Prediction of final product properties after cocurrent spray drying

M. Kwapińska; I. Zbiciński

doi:10.1081/DRT-200065075

Prediction of final product properties after cocurrent spray drying

M. Kwapińska, I. Zbiciński

Lodz University of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

The effect of drying and atomization conditions on the physical properties of powders for agglomerate-like materials and skin-forming material are studied in this article. A neural model is used for powder bulk and tapped density predictions.

Original language	English
Pages (from-to)	1653-1665
Number of pages	13
Journal	Drying Technology
Volume	23
Issue number	8
DOIs	https://doi.org/10.1081/DRT-200065075
Publication status	Published - 2005
Externally published	Yes

Keywords

Density
Neural network
Particle diameter
Powder
Principal component analysis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1081/DRT-200065075

Cite this

@article{79161a529cfc47e6a0b87279ebea5155,

title = "Prediction of final product properties after cocurrent spray drying",

abstract = "The effect of drying and atomization conditions on the physical properties of powders for agglomerate-like materials and skin-forming material are studied in this article. A neural model is used for powder bulk and tapped density predictions.",

keywords = "Density, Neural network, Particle diameter, Powder, Principal component analysis",

author = "M. Kwapi{\'n}ska and I. Zbici{\'n}ski",

year = "2005",

doi = "10.1081/DRT-200065075",

language = "English",

volume = "23",

pages = "1653--1665",

journal = "Drying Technology",

issn = "0737-3937",

number = "8",

}

TY - JOUR

T1 - Prediction of final product properties after cocurrent spray drying

AU - Kwapińska, M.

AU - Zbiciński, I.

PY - 2005

Y1 - 2005

N2 - The effect of drying and atomization conditions on the physical properties of powders for agglomerate-like materials and skin-forming material are studied in this article. A neural model is used for powder bulk and tapped density predictions.

AB - The effect of drying and atomization conditions on the physical properties of powders for agglomerate-like materials and skin-forming material are studied in this article. A neural model is used for powder bulk and tapped density predictions.

KW - Density

KW - Neural network

KW - Particle diameter

KW - Powder

KW - Principal component analysis

UR - http://www.scopus.com/inward/record.url?scp=24344492752&partnerID=8YFLogxK

U2 - 10.1081/DRT-200065075

DO - 10.1081/DRT-200065075

M3 - Article

AN - SCOPUS:24344492752

SN - 0737-3937

VL - 23

SP - 1653

EP - 1665

JO - Drying Technology

JF - Drying Technology

IS - 8

ER -

Prediction of final product properties after cocurrent spray drying

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this