Scalable synthesis of porous silicon nanoparticles by the magnesiothermic method as anode lithium-ion batteries with sodium alginate as the binder

(1)

South African Journal of Chemical Engineering 41 (2022) 203–210

Available online 19 June 2022

1026-9185/© 2022 The Authors. Published by Elsevier B.V. on behalf of Institution of Chemical Engineers. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Scalable synthesis of porous silicon nanoparticles from rice husk with the addition of KBr as a scavenger agent during reduction by the

magnesiothermic method as anode lithium-ion batteries with sodium alginate as the binder

Amru Daulay

^a

, Andriayani

^b^,^*

, Marpongahtun

^b

, Saharman Gea

^b

, Tamrin

^b

aPostgraduate School, Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Sumatera Utara, Jl Bioteknologi No.1, Medan, 20155, Indonesia

bDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Sumatera Utara, Jl. Bioteknologi No.1 Medan, 20155, Indonesia

A R T I C L E I N F O Keywords:

Anode

Lithium-ion battery Magnesiothermic method Porous silicon nanoparticles Rice husk

A B S T R A C T

Porous silicon nanoparticle has been synthesized via a highly scalable heat scavenger-assisted magnesiothermic reduction of rice husk. Addition of KBr as scavenger agent for the highly exothermic magnesium reduction process. Porous silicon nanoparticles are a promising anode material for lithium-ion batteries. Effective binders can keep porous silicon nanoparticle anode materials from breaking down and losing their anode capacity because of the massive volume changes during alloy dealloying. The porous silicon nanoparticles are charac- terized by x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), nitrogen adsorption, and scanning electron microscope (SEM). The application of silicon nanoparticles on lithium-ion batteries with sodium alginate as the binders resulted in a good performance. The cyclic voltammetry (CV) curve of PSiNPs-1 shows a reduction peak at 0.17 V with oxidation peaks at 0.77 V. PSiNPs-1.5 shows a reduction peak at 0.18 V with oxidation peaks at 0.83 V. PSiNPs-2 shows a reduction peak at 0.20 V with oxidation peaks at 0.83 V. The PSiNPs-1 after the first cycle shows the charge-transfer resistance (Rct) value of 488 Ω, lower than PSiNPs-1.5 and PSiNPs-2. It indicates an improved charge transferability, confirming the role of porous silicon nanoparticles in enhancing electrical conductivity. Warburg coefficient of PSiNPS-1 shows lower impedance, suggesting the greatly enhanced lithium ions transport inside the active material particles. In comparison, the PSiNPs-1 electrode delivers a high initial specific capacity of 2777 mAh g⁻¹and maintains a specific capacity of 2579 mAh g⁻¹after 100 cycles.

1. Introduction

Electrode materials that are low cost and can store much energy are needed to make the next generation of lithium-ion batteries (LIBs) (Liu et al., 2017; Pomerantseva et al., 2019; Sun et al., 2016). A wide range of new anode and cathode materials is getting a lot of attention (Wang et al., 2016; Zheng et al., 2014). Next-generation LIBs could use anodes made of silicon (Si), with a high theoretical capacity of 4200 mAhg⁻¹. It is more than ten times more than the theoretical capacity of graphite anodes (Wang et al., 2020). A silicon anode will allow more advanced lithium-ion battery chemistries and reduce cell costs (Yan et al., 2022).

Since its volume changes so much during lithiation and delithiation, Si has difficulty cycling. Its electrodes are pulverized, and the solid-

electrolyte interphase, or SEI (Huang et al., 2019b, 2019a). In general, reducing the size of silicon to the nanoscale in at least one dimension can lessen the stress and prevent fracture. Nanoparticles (Muna`o et al., 2012), nanorods (Tanaka et al., 2021), nanowires (Ge et al., 2012), nanotubes (Bourderau et al., 1999), nanosheets (Park et al., 2021), and many other Si nanostructures have shown that they can be used more often than bulk Si. It is because have a longer cycle life than bulk Si.

However, these Si nanostructures have a low initial coulombic efficiency because they have a lot of surface area, which leads to a lot of SEI growth and a low volumetric energy density of their low tap density (Liu et al., 2014). Porous Si particles made from nanostructured parts could have a higher coulombic efficiency and volumetric energy density while still being stable and having enough void space to buffer the volume

* Corresponding author.

E-mail address: [email protected] (Andriayani).

Contents lists available at ScienceDirect

South African Journal of Chemical Engineering

journal homepage: www.elsevier.com/locate/sajce

https://doi.org/10.1016/j.sajce.2022.06.005

Received 1 May 2022; Received in revised form 22 May 2022; Accepted 18 June 2022

(2)

South African Journal of Chemical Engineering 41 (2022) 203–210 expansion. It would make them suitable for cycling. Moreover, the yield

Si product obtained is low (Liang et al., 2014; Ren et al., 2016). Because the relationship between the conditions used to make the product and its properties is important (Chen et al., 2018), but often not enough thought has been given to this point to make microscale porous Si anodes with high yields and good electrochemical performance.

