CN111310911A - Device, method, medium, photosensitive resin composition, and method for producing laminate - Google Patents
Device, method, medium, photosensitive resin composition, and method for producing laminate Download PDFInfo
- Publication number
- CN111310911A CN111310911A CN201911090042.8A CN201911090042A CN111310911A CN 111310911 A CN111310911 A CN 111310911A CN 201911090042 A CN201911090042 A CN 201911090042A CN 111310911 A CN111310911 A CN 111310911A
- Authority
- CN
- China
- Prior art keywords
- composition
- photosensitive resin
- resin composition
- data
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
- G03F7/004—Photosensitive materials
-
- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
- G03F7/004—Photosensitive materials
- G03F7/027—Non-macromolecular photopolymerisable compounds having carbon-to-carbon double bonds, e.g. ethylenic compounds
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Biomedical Technology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Polymerisation Methods In General (AREA)
- Exposure And Positioning Against Photoresist Photosensitive Materials (AREA)
- Materials For Photolithography (AREA)
Abstract
The invention provides a device, a method, a medium, a photosensitive resin composition and a method for manufacturing a laminated body, aiming at solving the problem of poor efficiency of composition obtained by repeated tests. The device provided by the invention comprises: a composition acquisition unit that acquires composition data indicating a composition of the photosensitive resin composition; a characteristic acquisition unit that acquires characteristic data indicating characteristics of the photosensitive resin composition; and a learning processing section that performs learning processing of a model for outputting recommended composition data representing a composition of the recommended photosensitive resin composition in response to input of target characteristic data representing a characteristic of the photosensitive resin composition as a target, using learning data including the acquired composition data and characteristic data.
Description
Technical Field
The present invention relates to a device, a method, a program, a method for producing a photosensitive resin composition, and a method for producing a photosensitive resin laminate.
Background
Conventionally, in the case of producing a photosensitive resin composition, a preferable composition has been found by trial and error by a skilled operator in order to obtain desired characteristics (for example, see patent document 1).
Patent document 1: japanese patent laid-open publication No. 2017-114080
Disclosure of Invention
Problems to be solved by the invention
However, the efficiency of obtaining the composition by trial and error is poor.
Means for solving the problems
In order to solve the above problem, the present invention provides, in claim 1, an apparatus. The apparatus may include a composition acquisition unit that acquires composition data indicating a composition of the photosensitive resin composition. The apparatus may include a characteristic acquisition unit that acquires characteristic data indicating characteristics of the photosensitive resin composition. The apparatus may include a learning processing section that performs learning processing of a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of target characteristic data representing a characteristic of a target photosensitive resin composition, using learning data including the acquired composition data and characteristic data.
In the 2 nd aspect of the present invention, there is provided an apparatus. The apparatus may include a target property acquisition unit that acquires target property data indicating a property of a target photosensitive resin composition. The apparatus may include a target characteristic supply unit that supplies the target characteristic data acquired by the target characteristic acquisition unit to a model for outputting recommended composition data indicating a recommended composition of the photosensitive resin composition in response to input of the target characteristic data. The apparatus may be provided with a recommended composition acquisition section that acquires recommended composition data that is output by the model in response to the supply of the target characteristic data to the model.
In embodiment 3 of the present invention, a method is provided. The method may include a composition acquisition phase as follows: composition data indicating the composition of the photosensitive resin composition was obtained. The method may comprise a property acquisition phase of: characteristic data representing the characteristics of the photosensitive resin composition is acquired. The method may comprise the following learning processing stages: learning processing of a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of target characteristic data representing characteristics of the photosensitive resin composition as a target is performed using learning data including the acquired composition data and characteristic data.
In the 4 th aspect of the present invention, a method is provided. The method may comprise a target property acquisition phase of: target property data indicating the properties of the target photosensitive resin composition is acquired. The method may comprise a target property supply phase of: target characteristic data acquired by a target characteristic acquisition stage is supplied to a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of the target characteristic data. The method may comprise a recommendation composition acquisition phase as follows: recommended composition data output by the model in response to the supply of the target characteristic data to the model is acquired.
The invention provides a method for producing a photosensitive resin composition according to claim 5. The manufacturing method may comprise the following stages: the composition of the photosensitive resin composition is determined based on the recommended composition data obtained by the method of embodiment 4. The manufacturing method may comprise the following stages: raw materials for producing the photosensitive resin composition are mixed.
The present invention provides, in accordance with claim 6, a method for producing a photosensitive resin laminate. The manufacturing method may comprise the following stages: the fluid of the photosensitive resin composition obtained by mixing by the production method of embodiment 5 is applied to a base film. The manufacturing method may comprise the following stages: a cover film is provided on the applied photosensitive resin composition.
In the 7 th aspect of the present invention, there is provided a program. The program may cause the computer to function as a composition acquisition section that acquires composition data indicating the composition of the photosensitive resin composition. The program may cause the computer to function as a characteristic acquisition section that acquires characteristic data indicating the characteristics of the photosensitive resin composition. The program may cause the computer to function as a learning processing section that executes learning processing of a model for outputting recommended composition data indicating a recommended composition of the photosensitive resin composition in response to input of target characteristic data indicating characteristics of the target photosensitive resin composition, using learning data including the acquired composition data and characteristic data.
