Vol 359 ◽  
pp. 535-543 ◽  
Author(s):  
Feng Yan ◽  
Jianguo Jiang ◽  
Nuo Liu ◽  
Yuchen Gao ◽  
Yuan Meng ◽  
...  
Keyword(s):  
Fly Ash ◽  
Green Synthesis ◽  
Coal Fly Ash

Green Synthesis of Nanosilica from Coal Fly Ash and Its Stabilizing Effect on CaO Sorbents for CO2 Capture

2017 ◽  
Vol 51 (13) ◽  
pp. 7606-7615 ◽  
Author(s):  
Feng Yan ◽  
Jianguo Jiang ◽  
Kaimin Li ◽  
Nuo Liu ◽  
Xuejing Chen ◽  
...  
Keyword(s):  
Fly Ash ◽  
Green Synthesis ◽  
Co2 Capture ◽  
Coal Fly Ash ◽  
Stabilizing Effect

UTILIZATION OF COAL FLY ASH FROM POWER PLANTS - I. ASH CHARACTERIZATION

2008 ◽  
Vol 7 (3) ◽  
pp. 289-293 ◽  
Author(s):  
Maria Harja ◽  
Marinela Barbuta ◽  
Lacramioara Rusu ◽  
Nicolae Apostolescu
Keyword(s):  
Fly Ash ◽  
Power Plants ◽  
Coal Fly Ash

Evaluasi Prediksi Higher Heating Value (HHV) Biomassa Berdasarkan Analisis Proksimat

2020 ◽  
Vol 4 (1) ◽  
pp. 1-7
Author(s):  
Made Dirgantara ◽  
Karelius Karelius ◽  
Marselin Devi Ariyanti, Sry Ayu K. Tamba
Keyword(s):  
Renewable Energy ◽  
Natural Gas ◽  
Key Words ◽  
Critical Analysis ◽  
Fossil Fuels ◽  
Calorific Value ◽  
Proximate Analysis ◽  
Heating Value ◽  
Bomb Calorimeter ◽  
Hhv Prediction

Abstrak – Biomassa merupakan salah satu energi terbarukan yang sangat mudah ditemui, ramah lingkungan dan cukup ekonomis. Keberadaan biomassa dapat dimaanfaatkan sebagai pengganti bahan bakar fosil, baik itu minyak bumi, gas alam maupun batu bara. Analisi diperlukan sebagai dasar biomassa sebagai energi seperti proksimat dan kalor. Analisis terpenting untuk menilai biomassa sebagai bahan bakar adalah nilai kalori atau higher heating value (HHV). HHV secara eksperimen diukur menggunakan bomb calorimeter, namun pengukuran ini kurang efektif, karena memerlukan waktu serta biaya yang tinggi. Penelitian mengenai prediksi HHV berdasarkan analisis proksimat telah dilakukan sehingga dapat mempermudah dan menghemat biaya yang diperlukan peneliti. Dalam makalah ini dibahas evaluasi persamaan untuk memprediksi HHV berdasarkan analisis proksimat pada biomassa berdasarkan data dari penelitian sebelumnya. Prediksi nilai HHV menggunakan lima persamaan yang dievaluasi dengan 25 data proksimat biomassa dari penelitian sebelumnya, kemudian dibandingkan berdasarkan nilai error untuk mendapatkan prediksi terbaik. Hasil analisis menunjukan, persamaan A terbaik di 7 biomassa, B di 6 biomassa, C di 6 biomassa, D di 5 biomassa dan E di 1 biomassa.Kata kunci: bahan bakar, biomassa, higher heating value, nilai error, proksimat  Abstract – Biomass is a renewable energy that is very easy to find, environmentally friendly, and quite economical. The existence of biomass can be used as a substitute for fossil fuels, both oil, natural gas, and coal. Analyzes are needed as a basis for biomass as energy such as proximate and heat. The most critical analysis to assess biomass as fuel is the calorific value or higher heating value (HHV). HHV is experimentally measured using a bomb calorimeter, but this measurement is less effective because it requires time and high costs. Research on the prediction of HHV based on proximate analysis has been carried out so that it can simplify and save costs needed by researchers. In this paper, the evaluation of equations is discussed to predict HHV based on proximate analysis on biomass-based on data from previous studies. HHV prediction values using five equations were evaluated with 25 proximate biomass data from previous studies, then compared based on error value to get the best predictions. The analysis shows that Equation A predicts best in 7 biomass, B in 6 biomass, C in 6 biomass, D in 5 biomass, and E in 1 biomass. Key words: fuel, biomass, higher heating value, error value, proximate 

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