Rice husk is the byproduct of rice milling and is one of the biggest wastes from agriculture. The amount of silica range from 15% to 28%

(Singh, 2018). Silicon is essential for rice to grow, and it can even be thought of as rice food (Nwite et al., 2019). As water-soluble silicic acid, silicon enters rice. It is then polymerized and precipitated as amorphous silica (Daulay et al., 2021a). It is possible to make biogenic silica nanostructured frameworks in the body under mild conditions (Daulay et al., 2021b).

Carbothermal, magnesiothermic, aluminothermic, and calciother- mic methods are some of the well-known ways to reduce SiO2. Carbo- thermal reduction uses electric arc furnaces at 2000^◦C and is the primary way to make metallurgical silicon (Liu et al., 2019; Maeng et al., 2020).

However, this process uses much energy and melts the silicon, which makes the SiO2 look different than it did before. The magnesiothermic reduction has been getting much attention because it can run at a much lower temperature than other types of cutting (800^◦C). Usually, Add Mg powder with SiO2 powder in a furnace, and the furnace is heated until the Mg evaporates. However, this method of reducing Mg to Mg2Si produces different composition zones. Mg2Si forms near the Mg powder, Si is in the middle, and unreacted SiO2 is farthest from the Mg (A.

Andriayani, 2014; Agusman and Andriayani, 2020; Andriayani et al., 2021). In this highly exothermic reaction, much heat is released. In addition, KBr to the reduction process as a scavenger agent during the reduction of heat generated during this highly exothermic reaction. KBr effectively halts the reaction temperature rise during fusion, preventing the reaction from surpassing the melting point of silicon and thus aiding in preserving the original SiO2 morphology.

This study synthesized nanoporous silicon nanoparticles from rice husk using the magnesiothermic method with Mg powder (A.

Andriayani et al., 2015; Agusman and Andriayani, 2020; Andriayani et al., 2021). Addition of KBr as a scavenger agent during reduction by the magnesiothermic method. The first was the preparation of silica from rice husks. The second step was the reduction of silica to nanoporous silicon nanoparticles. The third step was to purify nanoporous silicon nanoparticles. The nanoporous silicon nanoparticles were applied as anode lithium-ion batteries.

2. Materials and methods 2.1. Materials

Rice husk was obtained from Deli Serdang, Indonesia, and dried for 12 h. Distilled water was purchased CV. Rudang Jaya. Deionized water (DI) was purchased CV. Anugerah Cahaya Abadi. Sodium hydroxide (NaOH 98wt%), hydrochloric acid (HCl 37wt%), potassium bromide (KBr 98wt%), magnesium powder (Mg 98wt%), ethanol (EtOH 98wt%), hydrofluoric acid (HF 40%wt), lithium hexafluorophosphate (LiPF6

99wt%), ethylene carbonate (EC 99wt%), diethyl carbonate (DEC 99wt

%), ethyl methyl carbonate (EMC 98wt%), acetylene black (AB), sodium alginate (SA), and n-methyl-2-pyrrolidone (NMP) were purchased by Sigma-Aldrich. Whatman glass microfiber filter was purchased by Cytiva. Cupper foil and lithium iron phosphate foil (LFP) were purchased by Shandong Gelon. All the chemical reagents as approved without additional purification.

2.2. Synthesis of porous silicon nanoparticles

Rice husk was calcined at a temperature 600^◦C for 5 h. Rice husk ash was added with NaOH and stirred at 240 rpm, 100^◦C for 3 h. The results were filtered, and the filtrate was added with HCl until pH 7, and a

precipitate was formed. The precipitate was filtered, and the filtrate was heated at 100^◦C for 3 h. Washed repeatedly with distilled water and dried again. It obtains silica powder. The mixture of silica and KBr in a ratio of 1:10 then added DI water and stirred for 3 h. The stirrer was ultrasonicated for 6 h. The results of the ultrasonicated were decanted, and the filtered was dried for 12 h. The dried powder was added with Mg powder in a ratio of 1:X (X = 1, 1.5, and 2). Calcination was carried out at 800^◦C for 6 h. The first step of purification with the addition of 150 mL DI and 15 mL ethanol was stirred for 3 h. The stirrer was centrifuged at 4000 rpm for 30 min. It was dried and washed repeatedly with DI and then dried at 80^◦C for 6 h. The second step was the addition of 150 mL of 5 N HCl and then left for 12 h. The centrifugate at 4000 rpm for 30 min.

It was dried and washed repeatedly with DI and then dried again at 80^◦C for 6 h. The third step by adding 150 mL of 10% HF and leaving for 15 min. Dried and washed repeatedly with DI and then dried again at 80^◦C for 6 h. Three samples were named PSiNPs-1, PSiNPs-1.5, and PSiNPs-2.

