JP5858635B2 - Method for predicting the crystallization index of cellulose - Google Patents

Description

  The present invention relates to a method for predicting a crystallization index of cellulose in a powder obtained according to conditions when a cellulose-containing raw material is processed by mechanochemical treatment.

  Cellulose obtained by pulverizing cellulose-containing raw materials such as pulp is used as industrial raw materials such as cellulose ether raw materials, cosmetics, foods, and biomass materials. As these industrial raw materials, cellulose having an amorphous cellulose crystal structure is particularly useful. For example, the present applicant has previously proposed a method for producing amorphous cellulose from a cellulose-containing raw material having a cellulose I-type crystallization index exceeding 33% (see Patent Document 1). In this method, a raw material having a cellulose content of 20% by mass or more in the remaining components excluding water from the raw material is used, and the cellulose-containing raw material is mechanically processed using a vibration mill filled with a rod. Thus, the cellulose I-type crystallization index is reduced to 33% or less. In addition, Patent Document 2 includes container-driven pulverizers such as a rolling mill, a vibration mill, a planetary mill, and a centrifugal fluid mill as pulverizers used for processing. Among these, pulverization efficiency is high. There is a description that a vibration mill is preferable from the viewpoint of high productivity. Further, as the pulverizer, there are a ball, a rod, a tube, and the like, but it is described that the ball and the rod are preferable from the viewpoint of productivity, and the rod is more preferable.

  In the industrialization study of the container drive medium mill device, it is difficult to achieve the same performance with a large-scale mass-produced machine even if the operating conditions of a small laboratory machine used in a laboratory are used. The reason is that, since the movement of the medium is different between the lab machine and the mass production machine, it is not easy to find a condition suitable for the operation of the mass production machine from the operation conditions adopted in the lab machine. Therefore, it is the situation that we have found the optimum conditions for the amorphization of cellulose-containing raw materials by repeating trial and error experiments using pilot machines and mass production machines that are intermediate in size between laboratory machines and mass production machines. It takes days and costs to establish mass production conditions.

  In addition, when performing “Improvement of the structure of a mill device aimed at improving the performance of mass production machines” or “Manufacturing a larger-scale mass production machine”, there are more design options, making it more difficult to find specific guidelines. Trial and error becomes stronger. However, since the mill apparatus becomes large-scale, it is difficult to perform many examinations, and the desired performance may not be realized.

  In order to solve these problems, the container-driven media mill device using a spherical medium is a unit obtained by performing simulation analysis using the discrete element method for device motion such as rolling, vibration, and planetary motion. Attempts have been made to clarify the relationship between the time dissipation energy and collision energy and the pulverized particle size and crystallization index, which are experimental results (see Patent Documents 3 to 5).

  However, the techniques described in Patent Documents 3 to 5 are based on the premise that a spherical medium is used. Therefore, the techniques described in these documents cannot be directly applied to non-spherical media such as the rods described in Patent Documents 1 and 2. The reason is that no method has been established for discrete element methods other than spherical. Some commercial software uses a multi-sphere DEM method in which non-spherical particles are approximated by spherical particles, and in principle, analysis is possible using such software. However, it is also known that the simulation result varies greatly depending on the number of contact points of the spherical particles that are in contact, and Non-Patent Documents 1 and 2 present problems related to quantitativeness.

  In Non-Patent Document 1, in order to confirm the validity of the Multi-Sphere DEM method, simulation of collision characteristic parameters such as restitution coefficient, rotational speed, and collision time obtained from the recoil experiment of spherical particles (aluminum alloy, aluminum oxide) The reproduction study by is done. There, a general analysis in which spherical particles are considered as one elastic body is compared with an analysis in a coupled particle composed of a plurality of spherical particles using the Multi-Sphere DEM method. In addition, for the coupled particles, the collision characteristics in three states of one-point contact, two-point contact, and three-point contact are compared in order to consider an artificial collision state based on spherical particle approximation. It was confirmed that the collision parameters obtained by simulation considering a spherical particle as one elastic body qualitatively match the collision characteristic parameters obtained from the experimental results, but the Multi-Sphere DEM method is in a collision state. On the other hand, the result is greatly changed and does not match with the one-point contact and the two-point contact, but the three-point contact shows a good agreement with the experimental result except for some collision parameters.

  In Non-Patent Document 2, a cylinder is composed of spherical particles as in the rod mill analysis, and the contact state is compared with the analysis result by FEM, and the problem of the Multi-Sphere DEM method is shown. In this case, stress is calculated (linear elastic model) by the finite element method (FEM) when the cylinder is brought into contact with the flat plate in a tilted state and the contact angle and the contact distance are changed. The same shape as the cylinder analyzed by FEM is composed of spherical particles with a constant interparticle distance, and the physical property values of the spherical particle contact model that reproduces the results of contact angle-stress and contact distance-stress obtained by FEM are calculated backward. doing. It is desirable that the physical property values used in the spherical particle contact model be specific to the material, but the physical property values obtained vary greatly depending on the contact angle due to the large dependence of stress on the contact angle, and the changes are complex and simple. It is reported that it cannot be expressed as a function.

