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Ghoshal3, c 1, 2, 3Department of Physics, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor.
The glass sample is cut in the dimension of 1 cm x 1 cm x 1 cm using diamond cutter.
Table 1 Optical parameters of Eu3+ doped lithium tellurite glass.
References [1] B.J.
Lin, Journal of Alloys and Compounds 479 (2009) 352-356

The stirring time was varieties by 1, 2, 3 hours.
Stirring time was varieties for 1, 2, and 3 hours.
Particle was agglomerated as Fig 1(a) for pH 7,5, but particle appear porous as Fig 1(b).
References [1] Ataie, A., S.E.
Yanwei, Journal of Alloys and Compounds 479 (2009) : 863-869

Fig. 1: XRD pattern of Li7La3ZrSnO12 that prepared at 950 oC for 12 hours.
Beq x y z La1 8b 0 1/4 1/8 1 0.025 La2 16e 0.127 0 1/4 1 0.025 Zr1 16c 0 0 0 1 0.025 Li1 8a 0 1/4 3/8 1 0.025 Li2 16f 0.17970 0.42970 1/8 1 0.025 Li3 32g 0.08060 0.08570 0.80410 1 0.025 O1 32g -0.03380 0.05480 0.15240 1 0.025 O2 32g 0.05410 0.85290 0.53380 1 0.025 O3 32g 0.14960 0.02760 0.44640 1 0.025 Crystal symmetry Tetragonal Space group I41/acdz Lattice parameter a = 13.1279 Å, c = 12.6715 Å, V = 2183.83 Å3 Table 2: The initial structure of Li7La3Sn2O12 [4] Atom Wyckoff position Atomic Position Occ.
Beq x y z La1 16n 0 0.30471 0.30222 1 0.025 La2 8h 0.30429 0.30429 0 1 0.025 Sn1 8i 0.35088 0 0 1 0.025 Sn2 4e 0 0 0.32140 1 0.025 Li1 16m 0.1340 0.1340 0.863 1 0.025 Li2 8f 1/4 1/4 1/4 1 0.025 Li3 2a 0 0 0 1 0.025 O1 32o 0.8039 0.3696 0.6302 1 0.025 O2 16m 0.3671 0.3671 0.8116 1 0.025 O3 8g 0 1/2 0.8732 1 0.025 O4 8j 0.7681 1/2 0 1 0.025 O5 8i 0.159 0 0 0.4463 0.025 O6 2b 0 0 1/2 1 0.025 O7 4e 0 0 0.141 0.945 0.025 Crystal symmetry Tetragonal Space group I4/mmm Lattice parameter a = 12.054 Å, c = 11.890 Å, V = 1727.6 Å3 The Rietveld refinements proved that the tetragonal phase of Li7La3Zr2O12 (S.G = I41/acdZ) and Li7La3Sn2O12 (S.G. = I4/mmm) are co-exist in the sample.
References [1] K.
Chemistry of Materials, 25, 3048-3055 DOI: https://doi.org/10.1021/cm401232r [9] Mohd Sobri Idris and Rozana AM Osman, Structure Refinement Strategy of Li-based Complex Oxides using GSAS-EXPGUI software package, Advanced Materials Research, 795, 479-482 (2013). | DOI: https://doi.org/10.4028/www.scientific.net/AMR.795.479 [10] Ku Noor Dhaniah Ku Muhsen, Rozana Aina Maulat Osman, Mohd Sobri Idris, Giant anomalous dielectric behaviour of BaSnO3 at high temperature, Journal of Materials Science: Materials in Electronics, 30, 7514– 7523(2019) DOI: https://doi.org/10.1007/s10854-019-01065-x [11] J.

The composition of commercial glass billets is presented in Table 1 [4-5].
Table 1.
At 1350 °C, 1, 3 and 5 batches are almost completely melted.
The chemical heat demand and exploited heat of batches Thermodynamic data Batch 1 2 3 4 5 Hochem (kWh/t) 157 117 140 149 137 Hex (kWh/t) 489 477 479 494 488 The chemical analysis of glasses is presented in table 4.
a b c d e Fig.1 The glass batches after melted at 1350 °C for 1 hr.

However, there are minor peaks of unreacted precursor Co3O4 observed from Zn1-xCoxO powders annealed at 600 oC as shown in Fig.1 (a).
Fig. 1 (b) shows XRD peaks of the powders annealed at 800 oC.
References [1] H.
Alloys Compd. 479 (2009) 520-524
Phys. 93 (2003) 1-21

Fig. 1 shows the OM and SEM microstructure of the three alloys.
The initial melting temperature for the three alloys varies in a small range of 477~479℃ and quite small bending of the peaks exists on about 485℃, which proves the phase identification of SEM observation.
Fig. 1 OM and SEM images of as-cast Al-Zn-Mg-Cu alloys.
References [1] P.
Alloys Compd. 2008, 456(1-2): 163-169

Table 1.
Vol 54 No.1, Maret, hal. 11- 19 [7] Callahan, Richard.
Flywheel: Jurnal Teknik Mesin Untirta, 2(1)
JURNAL TEKNIK MESIN, 22(1)
TRAKSI, 14(1)

Results and discussion Fig. 1 shows the relation between solder spreading area and soldering time at 310ºC.
The Sn-3.5Ag-1.0Cu-0.7Zn solder has higher spreading area compared to other solder alloys.
The formation of Cu3Sn intermetallic at the later stage of aging was explained by Liu & Lee [6] using (1).
References [1] S.W.
Mater. 35(2006) 479-485

Finally, experiments of a variable mass cylindrical shell are adopted to demonstrate the efficiency of the two kinds of time varying parameter identification methods. 1 Introduction In many practical systems, the parameters often change over time.
Among them, the least square method [1] is one of the most widely used methods.
If ,let;If,let,,,in which is the previous moment;;and are unit matrix of and zero matrix. 3 Simulations 3.1 Simulation 1 The system differential equation is A white noise is given to generate output signals.
References [1] Chen Xian-zhi,Chen Chong.Parameter identification of time varying systems based on the least-squares modified algorithm [J].Journal of Fuzhou University,2005,33(2):163-166
[2] Chen Xin-hai,Yan Xiao-ming,Li Yan-jun.An identitication method of fast time varying parameters adapted to aircraft control systems [J].Acta Aeronautica Et Astronautica Sinica, 1990, 11(9):475-479

Oceanic waves’ magnetic noise is mainly arisen by stormy waves, ocean current, and tide[1].
Make Z-transform for formula (1).
References [1] Lin Chun-sheng, Gong Shen-guang.
Journal of Wuhan University of Technology. vol 28, pp. 479-481, July 2004.
Processing of a scalar magnetometer signal contaminated by 1/fα noise [J].