That 1, 1.5, and 2 are based on the ratio of Mg powder.

2.3. Characterization

X-ray diffraction (XRD) patterns of the samples were recorded CuKα (λ = 0.15406 nm) radiation from 10^◦to 90^◦. A multi-technique ultra- high vacuum Imaging XPS microprobe system performed X-ray photoelectron spectroscopy (XPS) analysis. Nitrogen adsorption and desorption isotherms were determined by nitrogen physisorption at 77 K on Quantachrome Instruments. Scanning Electron Microscope (SEM, JED- 2300, Jeol) to investigate the morphology.

2.4. Electrochemical measurement

Swagelok-type cells were assembled to evaluate the electrochemical performance. Working electrodes were composed of 60 wt% the nanoporous silicon nanoparticles, 20 wt% AB as a conductive agent, and 20 wt% SA as the binder. The electrode ingredients were mixed in NMP to obtain a uniform slurry. The obtained electrode slurry was spread on the copper foil and dried at 80^◦C for 12 h. The electrolyte was 1 mol LiPF₆ with a mixture of EC, DEC, and EMC with 1:1:1. LFP was used as the counter electrode. The separator was a Whatman glass microfiber filter.

The galvanostatic charge and discharge (GCD), Cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) were carried out with Corrtest. The scan rate for CV was 0.2 mVs⁻¹.

3. Results and discussions 3.1. Analysis of XRD

XRD diffractogram of porous silicon nanoparticles is shown in Fig. 1.

In diffractogram obtained 2θ at 28.42ô, 47.30ô, 56.10ô, 69.17ôaccording to hkl (111), (220), (311), (400). It indicates that the diffractogram has formed silicon, according to JCPDS Card No. 00-005-0565. There was no significant difference in peaks for PSiNPs-1, PSiNPs-1.5, and PSiNPs-2.

The particle size can be determined using the Debye Scherrer formula.

Based on the calculation results, it was found that the particle size of PSiNPs-1 is 25.75 nm, PSiNPs-1.5 is 26.32 nm, and PSiNPs-2 is 26.33 nm. Based on the particle size of PSiNPs-1, PSiNPs-1.5, and PSiNPs-2, it can be concluded that the porous silicon formed is a nanoparticle (Khan et al., 2019).

3.2. Analysis of XPS

The XPS spectrum for the porous nanoparticles is shown in Fig. 2.

Overall, there was no significant difference in the wide scan XPS spectrum (Fig. 2a). The spectrum shows Si2p and Si2s. It is common to indicate the presence of silicon (Kaur et al., 2016). The wide scan shows the presence of O1s that indicates silicon impurity, such as SiO2 (Idriss, 2021). The presence of Mg1s is a silicon impurity because the A. Daulay et al.

(3)

purification is not completely perfect. The higher Mg with the ratio of silica and Mg during reduction as magnesiothermic, the more silicon impurity Mg exists (Uhl and Staemmler, 2019). The presence of C1s indicates that when calcination generates carbon (Morgan, 2021). XPS spectrum high scan Si2p (Fig. 2b) PSiNPs-1, PSiNPs-1.5, and PSiNPs-2 show Si-Si and SiO2. In PSiNPs-1, certainly, SiO2 is not visible. Howev- er, the PSiNPs-1.5 and PSiNPs-2 show SiO2. Especially on PSiNPs-2, it shows a high spectrum for SiO2. It indicates that PSiNPs-2 is more impure than PSiNPs-1.5 and PSiNPs-1. The highest silicon purity was obtained at PSiNPs-1. It shows that the addition of Mg makes it difficult to remove SiO2 in the purity of the silicon process.

3.3. Analysis of N2 Adsorption

Nitrogen adsorption and desorption were performed isotherm at a temperature of 77 K (Fig. 3 and Table 1). The graph of the adsorption isotherm using the Brunauer-Emmet-Teller (BET) method is shown in the graph in Fig. 3a, and the pore size distribution using the Barret- Joyner-Halenda (BJH) method is shown in Fig. 3b. The adsorption isotherm graph shows that PSiNPs-1, PSiNPs-1.5, and PSiNPs-2 are porous. PSiNPs-1, PSiNPs-1.5, and PSiNPs-2 showed hysteresis loops on their adsorption/desorption graphs. The appearance of a hysteresis loop on the adsorption/desorption graph indicates that the material has adsorbed nitrogen through the capillary condensation process. In capillary condensation, two different relative pressure values are Fig. 1. XRD diffractogram of porous silicon nanoparticles

Fig. 2. XPS spectrum of porous silicon nanoparticles on (a) wide scan and (b) high scan Si2p

(4)