JP 2009-161717 A JP 2011-1547 A Japanese Patent Laid-Open No. 11-147048 JP-A-11-207203 JP 2006-10261 A

H. Kruggel-Emden, S. Rickelta, S. Wirtza and V. Scherer, "A study on the validity of the multi-sphere Discrete Element Method", Powder Technology 188, (2008), 153-165. M. Kodam, R. Bharadwaj, J. Curtis, B. Hancock, and C. Wassgren, "Force Model Considerations for Glued Sphere Discrete Element Method Simulations", Chemical Engineering Science, 64, (2009), 3466-3475.

  Accordingly, an object of the present invention is to provide a method capable of accurately predicting the crystallization index of cellulose after processing powder comprising cellulose-containing particles with a container-driven medium mill using a non-spherical medium. It is in.

The present invention is a method for predicting the crystallization index of cellulose in a powder obtained by processing a cellulose-containing raw material using a container-driven medium mill device,
By simulating the motion of the non-spherical medium in the mill apparatus by a discrete element method using a viscoelastic dynamic model, the unit time dissipated energy due to all collisions occurring in the mill apparatus is calculated,
The cellulose crystallization index in the powder obtained by processing the cellulose-containing raw material by the mill apparatus under predetermined conditions is measured in advance, the crystallization index, the unit time dissipation energy, and the mill apparatus. Find the correlation with the dissipated energy calculated from the processing conditions using
Based on the correlation between the crystallization index and the dropped dissipation energy, cellulose is used to predict the crystallization index of cellulose in the powder when the cellulose-containing raw material is processed by applying a predetermined dropped dissipation energy to the mill device. It provides a method for predicting the crystallization index.

  In the prediction method, the non-spherical medium is configured by a combined body in which a plurality of spherical particles are overlapped, and the combined body in the collision between the combined body and the collision between the combined body and the inner wall of the mill. It is preferable that the average contact number of the spherical particles is obtained in advance, so that the motion state of the combined body is simulated by a discrete element method to calculate the dropped energy.

In addition, the present invention treats a cellulose-containing raw material using a container-driven medium mill device, and predicts the energy consumed by dropping to predict the energy dissipated by dropping the cellulose crystallization index in the powder obtained by the processing to a target value. A method for predicting energy,
By simulating the motion of the non-spherical medium in the mill apparatus by a discrete element method using a viscoelastic dynamic model, the unit time dissipated energy due to all collisions occurring in the mill apparatus is calculated,
The cellulose crystallization index in the powder obtained by processing the cellulose-containing raw material by the mill apparatus under predetermined conditions is measured in advance, the crystallization index, the unit time dissipation energy, and the mill apparatus Find the correlation with the dissipated energy calculated from the processing conditions used,
Provided is a method for predicting dropped energy, which predicts dropped energy required for reducing the crystallization index of cellulose in the powder to a target value based on the correlation between the crystallization index and the dropped energy. It is.

Furthermore, the present invention is a method for producing a powder having a cellulose crystallization index reduced to a target value by processing a cellulose-containing raw material using a container-driven medium mill device,
Using the method for predicting the dropped dissipation energy, predicting the dropped dissipation energy required for the crystallization index of the cellulose in the powder to fall to the target value,
The present invention provides a method for producing a powder, in which a cellulose-containing raw material is processed using the mill apparatus set to a processing condition in which a predicted dropped dissipation energy is generated.

  ADVANTAGE OF THE INVENTION According to this invention, the crystallization index | exponent of this cellulose after processing the powder consisting of the particle | grains containing a cellulose can be accurately estimated with the container drive medium mill apparatus using a non-spherical medium. Therefore, when the container drive medium mill device is scaled up, the cellulose crystallization index after processing the powder composed of cellulose-containing particles can be predicted by the scaled up device without actually conducting experiments. .

FIG. 1 is a model diagram showing a state in which a rod-shaped medium is constituted by a combined body in which spherical particles are connected in a straight line. FIG. 2 is a flowchart of a simulation performed in the prediction method of the present invention. FIG. 3 is a schematic diagram illustrating a bonded state of spherical particles in the bonded body illustrated in FIG. 1. FIG. 4 is a model diagram showing a state when the combined body collides with the inner wall of the mill. FIG. 5 is a model diagram showing a state when the combined bodies collide with each other. FIG. 6 is a graph plotting the relationship between the dropped dissipation energy calculated in the examples according to the method of the present invention and the crystallization index of cellulose in the powder obtained by actually performing the treatment. FIG. 7 is a graph plotting the relationship between the actually measured dropped energy and the crystallization index of cellulose in the powder obtained by the actual treatment.

  Hereinafter, the method for predicting the crystallization index of cellulose of the present invention will be described based on preferred embodiments thereof. In the prediction method of the present invention, in the treatment of the cellulose-containing raw material using a container-driven medium mill device, the crystal of cellulose in the powder obtained by processing the cellulose-containing raw material by applying a predetermined drop energy to the mill device. Predict the conversion index. This prediction is based on the crystallization index (actual value) of cellulose in the powder obtained by pre-processing the cellulose-containing raw material with the mill apparatus under the predetermined conditions, and the dropped energy (calculated value) at the crystallization index. ). The thrown away energy (calculated value) is calculated from the unit time dissipated energy (calculated value) and the actual processing condition (actually measured value) using the mill device. The unit time dissipated energy is a unit time resulting from all collisions occurring in the mill device, which is calculated by simulating the motion of the non-spherical medium in the mill device by a discrete element method using a viscoelastic dynamic model. It is the dissipated energy.

  First, “cellulose-containing raw material”, “crystallization index”, and “calculation of crystallization index” used in this specification will be described.

