Harri Niemi's research while affiliated with Lappeenranta – Lahti University of Technology LUT and other places
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Publications (5)
A method for the simulation of membrane processes by using neural networks was developed. The neural network model is used for obtaining an estimation of permeate flux and rejection over the entire range of the process variables, i.e. pressure, concentration of solute, temperature and superficial flow velocity. Permeate flux and rejection are depen...
A membrane separation model for tubular module reverse osmosis and ultrafiltration processes was developed in this work. The membrane area of a process can be calculated by this model and the stream matrix of a process can be determined by a process simulation program. In this work the unicorn simulation program was used. The membrane separation mo...
A method for calculation of ultrafiltration and reverse osmosis processes has been developed to enable the calculation of permeate flux and rejection at different pressures and concentrations. The method has been combined with a process simulation program which calculates all streams of the process. Permeate flux and rejection in membrane processes...
Crystallization methods for proteins have been the subject of decades of development yet protein crystallization remains the limiting step in structural studies. We present here a new method for protein crystallization--based on the use of high pressure--that enabled us to accelerate dramatically the growth of glucose isomerase crystals. We think t...
id="ab1"The effect of high pressure combined with a sweating technique was studied in purification of organic crystalline chemicals. The dependence of product purity and yield on pressure, pressing period, and mass of charge were determined. Mixtures studied were guaiacol glycerin ether with guaiacol as impurity and naphthalene with diphenyl as imp...
Citations
... Generally, it is often accepted that the membrane's nanopores size controls the rejection ability of the uncharged pollutants (organic materials) based on the organic particles and membrane's pores sizes [18]. Sieving mechanism based on the pores sizes has been considered as the main process for uncharged particles removal, where the other interactions have been neglected [17,[19][20][21]. ...
... There are several more examples of Nernst-Planck-derived models for membrane transport, for example, surface force PF models [33] (and variations) and the finely porous model [34]. Both examples use the same equation but different physical parameters, replacing K d,i and K c,i by 1/(χ i,V + χ i,m ) and χ i,V /(χ i,V + χ i,m ), respectively, where χ i,V χ i,m are interpreted as friction coefficients between solute-solute and solvent-membrane. ...
... Several research studies [59][60][61] have utilized smart models to predict membrane fouling indices such as transmembrane pressure (TMP) or membrane permeate flux. These models are based on AI and aim to provide higher accuracy than mechanistic models while at the same time eliminating the need for model calibration. ...
... High quality protein crystals that can be analyzed at high resolution (<1.5 Å) are prerequisites for structure-based drug design, which is defined as a method to optimize the potency of a drug using the precise structural information of a target protein [1]. As the protein data bank (PDB) shows that 15,183 structures of protein molecules deposited until 22 December 2021 show their resolution limit higher than 1.5 Å [2], many researchers have crystallized huge number of proteins using various methods (dialysis, vapor diffusion, batch, gel-mediated, and so forth) [3] and conditions (under high magnetic field [4], electric field [5], flow [6], high pressure [7], microgravity [8], and so forth). In spite of a wide variety of methods and conditions, most of the proteins were commonly crystallized using precipitants. ...