South African Journal of Chemical Engineering 41 (2022) 203–210

produced, so it can be observed on the graph that there is a pressure difference between the adsorption and desorption processes. The hysteresis produced by the capillary condensation process can be caused by cylindrical pores, parallel-sided slits, wedge-shaped slits, and gaps between particle spheres (Choi et al., 2018). The adsorption isotherms on silicon nanoparticles PSiNPs-1, PSiNPs-1.5, and PSiNPs-2 show a type IV isotherm graph (Abebe et al., 2018). The BET surface area of PSiNPs-1 is 11.28 m²g⁻¹, PSiNPs-1.5 is 46.37 m²g⁻¹, and PSiNPs-2 is 74.85 m²g⁻¹. It indicates that the increasing addition of Mg in ratio silica and Mg during reduction as magnesiothermic increases the surface area (Kim et al., 2015). The porous silicon nanoparticles are not complete during the purification process, and there is a small amount of Mg, which causes a large surface area (Maldonado, 2020). The pore size in PSiNPs-1 is 1.69 nm, PSiNPs-1.5 is 1.70 nm, and PSiNPs-2 is 2.42 nm. Due to small amounts of Mg in the porous silicon, the pore size increases. PSiNPS-1 certainly has a small pore size and a small surface area.

3.4. Analysis of SEM

SEM images are present in Fig. 4. The SEM image shows that the porous silicon nanoparticles are spherical, respectively. It refers to the general shape of silicon, which is spherical (Molet et al., 2020). Several

pores indicate cylindrical pores. It is also related to the graph form of the BET adsorption isotherm in Fig. 3a, which has the shape of cylindrical pores (Coasne et al., 2002). PSiNPs-1 has a spherical shape without any agglomeration. However, PSiNPs-1.5 and PSiNPs-2 have agglomeration, which means the porous silicon nanoparticles are not pure. The porous silicon nanoparticles impurities can be either SiO2 or Mg.

3.5. Analysis of Electrochemical

The CV curves of porous silicon nanoparticles are shown in Fig. 5a. It indicates that the increasing addition of Mg in ratio silica and Mg during reduction as magnesiothermic increases the reduction peak is attributed to the formation of Li-Si alloy (LixSi) and oxidation peaks attributed to the dealloying process of Li-Si phases to amorphous Si. The CV curve of PSiNPs-1 (Fig. 5b) shows a reduction peak around 0.17 V attributed to the formation of Li-Si alloy (LixSi). During the anodic scanning, the oxidation peaks around 0.37 V and 0.77 V correspond to the dealloying process of Li-Si phases to amorphous Si. The CV curve of PSiNPs-1.5 (Fig. 5c) shows a reduction peak around 0.18 V attributed to the formation of Li-Si alloy (LixSi). During the anodic scanning, the oxidation peaks around 0.35 V and 0.83 V correspond to the dealloying process of Li-Si phases to amorphous Si. The CV curve of PSiNPs-2 (Fig. 5d) shows a reduction peak around 0.20 V attributed to the formation of Li-Si alloy (LixSi). During the anodic scanning, the oxidation peaks around 0.40 V and 0.83 V correspond to the dealloying process of Li-Si phases to amorphous Si. The gradual activation of the porous silicon nanoparticles electrode causes the increasing peak current. Generally, a high peak current means excellent Li-ion transport kinetics (Hu et al., 2019). The PSiNPs-1 exhibits a maximum oxidation peak current value of 4.23 Ag⁻¹ at the fifth cycle, higher than PSiNPs-1.5 (4.19 Ag⁻¹) and PSiNPs-2 (4.17 Ag⁻¹). The previous study about sodium alginate can be an effective Fig. 3. N2 adsorption porous silicon nanoparticles of (a) Brunauer-Emmett-Teller (BET) and (b) Barrett-Joyner-Halenda (BJH).

Table 1

Physical properties of the porous silicon nanoparticles

Samples BET surface area (m²g⁻¹) Pore volume (cm³g⁻¹) Pore size (nm)

PSiNPS-1 11.28 0.02 1.69

PSiNPS-

1.5 46.37 0.11 1.70

PSiNPS-2 74.85 0.10 2.42

Fig. 4. SEM images of (a) PSiNPs-1, (b) PSiNPs-1.5, and (c) PSiNPs-2 with magnification 5000x

A. Daulay et al.

(5)

method to enhance the capacity of silicon anodes (Liu et al., 2014). It attributed the improved capacity of Si anode to the contribution of the binder.