[Cellulose-containing raw material]
The cellulose-containing raw material may be composed only of cellulose, or may be composed of cellulose and other components. Examples of other components include lignin. When the cellulose-containing raw material is composed of cellulose and other components, the cellulose content in the remaining components excluding water from the cellulose-containing raw material is preferably 20% by mass or more, more preferably 40% by mass or more. More preferably, it is 60% by mass or more. The cellulose content means the total amount of the cellulose content and the hemicellulose content in the cellulose-containing raw material.

  Cellulose-containing raw materials are not particularly limited, and various wood chips; pulps such as wood pulp produced from wood and cotton linter pulp obtained from fibers around cotton seeds; newspapers, cardboard, magazines, fine paper, etc. Papers: plant stems and leaves such as rice straw and corn stalks; powders made from plant shells such as rice husks, palm husks, and coconut husks are used as raw materials. In the case of commercially available pulp, the cellulose content in the remaining components excluding water is generally 75 to 99% by mass, and lignin and the like are included as other components. Moreover, the cellulose type I crystallization index in commercially available pulp is usually 60% or more. The water content in the cellulose-containing raw material is preferably 20% by mass or less, more preferably 15% by mass or less, and particularly preferably 10% by mass or less. If the water content in the cellulose-containing raw material is 20% by mass or less, the cellulose-containing raw material can be easily pulverized using a container drive medium mill device, and the crystallization index of cellulose can be easily reduced by the pulverization treatment. .

[Cellulose type I crystallization index]
The crystallization index is calculated by the Segal method from the diffraction intensity value by the X-ray diffraction method, and is defined by the following calculation formula (1).
Cellulose type I crystallization index (%) = [(I _22.6 −I _18.5 ) / I _22.6 ] × 100 (1)
Wherein, I _22.6, the lattice plane in X-ray diffraction (002 plane) indicates the diffraction intensity of the (diffraction angle 2θ = 22.6 °), I _18.5 is amorphous portion (angle of diffraction 2 [Theta] = 18.5 °) The diffraction intensity is shown. ]

  The cellulose in the powder produced using the prediction method of the present invention (hereinafter referred to as “cellulose-containing powder” for the sake of simplicity) preferably has a cellulose I-type crystallization index reduced to 33% or less. It is. If the cellulose I-type crystallization index is 33% or less, as described above, the chemical reactivity of cellulose is improved. For example, in the production of cellulose ether, alkali celluloseization easily proceeds when an alkali is added. As a result, the reaction conversion rate of the cellulose etherification reaction can be improved. In this respect, the cellulose I type crystallization index is preferably 30% or less, more preferably 20% or less, still more preferably 10% or less, and particularly preferably 0% or less in which no crystals are detected by X-ray diffraction. When the cellulose I-type crystallization index is 0% or less, it is preferably −10% or less, more preferably −20% or less, and still more preferably −30% or less.

[Calculation of cellulose type I crystallization index]
The cellulose I-type crystallization index is calculated based on the above calculation formula by measuring the X-ray diffraction intensity of the sample under the following conditions using “Rigaku RINT 2500VC X-RAY diffractometer” manufactured by Rigaku Corporation. The measurement conditions were as follows: X-ray source: Cu / Kα-radiation, tube voltage: 40 kV, tube current: 120 mA, measurement range: diffraction angle 2θ = 5-45 °. The measurement sample is obtained by compressing powder into pellets having an area of 320 mm ^{2 and a} thickness of 1 mm. The X-ray scanning speed was 10 ° / min.

  Next, a procedure for calculating unit time dissipated energy by simulation will be described. The prediction method of the present invention is characterized in that a non-spherical medium is used for processing a cellulose-containing raw material using a container-driven medium mill apparatus. Although the technique of the present invention can be applied to a spherical medium, the medium used in the examples of Patent Document 2 is a rod, and the use of a non-spherical medium increases the crystallization index of cellulose in a cellulose-containing powder. Since it is suggested that it can be lowered, the procedure for calculating the unit time dissipation energy when using a non-spherical medium will be described below. Note that this simulation predicts the motion of only the medium filled in the container-driven medium mill apparatus, and does not include prediction of phenomena such as particle collision and crushing.

  There is no particular limitation on the non-spherical medium used in the container drive medium mill apparatus, but a rod-shaped medium is used in the embodiment in Patent Document 1. The rod shape refers to a rod shape that is elongated in a uniaxial direction and has a cross-sectional shape that is the same at any position in a direction orthogonal to the direction. Examples of the cross-sectional shape of the rod-shaped medium include a circle, an ellipse, and a polygon such as a quadrangle and a hexagon. In the simulation in the present invention, a rod-shaped medium having a circular cross section is a target.

  In the present invention, the non-spherical medium is configured by superposing a plurality of spherical particles, and the collision motion of the non-spherical medium is simulated by the discrete element method. Specifically, as shown in FIG. 1, a rod-shaped medium M, which is a non-spherical medium, is configured by superposing a plurality of spherical particles S having the same diameter as the diameter of the cross-section in a straight line. Let it be conjugate C. Then, the collision motion of the rod-shaped medium M is simulated by applying a discrete element method using a viscoelastic dynamic model to the coupled body C. In the discrete element method, a dynamic model is adopted between particles, and forces acting on individual particles are calculated one by one. As a dynamic model to be adopted, a forked model is generally used, and this model is also adopted in the present invention. The forked model is a dynamic model expressed by an elastic spring, a viscous dashpot, and a friction slider.