In the 8 th aspect of the present invention, there is provided a program. The program may cause the computer to function as a target property acquisition unit that acquires target property data indicating a property of the target photosensitive resin composition. The program may cause the computer to function as a target property supplying section that supplies the target property data acquired by the target property acquiring section to a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of the target property data. The program may cause the computer to function as a recommended composition acquisition section that acquires recommended composition data that is output by the model in response to the target characteristic data being supplied to the model.
In the 9 th aspect of the present invention, there is provided a storage medium. The storage medium stores a program that realizes the following stages when executed by a computer: a composition acquisition step of acquiring composition data indicating the composition of the photosensitive resin composition; a characteristic acquisition step of acquiring characteristic data representing the characteristics of the photosensitive resin composition; and a learning processing stage of performing learning processing of a model for outputting recommended composition data representing a composition of the recommended photosensitive resin composition in response to input of target characteristic data representing a characteristic of the photosensitive resin composition as a target, using learning data including the acquired composition data and characteristic data.
In a 10 th aspect of the present invention, there is provided a storage medium. The storage medium stores a program that realizes the following stages when executed by a computer: a target characteristic acquisition step of acquiring target characteristic data indicating characteristics of a target photosensitive resin composition; a target characteristic supply step of supplying the target characteristic data acquired by the target characteristic acquisition step to a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of the target characteristic data; and a recommended composition acquisition phase of acquiring recommended composition data output by the model in response to the supply of the target characteristic data to the model.
The above summary of the present invention does not necessarily list all the essential features of the present invention. In addition, a sub-combination of these feature groups can also constitute the invention separately.
Drawings
Fig. 1 shows a system 1 according to the present embodiment.
Fig. 2 illustrates a learning method of the model 35.
Fig. 3 shows a method for producing a photosensitive resin composition using a mold 35.
Fig. 4 illustrates a method of using the dry film 100.
FIG. 5 illustrates an example of a computer 2200 in which aspects of the invention may be embodied, in whole or in part.
Description of the reference numerals
1: a system; 2: a manufacturing device; 3: a learning processing device; 20: a mixing section; 21: a generation unit; 32: an acquisition section; 33: a characteristic acquisition unit; 34: a learning processing unit; 35: a model; 36: a target characteristic acquisition unit; 37: a target characteristic supply unit; 38: a recommended composition acquisition unit; 39: a control unit; 100: drying the film; 101: covering the film; 200: a substrate; 201: an insulating plate; 202: copper foil; 203: a copper wire; 300: a mask; 2200: a computer; 2201: a DVD-ROM; 2210: a main controller; 2212: a CPU; 2214: a RAM; 2216: a graphics controller; 2218: a display device; 2220: an input/output controller; 2222: a communication interface; 2224: a hard disk drive; 2226: a DVD-ROM drive; 2230: a ROM; 2240: an input/output chip; 2242: a keyboard.
Detailed Description
The present invention will be described below with reference to embodiments thereof, but the following embodiments do not limit the invention according to the claims. In addition, all combinations of features described in the embodiments are not necessarily essential to the solution of the invention.
[1. System ]
Fig. 1 shows a system 1 according to the present embodiment. The system 1 includes a photosensitive resin composition production apparatus 2 and a learning processing apparatus 3. The photosensitive resin composition may be photocurable or light-soluble (photodegradable or light-softening). The photosensitive resin composition may be in the form of a film, and in this case, the photosensitive resin composition is also referred to as a dry film. In the present embodiment, the photosensitive resin composition may be formed in a roll shape by laminating and winding a base film (carrier film, support film) and a cover film for easy storage and transportation, and in this case, the rolled laminate is also referred to as a photosensitive resin laminate (dry film roll, dry film resist roll).
[1-1. production apparatus ]
The manufacturing apparatus 2 is used for manufacturing a photosensitive resin composition. For example, the manufacturing apparatus 2 may have: a mixing section 20 for mixing the raw materials of the photosensitive resin composition to form a fluid of the photosensitive resin composition; and a generating section 21 for generating a photosensitive resin laminate from the fluid of the photosensitive resin composition. The generating section 21 may include a filter section for filtering a raw material, an application section for applying a fluid of the photosensitive resin composition to a base film to form the photosensitive resin composition into a film shape, a roller section for providing (as an example, attaching) a cover film on the applied photosensitive resin composition and winding the laminate, and the like.
[1-2. learning processing device ]
The learning processing device 3 is an example of a device. The learning processing device 3 performs learning processing of a model 35, and includes a composition acquisition unit 32, a characteristic acquisition unit 33, a learning processing unit 34, and a model 35. The learning processing device 3 also performs an operation of the model 35, and includes a target characteristic acquisition unit 36, a target characteristic supply unit 37, a recommended composition acquisition unit 38, and a control unit 39.
[1-2-1. composition acquisition part ]
The composition acquisition unit 32 acquires composition data indicating the composition of the photosensitive resin composition. The composition acquisition unit 32 can acquire composition data of the photosensitive resin composition manufactured by the manufacturing apparatus 2. The composition acquisition portion 32 may supply the acquired composition data to the learning processing portion 34.
