Silicon production process evaluations

Chemical engineering analysis was continued for the HSC process (Hemlock Semiconductor Corporation) in which solar cell silicon is produced in a 1,000 MT/yr plant. Progress and status are reported for the primary engineering activities involved in the preliminary process engineering design of the plant base case conditions (96%), reaction chemistry (96%), process flow diagram (85%), material balance (85%), energy balance (60%), property data (60%), equipment design (40%), major equipment list (30%) and labor requirements (10%). Engineering design of the second distillation column (D-02, TCS column) in the process was completed. The design is based on a 97% recovery of the light key (TCS, trichlorosilane) in the distillate and a 97% recovery of the heavy key (TET, silicon tetrachloride) in the bottoms. At a reflux ratio of 2, the specified recovery of TCS and TET is achieved with 20 trays (equilibrium stages, N=20). Respective feed tray locations are 9, 12 and 15 (NF sub 1 = 9, NF sub 2 = 12,, and NF sub 3 = 15). A total condenser is used for the distillation which is conducted at a pressure of 90 psia

Production Process of Liquid Fertilizer From Banana Trunk

Banana a plant that many grow in Indonesia. Utilization of banana mostly just takes the fruitand leaves, while the trunk of banana has not been much used. The existence of Ca, P and K in bananatrunk, then the banana trunk can be used as alternative raw material for the production of liquidfertilizer. Produce liquid fertilizer from banana trunk done with the extraction process using a processtemperature of 700C and stirring speed of 240 rpm. Results from the extraction process to analyzelevels of Ca, P and K. Where available Ca content: 16.2% weight, P content: 30.05% weight and Kcontent: 21.5% weight with volume 600 ml of solvent and 15 minutes of stirring time

Silicon production process evaluations

Engineering design of the third distillation column in the process was accomplished. The initial design is based on a 94.35% recovery of dichlorosilane in the distillate and a 99.9% recovery of trichlorosilane in the bottoms. The specified separation is achieved at a reflux ratio of 15 with 20 trays (equilibrium stages). Additional specifications and results are reported including equipment size, temperatures and pressure. Specific raw material requirements necessary to produce the silicon in the process are presented. The primary raw materials include metallurgical grade silicon, silicon tetrachloride, hydrogen, copper (catalyst) and lime (waste treatment). Hydrogen chloride is produced as by product in the silicon deposition. Cost analysis of the process was initiated during this reporting period

Process system engineering in biodiesel production: a review

Biodiesel is fast becoming a popular alternative to fossil fuels, as it is natural, renewable and has low toxic emissions. Strategies that have been adopted to ensure continued growth of the biodiesel industry are policy development, reduction of biodiesel tax, offset funding for incremental fuel cost from CO2 emission fuel and support for research and development of potential biodiesel feedstocks. Recent innovations of biodiesel processes are focused on the development of more efficient catalysts and in the utilization of novel reaction media such as supercritical fluids as well as on a variety of oil feedstocks such as virgin and waste oils. Biodiesel production involves complex processes which require systematic process design and optimization. The main aim of designing biodiesel plants is to maxime conversion of ethyl or methyl esters at the lowest capital cost of the plant. The design should also consider safety and environmental concerns. Process system engineering (PSE) is a systematic approach to design and analyze complex processes by using a variety of PSE tools for the optimization of biodiesel production. This paper reviews the latest PSE tools used in development of novel biodiesel processes. It describes the main PSE elements such as process model development and product design, simulation of biodiesel processes, optimization of biodiesel synthesis, and integration of reactor and separation systems. This review also highlights the sustainability of biodiesel production

Process modelling of a PVC production plant

This paper presents the modelling of a Polyvinyl Chloride (PVC) resins manufacturing process with batch process simulator, SuperPro Designer V6.0. The simulation model has been developed based on the operating condition of a local PVC manufacturing plant. As the polymerisation process is carried out in batch operation mode, efforts have been made to document the scheduling details of each unit operation and results are presented in the Gantt chart. Cycle time for a complete polymerisation process is determined to be 14.28 hours. The model also reveals that approximately 17 batches of polymerisation reaction can be processed per day, which tallies the real operation of the PVC manufacturing plant

Process system engineering in biodiesel production: a review

Biodiesel is fast becoming a popular alternative to fossil fuels, as it is natural, renewable and has low toxic emissions. Strategies that have been adopted to ensure continued growth of the biodiesel industry are policy development, reduction of biodiesel tax, offset funding for incremental fuel cost from CO2 emission fuel and support for research and development of potential biodiesel feedstocks. Recent innovations of biodiesel processes are focused on the development of more efficient catalysts and in the utilization of novel reaction media such as supercritical fluids as well as on a variety of oil feedstocks such as virgin and waste oils. Biodiesel production involves complex processes which require systematic process design and optimization. The main aim of designing biodiesel plants is to maxime conversion of ethyl or methyl esters at the lowest capital cost of the plant. The design should also consider safety and environmental concerns. Process system engineering (PSE) is a systematic approach to design and analyze complex processes by using a variety of PSE tools for the optimization of biodiesel production. This paper reviews the latest PSE tools used in development of novel biodiesel processes. It describes the main PSE elements such as process model development and product design, simulation of biodiesel processes, optimization of biodiesel synthesis, and integration of reactor and separation systems. This review also highlights the sustainability of biodiesel production

Phase transition of the one-dimensional coagulation-production process

Recently an exact solution has been found (M.Henkel and H.Hinrichsen, cond-mat/0010062) for the 1d coagulation production process: 2A ->A, A0A->3A with equal diffusion and coagulation rates. This model evolves into the inactive phase independently of the production rate with $t^{-1/2}$ density decay law. Here I show that cluster mean-field approximations and Monte Carlo simulations predict a continuous phase transition for higher diffusion/coagulation rates as considered in cond-mat/0010062. Numerical evidence is given that the phase transition universality agrees with that of the annihilation-fission model with low diffusions.Comment: 4 pages, 4 figures include

r-Process Lanthanide Production and Heating Rates in Kilonovae

r-Process nucleosynthesis in material ejected during neutron star mergers may lead to radioactively powered transients called kilonovae. The timescale and peak luminosity of these transients depend on the composition of the ejecta, which determines the local heating rate from nuclear decays and the opacity. Kasen et al. (2013, ApJ, 774, 25) and Tanaka & Hotokezaka (2013, ApJ, 775, 113) pointed out that lanthanides can drastically increase the opacity in these outflows. We use the new general-purpose nuclear reaction network SkyNet to carry out a parameter study of r-process nucleosynthesis for a range of initial electron fractions $Y_e$, initial specific entropies $s$, and expansion timescales $\tau$. We find that the ejecta is lanthanide-free for $Y_e \gtrsim 0.22 - 0.30$, depending on $s$ and $\tau$. The heating rate is insensitive to $s$ and $\tau$, but certain, larger values of $Y_e$ lead to reduced heating rates, due to individual nuclides dominating the heating. We calculate approximate light curves with a simplified gray radiative transport scheme. The light curves peak at about a day (week) in the lanthanide-free (-rich) cases. The heating rate does not change much as the ejecta becomes lanthanide-free with increasing $Y_e$, but the light curve peak becomes about an order of magnitude brighter because it peaks much earlier when the heating rate is larger. We also provide parametric fits for the heating rates between 0.1 and $100\,\text{days}$, and we provide a simple fit in $Y_e$, $s$, and $\tau$ to estimate whether the ejecta is lanthanide-rich or not.Comment: 19 pages, 9 figure