  The simulation in the present invention can be performed by using, for example, commercially available software operating on a personal computer and giving various values described later as initial setting values. An example of such software is EDEM2.1 (trade name) manufactured by DEM solutions. Of course, an original program may be created and simulated.

  This simulation is performed according to the flowchart shown in FIG. The flowchart shown in the figure is roughly divided into (1) setting unit, (2) calculation unit, and (3) physical quantity calculation unit. Below, the detail of these each part is demonstrated.

  In the setting unit (1), an initial state for performing a simulation is set. First, the three-dimensional shape of the grinding cylinder of the container drive medium mill device is set. The container drive medium mill device is a device that moves the medium in the pulverization cylinder by vibrating the drum-shaped pulverization cylinder in which the pulverization medium (rod-shaped medium in this embodiment) is inserted. It is called a mill. In this simulation, the grinding cylinder is vibrated in the horizontal and vertical directions with a total amplitude of 8 (mm) and a rotational speed of 1200 (rpm), and the phase difference between the horizontal and vertical vibrations is π / 2. Furthermore, in order to obtain the recoil motion and energy loss when the particles collide with the inner wall of the mill, it is necessary to set the material of the inner wall of the mill device. As the physical property values characterizing the material of the inner wall, the elastic modulus, Poisson's ratio and density of the inner wall are set.

  In the setting part of (1), particle physical property parameters are also set. The term “particle” used herein refers to the spherical particle S shown in FIG. In the particle physical property parameter setting, basic parameters for automatically calculating various macro physical property values such as mass, volume, moment and the like of the bonded body C shown in FIG. 1 on software are set. Specific parameters to be set include the radius of the particle, the position of the particle in the bonded body C, and the material of the particle. Elastic properties, Poisson's ratio and density are set as physical property values characterizing the material of the particles.

  Further, in the setting unit (1), interaction parameters between the spherical particles S and the spherical particles S are set. The interaction parameter between the spherical particle S and the inner wall of the mill is also set. As the interaction parameter, values of a restitution coefficient, a static friction coefficient, and a rotational friction coefficient are set. These interaction parameters are set separately between the spherical particle S and the spherical particle S and between the spherical particle S and the inner wall of the mill. The coefficient of restitution is determined by dropping the target spherical particle S on a flat plate and reproducing the motion. The static friction coefficient and the rotational friction coefficient are determined by filling the spherical particles S into the mill device and reproducing the lift angle (rest angle) of the spherical particles S when the mill device is driven. If the material of the spherical particles S is a metal or ceramics such as iron or stainless steel, some candidate values are described in the patent literature and papers from the conventional studies. It may be used as a coefficient.

  Subsequently, the shape of the combined body C (see FIG. 1) adapted to the rod-shaped medium is set. As described above, the combined body C is obtained by approximating a rod-shaped medium in a shape in which spherical particles S are connected in a row. When the number of spherical particles to be combined is increased, the shape of the combined body C approaches a rod shape. This has a positive effect in that the accuracy of the simulation is improved. However, increasing the number N of spherical particles S to be combined has a disadvantage that the calculation load of simulation increases. Further, as described above, it is also known that the number of contact points of the spherical particles S in contact with the number N of the spherical particles S constituting the combined body C changes, and the simulation result changes greatly. Furthermore, when considering multiple collisions with a plurality of irregularly shaped media, it is necessary to obtain the number of contact points for each collision in advance, and therefore it is necessary to perform a calculation that exactly reproduces the individual movements of the irregularly shaped media. However, this calculation is very labor intensive. Therefore, in this simulation, the concept of average contact number m is introduced in order to easily and appropriately obtain physical quantities of collision energy and dissipation energy. When handling time average and statistical average physical quantities such as collision energy and dissipated energy from the motion of multiple media in the mill device of interest in this simulation, each number of contact points is not required for each collision. By giving the average number of contact points as the average value of the number of contact points in the collision, it is considered that the object of the present invention can be met without strictly obtaining the number of contact points of each collision. Furthermore, the minimum value of the number N of spherical particles S to be combined can be determined by using this average number of contacts. This concept has been introduced for the first time in the present invention and has not been used in the conventionally known Multi-Sphere DEM method.

The average contact number m is the average number of contact of the spherical particles S constituting the combined body C when the combined bodies C collide with each other and the combined body C and the inner wall of the mill collide with each other. In other words, it is the number of artificial contact points generated by approximating the rod-shaped medium M with the combined body C of the spherical particles S, and means that the number of contact points different for each collision is represented by a certain value m. . The average contact number m is determined by the following procedures (a) to (c) together with the number N of spherical particles S constituting the bonded body C. The order of (a) and (b) may be reversed.
(A) Calculation of unit time dissipated energy.
(B) Actual measurement of power consumption of the mill device.
(C) Determination of the average number of contacts m and the number N of spherical particles by comparing unit time dissipated energy and power consumption.

  In the above (a), the unit time dissipated energy is calculated by simulation. The unit time dissipated energy is a value obtained by dividing the energy generated by collision between media and collision between the media and the mill inner wall by unit time when operating a mill device filled with multiple media. It is a virtual value calculated by The unit time dissipated energy is expressed in W (watts).