[1-2-2. characteristic obtaining section ]
The characteristic acquiring unit 33 acquires characteristic data indicating the characteristics of the photosensitive resin composition. The characteristic acquiring unit 33 can acquire characteristic data of the photosensitive resin composition manufactured by the manufacturing apparatus 2. The characteristic acquisition unit 33 may supply the acquired characteristic data to the learning processing unit 34. In the present embodiment, the characteristic acquisition unit 33 acquires characteristic data from an operator, for example.
[1-2-3. learning processing section ]
The learning processing unit 34 executes learning processing of the model 35 using the input learning data. The learning data may include composition data from the composition acquisition portion 32 and characteristic data from the characteristic acquisition portion 33.
[1-2-4. model ]
The model 35 is configured to output recommended composition data indicating a recommended composition of the photosensitive resin composition in response to input of target characteristic data indicating a characteristic of the photosensitive resin composition as a target. Further, the model 35 may be stored in a server outside the learning processing apparatus 3.
[1-2-5. target characteristic obtaining section ]
The target property acquiring unit 36 acquires target property data indicating the properties of the target photosensitive resin composition. In the present embodiment, the target characteristic acquisition unit 36 acquires target characteristic data from an operator, for example. The target characteristic acquiring section 36 may supply the acquired target characteristic data to the target characteristic supplying section 37.
[1-2-6. target Property supply section ]
The target characteristic supply unit 37 supplies the model 35 with the target characteristic data from the target characteristic acquisition unit 36.
[1-2-7. recommended composition acquisition section ]
The recommended composition acquisition section 38 acquires recommended composition data output by the model 35 in response to the target characteristic data being supplied to the model 35. The recommended composition acquisition unit 38 may supply the acquired recommended composition data to the control unit 39. The recommended composition acquisition unit 38 may output the recommended composition data to the outside of the learning processing device 3.
[1-2-8. control section ]
The control unit 39 supplies the control condition data to the manufacturing apparatus 2, thereby causing the manufacturing apparatus 2 to operate under the control conditions indicated by the control condition data. For example, the control unit 39 may cause the mixing unit 20 of the manufacturing apparatus 2 to mix the raw materials to manufacture the photosensitive resin composition in the composition indicated by the recommended composition data by supplying the recommended composition data to the manufacturing apparatus 2.
According to the above system 1, the learning process of the model 35 for outputting recommended composition data in response to the input of the target characteristic data is performed using the learning data including the composition data and the characteristic data. Then, the target characteristics are input to the model 35, and the composition of the photosensitive resin composition for generating the target characteristics is output. Therefore, the composition of the photosensitive resin composition for producing the desired characteristics can be obtained without repeated tests by skilled workers.
[2. composition data ]
The composition indicated by the composition data may be the presence or absence of a raw material from which the photosensitive resin composition can be formed, or may be a compound contained in the raw material (for example, a name or a structural formula of a specific compound contained in the raw material indicated by a general name). The composition indicated by the composition data may be a content ratio of the compound contained in the raw material, and the content ratio may be 0. The raw material from which the photosensitive resin composition can be produced may include at least 1 of an alkali-soluble polymer, an ethylenically unsaturated bond-containing compound, a photopolymerization initiator, a resin having a repeating unit containing an acid-decomposable group (as an example, a group deprotected with an acid), and a phenol resin, a photoacid generator, a dissolution inhibitor, a sensitizer, a polymerization inhibitor, an adhesion agent, and a plasticizer.
The alkali-soluble polymer may be a binder polymer in the photocurable resin composition, and may be, for example, a carboxyl group-containing polymer (for example, a polymer represented by the following chemical formula (1)). The ethylenically unsaturated bond-containing compound may be a monomer in the photocurable resin composition, and may be a monomer represented by the following chemical formula (2), for example. The photopolymerization initiator can bond monomers to each other by exposure in the photocurable resin composition. The resin having a repeating unit having an acid-decomposable group and the phenolic resin may be polymers in the resin composition which are soluble in light and are decomposable by an acid. The photoacid generator generates an acid by exposure to light in the light-soluble resin composition. Dissolution inhibitors, also known as dissolution inhibitors, inhibit the dissolution of ingredients in aqueous alkaline solutions. The sensitizer may be a photosensitizer, for example, but may be another type of sensitizer such as N-phenylglycine. The polymerization inhibitor may be a substance that inhibits the polymerization reaction by the influence of light or heat. The sealing agent is a substance that improves the adhesion of the photosensitive resin composition to the surface of the substrate. The plasticizer is added to impart flexibility to the photosensitive resin composition or to facilitate processing.
[ chemical formula 1]
[ chemical formula 2]
[3. characteristic data ]
The characteristic indicated by the characteristic data may be, for example, at least 1 of the film thickness, the shortest development time, the sensitivity to light, the transmittance, the resolution, the minimum resist line width, the adhesion to the substrate, the developer foamability, the developer cohesiveness, the edge-melting characteristic, the flexibility of the cured film, the adhesiveness to the base film or the cover film, the hue stability, the peeling time, the size of the peeling sheet, and the covering property of the photosensitive resin composition.
