Lignin Phenol Formaldehyde Resins Synthesised Using South African Spent Pulping Liquor

Abstract Purpose The current study investigated to which extent phenol could be replaced by lignins to produce lignin phenol formaldehyde (LPF) resins, utilising soda lignin and sodium lignosulphonate as by-products from the South African pulping industry.Method The lignins were characterised and soda lignin indicated the highest reactivity. It was therefore utilised to produce LPF resins at 60%, 80%, and 100% phenol substitution, using central composite designs to maximise the adhesive strength. A one-pot method allowing direct transition from phenolation to resin synthesis was used for the first time with a pulping lignin at 60% and 80% substitution.Results Plywood made with LPF60, LPF80, and LPF100 resins attained their highest shear strengths of 0.786, 1.09, and 0.987 MPa, respectively, which adhered to the GB/T 14732-2013 standard (≥ 0.7 MPa). A substitution level of 68% produced the highest shear strength of 1.11 MPa. High-density particleboard made with this LPF68 resin gave a MOR and MOE of 40 and 3209 MPa, respectively, adhering to the ANSI A208.1 requirements. Thickness swelling and water absorption was 13.5% and 37.2%, respectively.Conclusion The soda-lignin isolated by precipitation from sugarcane bagasse pulping liquor is the first industrial lignin shown to produce LPF100 resins adhering to standard requirements, without modification or additives.

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Construction of Modified Central Composite Designs for Non-standard Models

International Journal of Statistics and Probability ◽

10.5539/ijsp.v7n5p95 ◽

2018 ◽

Vol 7 (5) ◽

pp. 95

Author(s):

Iwundu, M. P.

Keyword(s):

Loss Function ◽

Information Matrix ◽

Missing Observations ◽

Design Efficiency ◽

Central Composite Designs ◽

Standard Models ◽

Alternative Designs ◽

Composite Designs ◽

Hat Matrix ◽

Central Composite

The use of loss function in studying the reduction in determinant of information matrix due to missing observations has effectively produced designs that are robust to missing observations. Modified central composite designs are constructed for non-standard models using principles of the loss function or equivalently first compound of (I ) matrix associated with hat matrix . Although central composite designs (CCDs) are reasonably robust to model mis-specifications, efficient designs with fewer design points are more economical. By classifying the losses due to missing design points in the CCD portions, where there are multiple losses associated with specified CCD portions, the design points having less influence may be deleted from the full CCD. This leads to a possible increase in design efficiency and offers alternative designs, similar in the structure of CCDs, for non-standard models.

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An approach to measuring rotatability in central composite designs

International Journal of Advanced Statistics and Probability ◽

10.14419/ijasp.v3i2.4657 ◽

2015 ◽

Vol 3 (2) ◽

pp. 126

Author(s):

Emmanuel Ohaegbulem ◽

Polycarp Chigbu

Keyword(s):

New Approach ◽

Measure Design ◽

Central Composite Designs ◽

Composite Designs ◽

Central Composite

<p>An approach to measure design rotatability and a measure, that quantifies the percentage of rotatability (from 0 to 100) in the central composite designs are introduced. This new approach is quite different from the ones provided by previous authors which assessed design rotatability by the viewing of tediously obtained contour diagrams. This new approach has not practical limitations, and the measure is very easy to compute. Some examples were used to express this approach.</p>

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Optimal Prediction Variance Capabilities of Inscribed Central Composite Designs

Asian Journal of Probability and Statistics ◽

10.9734/ajpas/2020/v8i130194 ◽

2020 ◽

pp. 1-8

Author(s):

Julius C. Nwanya ◽

Kelechukwu C. N. Dozie

Keyword(s):

Central Composite Design ◽

Design Space ◽

Optimal Prediction ◽

Prediction Variance ◽

Central Composite Designs ◽

Scaled Prediction Variance ◽

Composite Designs ◽

Central Composite

This study looks at the effects of replication on prediction variance performances of inscribe central composite design especially those without replication on the factorial and axial portion (ICCD1), inscribe central composite design with replicated axial portion (ICCD2) and inscribe central composite design whose factorial portion is replicated (ICCD3). The G-optimal, I-optimal and FDS plots were used to examine these designs. Inscribe central composite design without replicated factorial and axial portion (ICCD1) has a better maximum scaled prediction variance (SPV) at factors k = 2 to 4 while inscribe central composite design with replicated factorial portion (ICCD3) has a better maximum and average SPV at 5 and 6 factor levels. The fraction of design space (FDS) plots show that the inscribe central composite design is superior to ICCD3 and inscribe central composite design with replicated axial portion (ICCD2) from 0.0 to 0.5 of the design space while inscribe central composite design with replicated factorial portion (ICCD3) is superior to ICCD1 and ICCD2 from 0.6 to 1.0 of the design space for factors k = 2 to 4.

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