  In order to calculate the unit time dissipated energy, an initial value of the number N of spherical particles constituting the combined body C is determined. The number N of spherical particles is a natural number satisfying N ≧ L / 2a, where L is the length of the rod-shaped medium and a is the radius. The radius of the spherical particle is of course a. When the distance between adjacent spherical particles, that is, the degree of overlap between adjacent spherical particles is Δx as shown in FIG. 3, the length L of the rod-shaped medium is expressed by L = 2a + Δx (N−1). Is done.

In this simulation, the unit time dissipation energy of each combination C is calculated by setting a number N of the spherical particles S of the combination C, and the behavior of the unit time dissipation energy with respect to the number N of the spherical particles S is calculated. It is important to seek. Specifically, the unit time dissipated energy needs to converge to a constant value as the number N of spherical particles S increases. For example, _n1 initial values N = N ₁ , N ₂ ,..., N _n1 can be determined. Then, an average contact number m is determined for each of n1 types of conjugates C having different numbers of spherical particles. For each combination C, it is necessary to set a plurality of average contact numbers m, and the calculated unit time dissipated energy needs to obtain an average contact number m that reproduces an actual measurement value of power consumption of the mill device.

  As described above, n2 average contact number m is given as an initial value for each of n1 types of conjugates C. That is, there are n1 × n2 combinations of initial values of N and m. For the n1 × n2 combinations, the unit time dissipation energy is calculated by the calculation unit described below (a specific calculation method will be described later). In the calculation, the number of rods and the initial value of the mill operation condition in the setting unit (1) in the flowchart shown in FIG. 2 are also set (this will also be described later). As the unit time dissipated energy, n1 × n2 values are calculated.

  In said (b), the mill apparatus used as the basis of the simulation of (a) is actually operated, and the power (W) during operation is measured. Specifically, a predetermined number of rod-shaped media are filled in the mill apparatus, and the mill apparatus is operated. The rod-shaped medium used has a length L and a radius a which are initial values used in the simulation of (a). The number of rod-shaped media is set to the value set as the initial value of the simulation. Examples of the mill device to be used include a vibration mill manufactured by Chuo Kako Co., Ltd., a vibro mill manufactured by Eurus Techno Co., Ltd., a small vibrating rod mill 1045 model manufactured by Yoshida Seisakusho Co., Ltd., and a vibration cup mill P-9 model manufactured by Fritsch, Germany A small vibration mill NB-O type manufactured by Nippon Ceramics Co., Ltd. can be used.

  Separately from the above operation, the idling power (W) is measured by idling the mill device without filling the rod-shaped medium. The operating conditions are the same as those described above except that the rod-shaped medium is not filled. Then, the power consumption (W) is calculated from the equation of power during operation (W) -idle power (W). This power consumption (W) is regarded as energy generated by the collision between rod-shaped media and the collision between the media and the mill inner wall.

  In (c), the n1 × n2 unit time dissipated energy (W) calculated in (a) is compared with the power consumption (W) actually measured in (b). This comparison may be performed as part of a simulation using a personal computer, or may be performed manually separately from the simulation. Then, among the n1 × n2 unit time dissipated energies, a combination of N and m that matches the power consumption of the mill device within an error of 10% is selected. The error is obtained by | unit time dissipated energy−power consumption | ≦ power consumption × 0.1. The selected combination of N and m is the number N of spherical particles and the average number of contacts m in the target conjugate C. When there are two or more selected combinations of N and m, the combination with the smallest error may be further selected.

  The setting of the number of rods and the mill operation condition in the setting unit (1) in the flowchart shown in FIG. 2 is performed as follows. The number of rods is set to an appropriate value according to the thickness of the rod-shaped medium and the dimensions of the mill. The number of rods is the same as the number of rod-shaped media used when the power (W) during operation is measured in the actual operation of the above-described mill apparatus. As operating conditions of the mill, for example, it is necessary to set the total amplitude (mm) and the rotation speed (rpm) when the mill apparatus is operated. In this simulation, the grinding cylinder is vibrated in the horizontal and vertical directions with a total amplitude of 8 (mm) and a rotational speed of 1200 (rpm). The phase difference between the vibrations in the horizontal direction and the vertical direction is π / 2.

  Next, the process of the calculation unit (2) in the flowchart shown in FIG. 2 is executed. Specifically, based on the set values that have been set up to now, a set number of combined bodies C are installed in a stationary state in the mill apparatus. The installation position of the combination C is determined by generating a random number. Therefore, the exact installation position (coordinates) of the combination C is not determined until the actual calculation starts (the number of rods to be arranged is set even when the rods are actually arranged in the mill device, but The initial position cannot be specified). Further, at this time, since each conjugate C is stationary, the velocity and acceleration of the spherical particles constituting the conjugate C are both zero. Also, the dissipated energy at this point is zero.

  Next, the calculation is started based on the given set value. The actual mill device moves (rolling, vibrating, and planetary motion) based on this set value. Since there is a frictional force between the rod-shaped medium and the inner wall of the mill, the rod-shaped medium also moves according to the movement of the mill device. The rod-shaped medium moves based on its own weight and moment of inertia. As a result, a collision between rod-shaped media and a collision between the rod-shaped medium and the inner wall of the mill occur. Due to these collisions, the rod-shaped medium recoils based on the laws of physics. These collisions are generally inelastic collisions in which a part of the collision energy is changed to thermal energy. This thermal energy is the dissipative energy described above. In this simulation, the unit time dissipated energy is calculated by the physical quantity calculator (3) in the flowchart shown in FIG.