Such improved electrochemical performances of porous silicon nanoparticles can be mainly due to the microscaled porous dendritic structure and the decoration of porous silicon nanoparticles. To further study the Li⁺ /electron transport mechanism, the EIS of PSiNPs-1, PSiNPs-1.5, and PSiNPs-2 after the first cycle was conducted, as shown in Fig. 4(a). From high frequency to low-frequency areas, both of them exhibit a depressed semicircle and then an oblique line, related to the charge-transfer process and Li+ diffusion process, respectively (Vortmann-Westhoven et al., 2017; Zhang et al., 2017). The electrolyte resistance (Rs), the charge-transfer resistance (Rct), and the diffusion parameter (Warburg Coefficient) of the impedance spectra were fitted by Zview software (Table 2), based on the equivalent circuit model (Fig. 4b). The PSiNPs-1 after the first cycle shows the Rct value of 488 Ω, lower than PSiNPs-1.5 (490.9 Ω) and PSiNPs-2 (496.4 Ω), indicating an improved charge transferability, confirming the role of porous silicon nanoparticles to enhance the electrical conductivity. In the low-frequency area, the electrochemical impedance spectra show an oblique line associated with the solid-state diffusion of lithium ions

inside the active material particles, and this process can be described by Warburg impedance. Warburg impedance is mainly caused by ion diffusion (Wu et al., 2018). The Warburg coefficient of PSiNPS-1 shows lower impedance, suggesting the greatly enhanced lithium ions transport inside the active material particles. Fig. 6

The ultimate evaluation of different binders comes down to electrochemical performance. The cycling performance of PSiNPs-1, PSiNPs- 1.5, and PSiNPs-2 are shown in Fig. 7. It can be found that the PSiNPs- 1.5 and PSiNPs-2 electrodes show a decrease in capacity after 100 cycles and remain at 2203 mAh g⁻¹and 2118 mAh g⁻¹, respectively. In comparison, the PSiNPs-1 electrode delivers a high initial specific capacity of 2777 mAh g⁻¹and maintains a specific capacity of 2579 mAh g⁻¹after 100 cycles, corresponding to coulombic efficiencies of 94.36%, respectively. The applied potential range for alloying lithium with silicon is beyond the lowest unoccupied molecular orbital of the carbonate- based electrolyte (Schroder et al., 2015). Therefore, porous silicon nanoparticles form due to the electrolyte reductive decomposition under the applied voltage during the lithiation. In the initial lithiation, the native oxide covering the surface of porous silicon nanoparticles is destroyed and generates an inner solid electrolyte interface primarily composed of LixSiOy and lithium ethylene dicarbonate. An outer solid electrolyte interface mainly comprises lithium ethylene dicarbonate, and LiF forms as the discharge continue. These solid electrolyte interface components containing lithium are stable under the applied potential window. Thus, the consumed Li cannot be entirely extracted from the established solid electrolyte interface components during delithiation, which leads to irreversible capacity loss and low coulombic efficiency for the first cycle. The slightly higher coulombic efficiency in the initial charge-discharge of PSiNPs-1 reveals the superior electrochemical Fig. 5. The cyclic voltametry curve of (a) porous silicon nanoparticles, (b) PSiNPs-1, (c) PSiNPs-1.5, and (d) PSiNPs-2 between 0.00 V and 2.0 V

Table 2

The fitted and calculated results of the porous silicon nanoparticles electrodes

Samples Rs (Ω) Rct (Ω) Warburg coefficient (Aw)

PSiNPS-1 39.18 488 8.56

PSiNPS-1.5 38.84 490.9 12.96

PSiNPS-2 38.89 496.4 22.30

(6)

South African Journal of Chemical Engineering 41 (2022) 203–210

compatibility of porous silicon nanoparticles with electrolytes (Li et al., 2017).

4. Conclusion

Synthesis of porous silicon nanoparticles from rice husk with KBr as a scavenger agent during reduction by the magnesiothermic method has been done with a highly scalable, cheap, and environmentally benign synthesis route for silicon production nanoparticles. A ratio of silica: Mg, which is 1:1, can produce porous silicon nanoparticles with minor impurities. Application of silicon nanoparticles on lithium-ion batteries with sodium alginate as the binders resulted in a good performance. The CV curve of PSiNPs-1 shows a reduction peak at 0.17 V with oxidation peaks at 0.77 V. PSiNPs-1.5 shows a reduction peak at 0.18 V with oxidation peaks at 0.83 V. PSiNPs-2 shows a reduction peak at 0.20 V

with oxidation peaks at 0.83 V. The PSiNPs-1 after the first cycle shows the Rct value of 488 Ω, lower than PSiNPs-1.5 and PSiNPs-2, indicating an improved charge transferability, confirming the role of porous silicon nanoparticles to enhance the electrical conductivity. Warburg coefficient of PSiNPS-1 shows lower impedance, suggesting the greatly enhanced lithium ions transport inside the active material particles. The PSiNPs-1.5 and PSiNPs-2 electrodes show decreased capacity after 100 cycles and remain at 2203 mAh g⁻¹and 2118 mAh g⁻¹, respectively. In comparison, the PSiNPs-1 electrode delivers a high initial specific capacity of 2777 mAh g⁻¹and maintains a specific capacity of 2579 mAh g⁻¹after 100 cycles.

Declaration of Competing Interest

The authors state that they have no known conflicting financial or Fig. 6. (a) Nyquist plots of the porous silicon nanoparticles electrodes measured after the first cycle. (b) The equivalent circuit model fits the electrochemical impedance spectra.