Here, the development of the photosensitive resin composition may mean: the dry film of the photosensitive resin composition is exposed to cure or melt the photosensitive resin composition in the exposed region, and then the photosensitive resin composition in the exposed or unexposed region is removed to develop a negative or positive image corresponding to the exposed region. When the photosensitive resin composition is photocurable (also referred to as negative type), the shortest development time is also referred to as a development point (break point) and represents the shortest time for developing the photosensitive resin composition. For example, the shortest development time may be a time until the photosensitive resin composition laminated on the substrate is not exposed to light but developed by spraying an alkaline solution until all the photosensitive resin composition is removed. The shortest development time may be a time when parameters that may affect the development time, such as the number of spray outlets and the spray pressure, are fixed values.
When the photosensitive resin composition is photocurable, the sensitivity to light is also referred to as the minimum curing exposure amount, and represents the minimum exposure amount at which an image corresponding to the exposed region can be formed. For example, regarding the sensitivity to light, when the photosensitive resin composition is photocurable, the exposure amount (mJ/cm) may be the minimum exposure amount (mJ/cm) of the photosensitive resin composition that is cured and remains on the substrate when a dry film of the photosensitive resin composition laminated on the substrate is exposed and developed2). For example, the sensitivity to light can be calculated from the lowest transmittance of the photosensitive resin composition after curing by exposing the photosensitive resin composition to light using a mask having stepwise different transmittances.
Transmittance is also referred to as transmittance and represents the transmittance of light. The wavelength of the transmitted light may be a wavelength for curing or solubilizing the photosensitive resin composition.
Resolution represents the density of the developable image. For example, the resolution may be a minimum resist width at which collapse of the resist or deformation due to exposure is not caused when a plurality of fine resist lines are formed while changing the exposure width by exposing and developing a dry film of the photosensitive resin composition laminated on the copper substrate. The film thickness of the resist may be arbitrary.
As an example, the adhesion to the substrate may be a minimum resist width that does not cause collapse or peeling of the resist when a plurality of resists having different thicknesses are formed by exposing and developing a dry film of the photosensitive resin composition laminated on the copper substrate.
The developer foamability indicates foamability in the case of developing the photosensitive resin composition with a developer. As the developer foamability, a value measured by a known various method can be used.
The developer cohesiveness indicates cohesiveness in the case of developing the photosensitive resin composition with a developer. As the developer coagulation property, a value measured by a known various method can be used.
The bead characteristic represents the amount of the photosensitive resin composition extruded from the end face of the dry film roll to the outside by the winding pressure during storage of the dry film roll. The smaller the edge-melting property, the longer the life of the dry film, and the more preferable. As the edge-melting characteristics, values measured by various known methods can be used.
The cured film flexibility indicates the flexibility of the photo-curable photosensitive resin composition after development. For example, the cured film flexibility may be a minimum diameter at which cracking of the resist does not occur when a dry film of the photosensitive resin composition laminated on a flexible substrate is wound around a plurality of cylinders having different diameters after exposure and development. As an example, the flexibility of the cured film can be measured by a mandrel bending test apparatus.
The adhesiveness to the base film or the cover film means the adhesiveness of the dry film to the base film or the cover film. For example, the tackiness may be a force required for peeling in the case where the dry film is peeled from the base film or the cover film using a universal tensile machine (Japanese: テンシロン apparatus). When the viscosity is too high or too low, the usability of the dry film roll is deteriorated, and therefore, the range is preferably within an appropriate range.
The peeling time indicates the peelability in the case of peeling the photosensitive resin composition from the substrate. For example, the peeling time may be a time until the photosensitive resin composition is peeled from the substrate in a case where the photosensitive resin composition is immersed in an alkaline peeling liquid for developing a dry film laminated on the substrate and exposed to light. The peeling time is preferably short.
The hue stability indicates the stability of color of the photosensitive resin composition. As the hue stability, a value measured by a known various method can be used.
The release sheet size indicates the size of the photosensitive resin composition (also referred to as a release sheet) released from the substrate. The size of the release sheet may be the size of the release sheet after being peeled from the substrate and thinned by the water washing spray. The release sheet is preferably small.
The hiding property indicates a fracture rate in the case where the lid hole of the substrate was hidden with a dry film. For example, the hiding property may be the number of cover holes that are broken when a dry film is laminated on a substrate having cover holes with a diameter of 1mm to 10mm and subjected to exposure development. The smaller the covering property, the more preferable.
[3. work ]
[3-1. learning processing of model ]
Fig. 2 illustrates a learning method of the model 35. The system 1 performs learning of the model 35 by the processing of steps S11 to S15.
In step S11, the control unit 39 causes the manufacturing apparatus 2 to manufacture the photosensitive resin composition. When the processing of steps S11 to S15 is performed a plurality of times, the controller 39 can perform the manufacturing by changing the composition of the photosensitive resin composition every time.