  The calculation in the calculation unit of (2) is the same as the calculation by the multi-sphere DEM method known so far. Specifically, each time the minute time Δt elapses from the stationary state, the position (coordinates) of each combination C is calculated, and whether each combination C is in contact with another combination C or the inner wall of the mill. Determine. When the bond C is in contact with another bond C or the inner wall of the mill, the force F and moment M are calculated for the bond C. The calculation of the force F and the moment M is calculated from the model diagram shown in FIG.

This expression represents the force F and the moment M due to the bonded body C coming into contact with the bonded bodies or the inner wall of the mill during the time t + Δt when a minute time Δt has elapsed from a certain time t. The subscript i in the above formula and FIG. 4 represents the i-th conjugate. k is the number of the spherical particle when the rod-shaped medium is approximated by a plurality of spherical particles. l represents a contact point between the bonded bodies or between the bonded body and the inner wall of the mill. The point l at which the spherical particle k contacts the bonded body or the inner wall of the mill is determined by sequentially tracking the movement of the bonded body by numerical calculation. In this equation, j _ikl represents the number of artificial contact points generated from the Multi-Sphere DEM method. For example, when rod-like particles such as rods collide with each other in parallel, when the number of bonds constituting the rod increases, the number of contact points at the time of collision increases with the increase, and the force F acting on the coupled particles increases. _Therefore , it is necessary to divide by the number of artificial contact points j _ikl . Therefore, originally, when calculating force and moment, it is necessary to obtain the number of contact points j _ikl for each collision in advance. However, it is _strictly necessary to obtain the number of artificial contact points in advance for each collision of an irregularly shaped medium. The calculation is very labor intensive. In order to solve this problem, it is a feature of the present invention that a constant value is given in advance as the number of contact points j _ikl = average number of contacts m.

In FIG. 4 and FIG. 4, F _ikl represents the force received by the spherical particles k constituting the combination i when the combination i comes into contact with the inner wall of the mill or another combination at the point l. . x _ikl represents the position (coordinates) when the spherical particle k constituting the combined body i comes into contact with the inner wall of the mill or another combined body at the point l. x _ik represents the position of the center of gravity of the spherical particle k when the spherical particle k constituting the combined body i contacts the inner wall of the mill or another combined body at a point l. x _i represents the position of the center of gravity of the combination i. M represents the number of spherical particles constituting the combined body i related to the collision. M _N represents the total number of contact points at which the spherical particles k related to the collision contact the bonded body or the inner wall of the mill. F _ikl , x _ikl , x _ik , x _i , M and M _N are determined by numerically calculating the motion of the conjugate sequentially.

  When the force received by the combined body C is calculated by the above procedure, the position of the combined body C can be specified from the model diagram shown in FIG. The following equation is based on Newton's equation of motion. Thereby, the position of the combination C at each time can be obtained.

Finally, processing in the physical quantity calculation unit (3) in the flowchart shown in FIG. As a result of tracking the position of the conjugate C, when collision occurs between the conjugate i ₁ and the conjugate i ₂ at time t → t + Δt, the collided spherical particles in the conjugate i ₁ and the conjugate i ₂ Since k ₁ and k ₂ are the radius of the spherical particle a, the overlap δ, that is, the movement distance between the spherical particle k ₁ and the spherical particle k ₂ is expressed by the following equation.

If the viscosity term of the force acting when the combined body i ₁ and the combined body i ₂ collide is Fv, the unit time dissipated energy resulting from the collision is calculated as δ × Fv. Therefore, the target unit time dissipation energy Σδ × Fv is calculated by adding all the unit time dissipation energy for each collision.

  As described above, the processing in the physical quantity calculation unit (3) in the flowchart shown in FIG. 2 is completed. The unit time dissipated energy is obtained by the above processing, and the dropped dissipated energy is calculated by the method described later from the unit time dissipated energy and the conditions when the cellulose-containing raw material is actually processed using a mill apparatus. The measurement of the crystallization index of cellulose in the cellulose-containing powder obtained by the treatment is to extract a very small amount of powder that is not in the middle of the treatment (about 1 g with respect to the amount for 100 g preparation) that does not affect the total amount. Do it. Thereby, the relationship of the crystallization index of cellulose with respect to the treatment time can be obtained. In order to increase the accuracy of the data, the same experiment may be performed a plurality of times.

For example, when processing using a mill apparatus is performed in a batch type, the following formula (from the processing time (h) and the charged amount (kg) and the unit time dissipated energy (W), which are the conditions of the batch type processing, Calculate the dissipated energy (Wh / kg) according to I). Calculations using this equation are performed for the number of processing conditions.
Dissipated energy (Wh / kg) = Dissipated energy per unit time (W) x Processing time (h) / Charged amount (kg) (I)

When processing using a mill apparatus is performed continuously, the following formula (II) is used from the feed amount per hour (kg / h) and the unit time dissipated energy (W) which are the conditions for the continuous processing. Calculate the energy dissipated. Calculations using this equation are performed for the number of processing conditions.
Dissipated energy (Wh / kg) = Dissipated energy per unit time (W) / Feed amount per hour (kg / h) (II)
Here, the feed amount per hour means the amount of charge divided by the time from when the powder is charged until it is discharged.