Fig. 7. Charge and discharge of porous silicon nanoparticles with 100 cycles

A. Daulay et al.

(7)

personal interests that might have influenced the work presented in this study.

Acknowledgments

The research has been carried out under the financial support obtained from PDD Dikti 2021 with a contract number 229/UN5.2.3.1/

PPM/KP-DRPM/2021.

References

Andriayani, A., 2014. Increased of Purity Silicon from Natural Sand with variation of Heating Time through Magnesiothermal. In: Proceeding The 2nd International Conference on Natural and Environmental Science (ICONES 2014), pp. 149–154.

Andriayani, A., Raja, S.L., Sihotang, H., Sofyan, N., 2015. Optimization of silicon extraction from Tanjung Tiram Asahan natural sand through magnesiothermic reduction. International Journal of Technology 6, 1174–1183. https://doi.org/

10.14716/ijtech.v6i7.1493.

Abebe, B., Murthy, H.C.A., Amare, E., 2018. Summary on Adsorption and Photocatalysis for Pollutant Remediation: Mini Review. Journal of Encapsulation and Adsorption Sciences 08, 225–255. https://doi.org/10.4236/jeas.2018.84012.

Agusman, R., Andriayani, 2020. The effects of mass variation potassium chloride (KCl) on characteristics of nanosilicone from natural sand through the magnesiothermic method. Journal of Physics: Conference Series 1485, 012051. https://doi.org/

10.1088/1742-6596/1485/1/012051.

Andriayani, Muis, Y., Nasution, D.Y., 2021. Chemical reduction of silica into silicon from extracted quartz sand using sodium hydroxide and hydrochloric acid solutions. p.

040002. 10.1063/5.0046150.

Bourderau, S., Brousse, T., Schleich, D., 1999. Amorphous silicon as a possible anode material for Li-ion batteries. Journal of Power Sources 81–82, 233–236. https://doi.

org/10.1016/S0378-7753(99)00194-9.

Chen, M., Li, B., Liu, X., Zhou, L., Yao, L., Zai, J., Qian, X., Yu, X., 2018. Boron-doped porous Si anode materials with high initial coulombic efficiency and long cycling stability. Journal of Materials Chemistry A 6, 3022–3027. https://doi.org/10.1039/

C7TA10153H.

Choi, K., Lee, S., Park, J.O., Park, J.-A., Cho, S.-H., Lee, S.Y., Lee, J.H., Choi, J.-W., 2018.

Chromium removal from aqueous solution by a PEI-silica nanocomposite. Scientific Reports 8, 1438. https://doi.org/10.1038/s41598-018-20017-9.

Coasne, B., Grosman, A., Ortega, C., Pellenq, R.J.M., 2002. Physisorption in nanopores of various sizes and shapes: A Grand Canonical Monte Carlo simulation study. pp.

35–42. 10.1016/S0167-2991(02)80217-8.

Daulay, A., Andriayani, Marpongahtun, Gea, S., 2021a. Effect of variation temperature at burning rice husk to obtain silica. AIP Conference Proceedings 2342, 040001.

https://doi.org/10.1063/5.0046151.

Daulay, A., Andriayani, Marpongahtun, Gea, S., 2021b. Extraction Silica from Rice Husk with Naoh Leaching Agent with Temperature Variation Burning Rice Husk. Rasayan Journal of chemistry 14, 2125–2128. https://doi.org/10.31788/RJC.2021.1436351.

Ge, M., Rong, J., Fang, X., Zhou, C., 2012. Porous Doped Silicon Nanowires for Lithium Ion Battery Anode with Long Cycle Life. Nano Letters 12, 2318–2323. https://doi.

org/10.1021/nl300206e.

Hu, S., Cai, Z., Huang, T., Zhang, H., Yu, A., 2019. A Modified Natural Polysaccharide as a High-Performance Binder for Silicon Anodes in Lithium-Ion Batteries. ACS Applied Materials & Interfaces 11, 4311–4317. https://doi.org/10.1021/acsami.8b15695.

Huang, W., Boyle, D.T., Li, Yuzhang, Li, Yanbin, Pei, A., Chen, H., Cui, Y., 2019a.

Nanostructural and Electrochemical Evolution of the Solid-Electrolyte Interphase on CuO Nanowires Revealed by Cryogenic-Electron Microscopy and Impedance Spectroscopy. ACS Nano 13, 737–744. https://doi.org/10.1021/acsnano.8b08012.

Huang, W., Wang, J., Braun, M.R., Zhang, Z., Li, Y., Boyle, D.T., McIntyre, P.C., Cui, Y., 2019b. Dynamic Structure and Chemistry of the Silicon Solid-Electrolyte Interphase Visualized by. Cryogenic Electron Microscopy. Matter 1, 1232–1245. https://doi.

org/10.1016/j.matt.2019.09.020.