In step S13, the composition acquisition unit 32 and the characteristic acquisition unit 33 acquire composition data and characteristic data of the photosensitive resin composition manufactured by the processing of step S11, respectively. The composition acquisition unit 32 may acquire composition data from at least one of an operator and the manufacturing apparatus 2, or may acquire composition data from another external apparatus (not shown). The characteristic acquisition unit 33 may acquire characteristic data from at least one of an operator and a measurement device (not shown) for measuring characteristics, or may acquire characteristic data from another external device (not shown). The measuring device may be disposed outside the manufacturing apparatus 2 or may be disposed inside. The characteristics can be obtained at a plurality of positions of the photosensitive resin composition. Further, the acquisition processing of the composition data in the processing of step S13 may be performed before the processing of step S11.
In step S15, the learning processing portion 34 executes the learning processing of the model 35 using the learning data including the acquired composition data and characteristic data. In the present embodiment, the model 35 is a neural network of a cyclic (recurrent) type, a time-lag type, or the like, as an example, but may be another machine learning algorithm including a random forest, a gradient boosting, a logistic regression, a Support Vector Machine (SVM), or the like. For example, the model 35 may include nodes corresponding to elements of the learning data in the input layer and nodes corresponding to raw materials of the recommended composition in the output layer. The number of nodes corresponding to 1 element of the learning data in the input layer may be 1 or more. There may be an intermediate layer (hidden layer) containing 1 or more nodes between the input layer and the output layer. The learning processing unit 34 can perform learning processing by adjusting the weight of the edge between the connection nodes and the offset value of the output node.
[3-2. handling of model ]
Fig. 3 shows a method for producing a photosensitive resin composition using a mold 35. The system 1 manufactures the photosensitive resin composition through the processes of steps S21 to S27.
In step S21, the target property acquiring unit 36 acquires target property data of the target photosensitive resin composition. The target characteristic data may include a target range of the characteristic for at least 1 characteristic. The target range may be defined by at least one of an upper limit value and a lower limit value.
In step S23, the target property supply unit 37 supplies the acquired target property data to the model 35.
In step S25, the recommended composition acquisition portion 38 acquires recommended composition data that is output by the model 35 in response to the supply of the target characteristic data to the model 35. The recommended composition acquiring unit 38 may perform bagging (also referred to as "guided aggregation") on the target characteristic data to generate a plurality of local target characteristic data obtained by sampling only a part of the target characteristic. The recommended composition acquiring unit 38 may acquire a plurality of pieces of recommended composition data by supplying the plurality of pieces of local target characteristic data to the model 35. The recommended composition acquisition unit 38 may acquire a set of recommended composition data indicating a composition that is possible to achieve the goal of all the characteristics in the target characteristic data and the achievement probability of the goal of a part of the characteristics by aggregating the plurality of pieces of recommended composition data acquired. The target achievement probability may be a value obtained by multiplying the achievement probabilities of all the characteristics, and may be a value obtained by multiplying the achievement probabilities of all the characteristics by weighting coefficients of the characteristics, for example. The recommended composition acquisition section 38 may acquire a set of the recommended composition data and a probability distribution of at least 1 characteristic value by using target characteristic data of a target range including the characteristic.
In addition, the recommended composition acquisition unit 38 may acquire recommended composition data by repeatedly using the model 35 using a genetic algorithm. For example, the recommended composition acquiring unit 38 may acquire a plurality of pieces of recommended composition data by supplying target characteristic data (or local target characteristic data) to the model 35, and then generate a plurality of pieces of recommended composition data of the next generation by selecting, crossing, and mutating the plurality of pieces of recommended composition data. The term "crossover" may mean, for example, a change in the content ratio of at least a part of the raw material among 2 pieces of recommended composition data. The mutation may refer to changing a content ratio of at least a part of raw materials in the recommended composition data. The recommended composition acquiring unit 38 may acquire a plurality of pieces of characteristic data by supplying the generated recommended composition data of the next generation to the model 35, and extract recommended composition data in which all the characteristics of the plurality of pieces of recommended composition data supplied to the model 35 satisfy the target. Then, the recommended composition acquiring unit 38 may acquire recommended composition data in which the achievement probability of the target exceeds the standard probability by performing any one of selection, intersection, and mutation on the extracted recommended composition data to generate a plurality of recommended composition data of the next generation, extracting recommended composition data in which the characteristic data of the recommended composition data satisfies the target, and repeating the above-described processing.
In step S27, the control unit 39 supplies the recommended composition data to the manufacturing apparatus 2, thereby causing the manufacturing apparatus 2 to manufacture the photosensitive resin composition in the composition indicated by the recommended composition data. When a plurality of pieces of recommended composition data are acquired from the recommended composition acquisition unit 38, the control unit 39 may display the pieces of recommended composition data and supply any 1 piece of recommended composition data selected by the operator to the manufacturing apparatus 2. In this case, the control unit 39 displays the plurality of pieces of acquired recommended composition data in the order of the highest achievement probability of the target. In addition, when the operator selects any 1 of the characteristics, the control section 39 may display a plurality of pieces of recommended composition data in order of the achievement probability of the target of the characteristic from high to low.