  Through the above processing, the thrown-off energy by simulation is calculated for each crystallization index of cellulose in the cellulose-containing powder. Next, a correlation between the calculated dropped energy and the crystallization index of cellulose in the cellulose-containing powder is obtained. This operation may be performed by plotting, for example, the dropped dissipation energy and the crystallization index of cellulose in the powder obtained according to the processing conditions used when calculating the dropped dissipation energy. An example of such a graph is shown in FIG. This figure is the result of an example described later. As is clear from the figure, it can be seen that the crystallization index of cellulose decreases (that is, becomes amorphous) as the dropped energy dissipation increases.

  Using the graph showing the correlation between the dropped dissipation energy and the crystallization index thus obtained, it is possible to predict the crystallization index of cellulose when it is assumed that a predetermined dropped dissipation energy is given to the mill apparatus. Therefore, if the graph is prepared by an experiment using a small mill device, for example, when certain operating conditions are determined, the crystallization index of cellulose in the cellulose-containing powder obtained under the conditions is expressed as time and Prediction can be easily performed without much effort.

  The above method is for predicting the crystallization index of cellulose when a predetermined drop energy is given to the mill device. In addition to this, according to the present invention, the cellulose-containing raw material is used in the mill device. It is also possible to predict the dropped energy dissipated to reduce the crystallization index of cellulose in the cellulose-containing powder obtained by the treatment to the target value. For example, when scaling up the amorphization process using a large-scale mass production type mill device, the drop-off energy suitable for obtaining a cellulose-containing powder having the desired crystallinity is set as described above. It can be easily predicted using a graph showing the correlation between the drop energy dissipated and the crystallization index. Then, by processing the cellulose-containing raw material using a mill apparatus set to the processing conditions that generate the predicted dropped dissipation energy, it is possible to easily obtain a cellulose-containing powder having a crystallization index reduced to a target value. it can.

  As mentioned above, although this invention was demonstrated based on the preferable embodiment, this invention is not restrict | limited to the said embodiment. For example, in the above-described embodiment, the simulation in the case where a rod-shaped medium is used as the non-spherical medium has been described as an example. Can be applied to.

  Hereinafter, the present invention will be described in more detail with reference to examples. However, the scope of the present invention is not limited to such examples. Unless otherwise specified, “%” means “mass%”.

(1) Amorphization treatment of cellulose in a cellulose-containing raw material using a small laboratory machine [1-1 cutting treatment]
As a cellulose-containing raw material, sheet-like wood pulp [HV +, manufactured by Tenbeck, 800 mm × 600 mm × 1 mm, crystallization index 81.5%, cellulose content (the amount in the remaining components excluding water from the cellulose-containing raw material, the same shall apply hereinafter) 96.0%, water content 8.5%]. This was applied to a sheet pelletizer (“SG (E) -220” manufactured by Horai Co., Ltd.) to make a chip-like pulp of about 4 mm × 4 mm × 1 mm.
[1-2 drying treatment]
Using a shelf dryer (ADVANTEC vacuum low-temperature dryer “DRV320DV”), the moisture content of the pulp after drying is 1.0%. Dried. The crystallization index of cellulose in the pulp after the drying treatment was 82% calculated from the X-ray diffraction intensity.
[1-3 Vibration mill treatment]
The pulp after the drying treatment was put into a vibration mill (manufactured by Chuo Kako Co., Ltd., “MB-1”, container total capacity 3.6 liter, mill diameter 142 mm, length in the longitudinal direction 226 mm). As the rod-shaped medium, 13 rods having a radius of 15 mm, a length of 211 mm, a stainless steel material, and a circular cross-sectional shape were used and filled in a vibration mill. Amorphization treatment was performed under conditions of a total amplitude of 8 (mm) and a rotational speed of 1200 (rpm). Five kinds of powders having different crystallization indexes of cellulose were obtained by changing the treatment time. Specifically, 100 g of pulp was charged and treated for 10 minutes, 20 minutes, 30 minutes, 45 minutes and 60 minutes, respectively. The crystallization index of cellulose in the cellulose-containing powder obtained by the treatment was determined from the X-ray diffraction intensity.

(2) Calculation of power consumption of vibration mill The vibration mill used in the above (1) is filled with the 13 rods used in the above (1) and operated under the above condition (1). The power during operation was measured. Next, 13 rods were taken out and idle running under the same conditions, and the idling power was measured. Then, the idling power was subtracted from the driving power, and the obtained value was defined as the power consumption (W) of the vibration mill. This value was 268.2W.

(3) Calculation of unit time dissipated energy The program according to the flowchart shown in FIG. 2 was executed on a personal computer, and unit time dissipated energy was calculated by simulation. In the simulation, the number N of spherical particles having a radius of 15 mm in the combined body C was set to four types of 15, 22, 31, and 43. Further, the average contact number m was set to three types: 1, N / 2, and N. That is, combinations of the number N of spherical particles and the average contact number m were 4 × 3 = 12. The unit time dissipated energy was calculated for each of these 12 combinations. The results are shown in Table 1 below. The table also shows the power consumption of the vibration mill calculated in (2) above. As is clear from the results shown in the table, among the combinations of the number N of spherical particles and the average number of contacts m, the one closest to the power consumption of the vibration mill was N = 31 and m = 31. Therefore, it was decided to adopt a combination C in which 31 spherical particles are connected in a straight line. The average number of contacts was 31. The unit time dissipated energy at this time was 273.8 W as shown in the table.