Idriss, H., 2021. On the wrong assignment of the XPS O1s signal at 531–532 eV attributed to oxygen vacancies in photo- and electro-catalysts for water splitting and other materials applications. Surface Science 712, 121894. https://doi.org/10.1016/j.

susc.2021.121894.

Kaur, A., Chahal, P., Hogan, T., 2016. Selective Fabrication of SiC/Si Diodes by Excimer Laser Under Ambient Conditions. IEEE Electron Device Letters 37, 142–145. https://

doi.org/10.1109/LED.2015.2508479.

Khan, Ibrahim, Saeed, K., Khan, Idrees, 2019. Nanoparticles: Properties, applications and toxicities. Arabian Journal of Chemistry 12, 908–931. https://doi.org/10.1016/j.

arabjc.2017.05.011.

Kim, K.H., Lee, D.J., Cho, K.M., Kim, S.J., Park, J.-K., Jung, H.-T., 2015. Complete magnesiothermic reduction reaction of vertically aligned mesoporous silica channels to form pure silicon nanoparticles. Scientific Reports 5, 9014. https://doi.org/

10.1038/srep09014.

Li, C., Liu, C., Ahmed, K., Mutlu, Z., Yan, Y., Lee, I., Ozkan, M., Ozkan, C.S., 2017.

Kinetics and electrochemical evolution of binary silicon–polymer systems for lithium ion batteries. RSC Advances 7, 36541–36549. https://doi.org/10.1039/

C7RA06023H.

Liang, J., Wei, D., Lin, N., Zhu, Y., Li, X., Zhang, J., Fan, L., Qian, Y., 2014. Low temperature chemical reduction of fusional sodium metasilicate nonahydrate into a honeycomb porous silicon nanostructure. Chemical Communications 50, 6856.

https://doi.org/10.1039/c4cc00888j.

Liu, J., Zhang, Q., Wu, Z.Y., Wu, J.H., Li, J.T., Huang, L., Sun, S.G., 2014. A high- performance alginate hydrogel binder for the Si/C anode of a Li-ion battery.

Chemical Communications 50, 6386–6389. https://doi.org/10.1039/c4cc00081a.

Liu, N., Lu, Z., Zhao, J., McDowell, M.T., Lee, H.-W., Zhao, W., Cui, Y., 2014.

A pomegranate-inspired nanoscale design for large-volume-change lithium battery anodes. Nature Nanotechnology 9, 187–192. https://doi.org/10.1038/

nnano.2014.6.

Liu, Y., Wang, S., Jiang, S., Kong, J., Wang, X., Gao, B., Xing, P., Luo, X., 2019. Clean Synthesis and Formation Mechanisms of High-Purity Silicon for Solar Cells by the Carbothermic Reduction of SiC with SiO 2. ChemistrySelect 4, 4025–4034. https://

doi.org/10.1002/slct.201900287.

Liu, Y., Zhou, G., Liu, K., Cui, Y., 2017. Design of Complex Nanomaterials for Energy Storage: Past Success and Future Opportunity. Accounts of Chemical Research 50, 2895–2905. https://doi.org/10.1021/acs.accounts.7b00450.

Maeng, S.-H., Lee, H., Park, M.S., Park, S., Jeong, J., Kim, S., 2020. Ultrafast carbothermal reduction of silica to silicon using a CO2 laser beam. Scientific Reports 10, 21730. https://doi.org/10.1038/s41598-020-78562-1.

Maldonado, S., 2020. The Importance of New “Sand-to-Silicon” Processes for the Rapid Future Increase of Photovoltaics. ACS Energy Letters 5, 3628–3632. https://doi.org/

10.1021/acsenergylett.0c02100.

Molet, P., Gil-Herrera, L.K., Garcia-Pomar, J.L., Caselli, N., Blanco, ´A., L´opez, C., Mihi, A., 2020. Large area metasurfaces made with spherical silicon resonators.

Nanophotonics 9, 943–951. https://doi.org/10.1515/nanoph-2020-0035.

Morgan, D.J., 2021. Comments on the XPS Analysis of Carbon Materials. C 7, 51. 10 .3390/c7030051.

Muna`o, D., Valvo, M., van Erven, J., Kelder, E.M., Hassoun, J., Panero, S., 2012. Silicon- based nanocomposite for advanced thin film anodes in lithium-ion batteries.

J. Mater. Chem. 22, 1556–1561. https://doi.org/10.1039/C1JM13565A.

Nwite, J.C., Unagwu, B.O., Okolo, C.C., Igwe, C.A., Wakatsuki, T., 2019. Improving soil silicon and selected fertility status for rice production through rice-mill waste application in lowland sawah rice field of southeastern Nigeria. International Journal of Recycling of Organic Waste in Agriculture 8, 271–279. https://doi.org/

10.1007/s40093-019-00299-3.

Park, S.-W., Ha, J.H., Cho, B.W., Choi, H.-J., 2021. Designing of high capacity Si nanosheets anode electrodes for lithium batteries. Surface and Coatings Technology 421, 127358. https://doi.org/10.1016/j.surfcoat.2021.127358.