The manufacturing apparatus 2 may determine the composition of the photosensitive resin composition to be manufactured based on the recommended composition data acquired from the learning processing apparatus 1, and may manufacture the photosensitive resin composition by mixing the raw materials (components) corresponding to the determined composition. For example, a solvent for dissolving other components or a dispersion medium for dispersing other components may be contained in the components of the photosensitive resin composition, and the mixing section 20 of the manufacturing apparatus 2 may mix the components to adjust the fluid (coating liquid) of the photosensitive resin composition. In addition, the manufacturing apparatus 2 may apply the fluid of the mixed photosensitive resin composition on the base film. The manufacturing apparatus 2 may remove the solvent and the dispersion medium by drying after applying the photosensitive resin composition. Thus, a laminate of the base film and the film-like photosensitive resin composition is produced. The manufacturing apparatus 2 can manufacture a photosensitive resin laminate by providing a cover film for protecting the photosensitive resin composition on the photosensitive resin composition. At least one of the determination of the composition, the mixing of the components, and the production of the laminate based on the recommended composition data may be performed by an operator without using the production apparatus 2. Further, after the photosensitive resin composition is manufactured, the model 35 can be relearned by the above-described processing of steps S11 to S15.
[4. method of Using photosensitive resin composition ]
Fig. 4 shows a method of using the dry film 100 of the photosensitive resin composition. In the present embodiment, the photosensitive resin composition is used for forming a metal wiring on a printed wiring board (a motherboard, for example).
First, as shown in (1) to (2), a photocurable dry film 100 is pasted on a substrate 200. In the present embodiment, the dry film 100 and the cover film 101 are attached to the substrate 200 while peeling off the base film from the dry film roll, for example. The substrate 200 may be a substrate in which the surface of the insulating plate 201 is covered with a copper foil 202. The cover film 101 may be made of polyethylene terephthalate (PET).
Next, as shown in part (3), the dry film 100 is exposed through a mask 300. The light to be irradiated may be visible light or light having a wavelength of 450nm or less (for example, ultraviolet light). Thereby, the dry film 100 in the exposed region is cured.
Next, as shown in part (4), the uncured dry film 100 is removed and developed. For example, the uncured dry film 100 is dissolved in a weakly alkaline aqueous solution (for example, Na)2CO3An aqueous solution).
Next, as shown in part (5), the remaining dry film 100 is etched as a resist. Thereby, the copper foil 202 in the portion not covered with the resist is removed, and the copper line 203 is formed from the remaining copper foil 202. The etching may be performed using an acidic aqueous solution (for example, CuCl)2An aqueous solution).
Then, as shown in part (6), the residual dry film 100, that is, the cured photosensitive resin composition is removed. When the residual dry film 100 is to be removed, for example, at least a contact portion between the dry film 100 and the copper wire 203 may be immersed in a strongly alkaline aqueous solution (for example, an aqueous NaOH solution), and then the dry film 100 may be peeled off from the insulating plate 201 and the copper wire 203.
In the above-described embodiment, the learning processing device 3 has been described as having the composition acquisition unit 32, the characteristic acquisition unit 33, and the learning processing unit 34, but at least 1 of them may not be provided. In this case, the learning processing device 3 may perform acquisition of the recommended composition data using the model 35 that has completed learning without performing the learning processing of the model 35. The learning processing device 3 has been described as having the target characteristic acquisition unit 36, the target characteristic supply unit 37, and the recommended component acquisition unit 38, but may not have at least 1 of them. In this case, the learning processing device 3 may perform the learning processing of the model 35 without performing the processing of acquiring the recommended composition data using the model 35. Further, although the description has been given with the learning processing device 3 including the control unit 39 and the model 35, at least 1 of them may not be included. For example, the control unit 39 and the model 35 may be provided in an external device of the learning processing device 3 (for example, a control device of the manufacturing apparatus 2).
The photosensitive resin composition is described as being used as a resist in the process of forming metal wiring on a printed wiring board, but may be used as a resist in the process of manufacturing a semiconductor.
Various embodiments of the present invention may be described with reference to flowcharts and block diagrams, and here, a block may indicate a stage of a process for performing the operation (1) or a part of an apparatus having a function for performing the operation (2). Certain stages and portions may be implemented by dedicated circuitry, programmable circuitry supplied with computer-readable instructions stored on a computer-readable medium, and/or a processor supplied with computer-readable instructions stored on a computer-readable medium. The application specific circuits may include digital and/or analog hardware circuits, may include Integrated Circuits (ICs) and/or discrete circuits. The programmable circuit may comprise a reconfigurable hardware circuit including storage elements such as logical AND (AND), logical OR (OR), logical exclusive OR (XOR), logical NAND (NAND), logical NOR (NOR) AND other logical operations, flip-flops, registers, Field Programmable Gate Arrays (FPGA), Programmable Logic Arrays (PLA), AND the like.