(4) Calculation of dropped dissipation energy and correlation with cellulose crystallization index in cellulose-containing powders The unit time dissipation energy obtained in (3) above and the cellulose amorphization treatment in (1) above. From the treatment time and the charged amount, the drop dissipation energy in each crystallization index was calculated according to the above formula (I), the calculated drop dissipation energy, and the crystallization index of cellulose in the cellulose-containing powder at that time From this, a graph showing the correlation between the two was created. This is shown in FIG.

(6) Verification with actual measurement value It was verified to what extent the result shown in FIG. For verification, in addition to “MB-1” manufactured by Chuo Kako Co., Ltd., which is the batch type vibration mill used in the above (1), the batch type vibration mill “FV-20” (mill volume 68. 9 liters, mill diameter 382.4 mm), continuous vibration mill “CD-25” (pod volume 58.6 liters × 2, mill diameter 236.0 mm) and continuous vibration mill “MC-15” (pod volume 15. 5 liters × 2, mill diameter 146.0 mm) was used. Depending on the device, it is important to match the center of the vibration source and the center of gravity of the mill in order to obtain stable vibration, and there are some devices in which two pots are connected. Using the pulp used in the above (1) as a raw material, an amorphous cellulose-containing powder was obtained using these vibration mills. The crystallization index of cellulose in the obtained cellulose-containing powder was measured, and the relationship with the dropped dissipation energy at that time was plotted on a graph. The dissipated dissipated energy regards the power consumption (W), which is the value obtained by subtracting the idling power from the operating power in these vibration mills, as the unit time dissipated energy, and this is expressed by formula (I) or formula (II) Was applied. The results are shown in FIG.

  As is clear from the comparison of the results shown in FIG. 6 and FIG. 7, the relationship between the crystallization index obtained according to the present invention and the dropped dissipation energy is the relationship between the crystallization index obtained by actual measurement and the dropped dissipation energy. It can be seen that there is a very good agreement.

M Rod-shaped medium S Spherical particle C Spherical particle combination

Claims (9)

A method for predicting a crystallization index of cellulose in a powder obtained by processing a cellulose-containing raw material using a container-driven medium mill device,
The non-spherical medium in the mill apparatus is composed of a combined body in which a plurality of spherical particles are superposed, and the motion of the combined body is simulated by a discrete element method using a viscoelastic dynamic model, thereby Calculate the unit time dissipated energy due to all collisions occurring in
The cellulose crystallization index in the powder obtained by processing the cellulose-containing raw material by the mill apparatus under predetermined conditions is measured in advance, the crystallization index, the unit time dissipation energy, and the mill apparatus. Find the correlation with the dissipated energy calculated from the processing conditions using
Based on the correlation between the crystallization index and the dropped dissipation energy, cellulose is used to predict the crystallization index of cellulose in the powder when the cellulose-containing raw material is processed by applying a predetermined dropped dissipation energy to the mill device. Of predicting the crystallization index of The prediction method according to claim 1, wherein the non-spherical medium is configured by a combined body in which a plurality of spherical particles are arranged in a straight line and the motion of the combined body is simulated by a discrete element method. The prediction method according to claim 2 non-spherical media is rod-shaped.   The average energy contact number of the spherical particles in the combined body in the collision between the combined bodies and in the collision between the combined body and a mill inner wall is obtained in advance, and the dropped dissipation energy is calculated. Prediction method.   The average number of contacts is determined so that the unit time dissipated energy resulting from the collision between the combined bodies and the collision between the combined bodies and the inner wall of the mill matches the power consumption of the mill apparatus within 10% error. 4. The prediction method according to 4. The processing using the mill apparatus is performed in a batch system, and the dropped energy dissipation is calculated by the following formula (I) from the processing time and preparation amount, which are the conditions of the batch processing, and the unit time energy dissipation. The prediction method according to claim 1.
Dissipated energy = unit time dissipated energy x processing time / amount charged (I) The processing using the mill apparatus is performed continuously, and the dropped energy dissipation is calculated by the following equation (II) from the feed amount per hour which is the condition of the continuous processing and the unit time energy dissipation. The prediction method according to claim 1.
Dissipated energy = unit time dissipated energy / feed amount per hour (II) This is a method for predicting dropped energy, which processes the cellulose-containing raw material using a container-driven medium mill and predicts the dropped energy required to reduce the crystallization index of cellulose to the target value in the powder obtained by the treatment. There,
The non-spherical medium in the mill apparatus is composed of a combined body in which a plurality of spherical particles are superposed, and the motion of the combined body is simulated by a discrete element method using a viscoelastic dynamic model, thereby Calculate the unit time dissipated energy due to all collisions occurring in
The cellulose crystallization index in the powder obtained by processing the cellulose-containing raw material by the mill apparatus under predetermined conditions is measured in advance, the crystallization index, the unit time dissipation energy, and the mill apparatus Find the correlation with the dissipated energy calculated from the processing conditions used,
A method for predicting dropped energy, which predicts dropped energy required for reducing the crystallization index of cellulose in the powder to a target value based on the correlation between the crystallization index and the dropped energy. A method of producing a powder in which a cellulose-containing raw material is processed using a container-driven medium mill device, and a crystallization index of cellulose is reduced to a target value,
Using the prediction method according to claim 8, predicting the dissipated dissipation energy required for the crystallization index of the cellulose in the powder to decrease to the target value,
A method for producing a powder, in which a cellulose-containing raw material is processed using the mill apparatus set to a processing condition in which the predicted dropped dissipation energy is generated.