Pomerantseva, E., Bonaccorso, F., Feng, X., Cui, Y., Gogotsi, Y., 2019. Energy storage:

The future enabled by nanomaterials. Science 366. https://doi.org/10.1126/science.

aan8285.

Ren, W., Wang, Y., Zhang, Z., Tan, Q., Zhong, Z., Su, F., 2016. Carbon-coated porous silicon composites as high performance Li-ion battery anode materials: can the production process be cheaper and greener? Journal of Materials Chemistry A 4, 552–560. https://doi.org/10.1039/C5TA07487H.

Schroder, K., Alvarado, J., Yersak, T.A., Li, J., Dudney, N., Webb, L.J., Meng, Y.S., Stevenson, K.J., 2015. The Effect of Fluoroethylene Carbonate as an Additive on the Solid Electrolyte Interphase on Silicon Lithium-Ion Electrodes. Chemistry of Materials 27, 5531–5542. https://doi.org/10.1021/acs.chemmater.5b01627.

Singh, B., 2018. Rice husk ash. Waste and Supplementary Cementitious Materials in Concrete: Characterisation, Properties and Applications 417–460. 10.1016/B978-0-0 8-102156-9.00013-4.

Sun, Y., Liu, N., Cui, Y., 2016. Promises and challenges of nanomaterials for lithium- based rechargeable batteries. Nature Energy 1, 16071. https://doi.org/10.1038/

nenergy.2016.71.

Tanaka, A., Ohta, R., Dougakiuchi, M., Tanaka, T., Takeuchi, A., Fukuda, K., Kambara, M., 2021. Silicon nanorod formation from powder feedstock through co- condensation in plasma flash evaporation and its feasibility for lithium-ion batteries.

Scientific Reports 11, 22445. https://doi.org/10.1038/s41598-021-01984-y.

Uhl, F., Staemmler, V., 2019. An ab initio study of the O1s and Mg1s, Mg2s, Mg2p core electron binding energies in bulk MgO. Journal of Electron Spectroscopy and Related Phenomena 233, 90–96. https://doi.org/10.1016/j.elspec.2019.03.009.

Vortmann-Westhoven, B., Winter, M., Nowak, S., 2017. Where is the lithium?

Quantitative determination of the lithium distribution in lithium ion battery cells:

Investigations on the influence of the temperature, the C-rate and the cell type.

Journal of Power Sources 346, 63–70. https://doi.org/10.1016/j.

jpowsour.2017.02.028.

Wang, J., Huang, W., Kim, Y.S., Jeong, Y.K., Kim, S.C., Heo, J., Lee, H.K., Liu, B., Nah, J., Cui, Y., 2020. Scalable synthesis of nanoporous silicon microparticles for highly cyclable lithium-ion batteries. Nano Research 13, 1558–1563. https://doi.org/

10.1007/s12274-020-2770-4.

Wang, J., Tang, H., Zhang, L., Ren, H., Yu, R., Jin, Q., Qi, J., Mao, D., Yang, M., Wang, Y., Liu, P., Zhang, Y., Wen, Y., Gu, L., Ma, G., Su, Z., Tang, Z., Zhao, H., Wang, D., 2016.

Multi-shelled metal oxides prepared via an anion-adsorption mechanism for lithium- ion batteries. Nature Energy 1, 16050. https://doi.org/10.1038/nenergy.2016.50.

Wu, Y., Chen, G., Wang, Z., Zhao, Y., Shi, L., Zhu, J., Zhang, M., Jia, R., Yuan, S., 2018. In situ constructed Ag/C conductive network enhancing the C-rate performance of Si based anode. Journal of Energy Storage 17, 102–108. https://doi.org/10.1016/j.

est.2018.02.016.

Yan, Z., Jiang, J., Zhang, Y., Yang, D., Du, N., 2022. Scalable and low-cost synthesis of porous silicon nanoparticles as high-performance lithium-ion battery anode.

Materials Today Nano 18, 100175. https://doi.org/10.1016/j.mtnano.2022.100175.

Zhang, X., Lu, J., Yuan, S., Yang, J., Zhou, X., 2017. A novel method for identification of lithium-ion battery equivalent circuit model parameters considering electrochemical properties. Journal of Power Sources 345, 21–29. https://doi.org/10.1016/j.

jpowsour.2017.01.126.

Zheng, G., Lee, S.W., Liang, Z., Lee, H.-W., Yan, K., Yao, H., Wang, H., Li, W., Chu, S., Cui, Y., 2014. Interconnected hollow carbon nanospheres for stable lithium metal

(8)

South African Journal of Chemical Engineering 41 (2022) 203–210 anodes. Nature Nanotechnology 9, 618–623. https://doi.org/10.1038/

nnano.2014.152.

A. Daulay et al.