The computer-readable medium may comprise any tangible device capable of holding instructions for execution by a suitable device, and as a result, the computer-readable medium with its stored instructions is provided with the product of: the article of manufacture includes instructions that can be executed to create a means for performing the operations specified in the flowchart or block diagram block or blocks. As examples of the computer readable medium, an electronic storage medium, a magnetic storage medium, an optical storage medium, an electromagnetic storage medium, a semiconductor storage medium, and the like may be included. As more specific examples of the computer-readable medium, Floppy (registered trademark) Floppy disks, magnetic disks, hard disks, Random Access Memories (RAMs), Read Only Memories (ROMs), erasable programmable read only memories (EPROMs or flash memories), Electrically Erasable Programmable Read Only Memories (EEPROMs), Static Random Access Memories (SRAMs), compact disc read only memories (CD-ROMs), Digital Versatile Discs (DVDs), blu-Ray (RTM) optical discs, Memory sticks (Memory sticks), integrated circuit cards, and the like may be included.
Computer readable instructions may include any code in the source code or object code described in any combination of one or more programming languages, including assembly instructions, Instruction Set Architecture (ISA) instructions, machine related instructions, microcode, firmware instructions, state setting data, or an object oriented programming language such as Smalltalk, JAVA (registered trademark), C + +, or the like, as well as the existing procedural programming languages, such as the "C" programming language or the same.
The computer readable instructions may be provided to a processor or programmable circuitry of a general purpose computer, special purpose computer, or other programmable data processing apparatus via a Wide Area Network (WAN), such as a local or Local Area Network (LAN), the internet, or the like, which execute the computer readable instructions to create means for performing the operations specified in the flowchart or block diagram block or blocks. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, and the like.
FIG. 5 illustrates an example of a computer 2200 in which aspects of the invention may be embodied, in whole or in part. A program installed in the computer 2200 can cause the computer 2200 to function as or perform the operations associated with the apparatus according to the embodiment of the present invention or 1 or more parts of the apparatus, or can cause the computer 2200 to perform the operations or the 1 or more parts, and/or can cause the computer 2200 to perform the process according to the embodiment of the present invention or the stages of the process. Such a program is executed by the CPU2212 in order to cause the computer 2200 to perform specific operations associated with several or all of the blocks of the flowcharts and block diagrams described in this specification.
The computer 2200 of the present embodiment includes a CPU2212, a RAM 2214, a graphic controller 2216, and a display device 2218, which are connected to each other through a main controller 2210. The computer 2200 also includes a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an input/output unit such as an IC card drive, which are connected to the main controller 2210 via an input/output controller 2220. The computer also includes a conventional input/output unit such as a ROM2230 and a keyboard 2242, which are connected to the input/output controller 2220 via an input/output chip 2240.
The CPU2212 operates in accordance with programs stored in the ROM2230 and the RAM 2214, thereby controlling the respective units. The graphic controller 2216 acquires image data generated by the CPU2212 in a frame buffer or the like provided into the RAM 2214 or itself, and the image data is displayed on the display device 2218.
ROM2230 stores therein boot programs and the like executed by computer 2200 at the time of activation, and/or programs dependent on the hardware of computer 2200. The i/o chip 2240 may also be used to connect various i/o units to the i/o controller 2220 via a parallel port, a serial port, a keyboard port, a mouse port, and the like.
The program is provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The program is read from a computer-readable medium, installed on the hard disk drive 2224, RAM 2214, or ROM2230, which is also an example of a computer-readable medium, and executed by the CPU 2212. The information processing described in these programs is read into the computer 2200, and cooperation between the programs and the various types of hardware resources described above is realized. An apparatus or method may be constructed by performing the operation or process of information in conjunction with the use of the computer 2200.
For example, in the case of performing communication between the computer 2200 and an external device, the CPU2212 may execute a communication program loaded into the RAM 2214, and instruct the communication interface 2222 to perform communication processing based on processing described in the communication program. The communication interface 2222 reads transmission data held in a transmission buffer processing area provided in a recording medium such as the RAM 2214, the hard disk drive 2224, the DVD-ROM 2201, or an IC card under the control of the CPU2212, and transmits the read transmission data to a network, or writes reception data received from the network into a reception buffer processing area provided on the recording medium, or the like.
In addition, the CPU2212 can read all or a necessary part of a file or a database held in an external recording medium such as the hard disk drive 2224, the DVD-ROM drive 2226(DVD-ROM 2201), an IC card, or the like to the RAM 2214, and perform various types of processing on data on the RAM 2214. The CPU2212 then writes the processed data back to the external recording medium.
Various types of information such as various types of programs, data, tables, and databases may be stored in the recording medium and subjected to information processing. The CPU2212 can execute various types of processing including various types of operations, information processing, condition judgment, conditional branching, unconditional branching, retrieval/replacement of information, and the like specified by an instruction sequence of a program described anywhere in the present invention on the data read out from the RAM 2214, and write the result back to the RAM 2214. In addition, the CPU2212 can search for information in a file, a database, or the like in the recording medium. For example, when a plurality of entries each having an attribute value of the 1 st attribute associated with an attribute value of the 2 nd attribute are stored in the recording medium, the CPU2212 may retrieve entries matching the condition for specifying the attribute value of the 1 st attribute from the plurality of entries, and may read the attribute value of the 2 nd attribute stored in the entry, thereby acquiring the attribute value of the 2 nd attribute associated with the 1 st attribute satisfying the predetermined condition.
The programs or software modules described above may be stored on the computer 2200 or in a computer-readable medium near the computer 2200. In addition, a recording medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the internet can be used as a computer-readable medium, thereby providing a program to the computer 2200 via the network.
The present invention has been described above with reference to the embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various changes or modifications can be made to the above-described embodiments. It is apparent from the description of the claims that the embodiments to which such changes or improvements are applied are also included in the scope of the present invention.
It should be noted that, as for the execution sequence of the operations, procedures, steps, and stages in the devices, systems, programs, and methods shown in the claims, the specification, and the drawings, the execution sequence can be realized in any sequence unless the cases where "prior to …", "prior to …", and the like are not particularly noted, and where the output of the prior process is used in the subsequent process. The operational flow in the claims, the specification, and the drawings is described using "first," "next," and the like for convenience, but this does not necessarily mean that the operations are performed in this order.
Claims (12)
1. An apparatus, comprising:
a composition acquisition unit that acquires composition data indicating a composition of the photosensitive resin composition;
a characteristic acquisition unit that acquires characteristic data indicating characteristics of the photosensitive resin composition; and
a learning processing section that performs learning processing of a model for outputting recommended composition data representing a composition of the recommended photosensitive resin composition in response to input of target characteristic data representing a characteristic of the photosensitive resin composition as a target, using learning data including the acquired composition data and the characteristic data.
2. An apparatus, comprising:
a target property acquisition unit that acquires target property data indicating a property of a target photosensitive resin composition;
a target characteristic supply unit that supplies the target characteristic data acquired by the target characteristic acquisition unit to a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of the target characteristic data; and
a recommended composition acquisition section that acquires the recommended composition data that is output by the model in response to the target characteristic data being supplied to the model.
3. The device according to claim 1 or 2,
the photosensitive resin composition is in the form of a film.
4. The device according to any one of claims 1 to 3,
the photosensitive resin composition is used for forming metal wiring.
5. The device according to any one of claims 1 to 4,
the composition of the photosensitive resin composition is:
the presence or absence of at least 1 of an alkali-soluble polymer, an ethylenically unsaturated bond-containing compound, a photopolymerization initiator, a resin having a repeating unit containing an acid-decomposable group, a phenol resin, a photoacid generator, a dissolution inhibitor, a sensitizer, a polymerization inhibitor, an adhesion agent, and a plasticizer,
a compound contained in at least 1 of an alkali-soluble polymer, an ethylenically unsaturated bond-containing compound, a photopolymerization initiator, a resin having a repeating unit containing an acid-decomposable group, a phenol resin, a photoacid generator, a dissolution inhibitor, a sensitizer, a polymerization inhibitor, an adhesion agent, and a plasticizer, or,
a content ratio of a compound contained in at least 1 of an alkali-soluble polymer, an ethylenically unsaturated bond-containing compound, a photopolymerization initiator, a resin having a repeating unit containing an acid-decomposable group, a phenol resin, a photoacid generator, a dissolution inhibitor, a sensitizer, a polymerization inhibitor, an adhesion agent, and a plasticizer.
6. The device according to any one of claims 1 to 5,
the characteristics of the photosensitive resin composition are:
the photosensitive resin composition has at least 1 of film thickness, shortest development time, sensitivity to light, transmittance, resolution, minimum resist line width, adhesion to a substrate, developer foamability, developer cohesiveness, edge melting property, cured film flexibility, adhesiveness to a base film or a cover film, hue stability, peeling time, peeling sheet size, and covering property.
7. A method, characterized in that it comprises the following phases:
a composition acquisition step of acquiring composition data indicating the composition of the photosensitive resin composition;
a characteristic acquisition step of acquiring characteristic data representing characteristics of the photosensitive resin composition; and
a learning processing stage of performing learning processing of a model for outputting recommended composition data representing a composition of the recommended photosensitive resin composition in response to input of target characteristic data representing a characteristic of the photosensitive resin composition as a target, using learning data including the acquired composition data and the characteristic data.
8. A method, characterized in that it comprises the following phases:
a target characteristic acquisition step of acquiring target characteristic data indicating characteristics of a target photosensitive resin composition;
a target characteristic supply step of supplying the target characteristic data acquired by the target characteristic acquisition step to a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of the target characteristic data; and
a recommended composition acquisition phase of acquiring the recommended composition data output by the model in response to the supply of the target characteristic data to the model.
9. A method for producing a photosensitive resin composition, comprising the steps of:
determining a composition of a photosensitive resin composition based on the recommended composition data obtained by the method according to claim 8; and
mixing raw materials for producing the photosensitive resin composition.
10. A method for manufacturing a photosensitive resin laminate, comprising the steps of:
coating a fluid of the photosensitive resin composition obtained by mixing by the production method according to claim 9 on a base film; and
and providing a cover film on the coated photosensitive resin composition.
11. A storage medium storing a program which, when executed by a computer, implements the stages of:
a composition acquisition step of acquiring composition data indicating the composition of the photosensitive resin composition;
a characteristic acquisition step of acquiring characteristic data representing characteristics of the photosensitive resin composition; and
a learning processing stage of performing learning processing of a model for outputting recommended composition data representing a composition of the recommended photosensitive resin composition in response to input of target characteristic data representing a characteristic of the photosensitive resin composition as a target, using learning data including the acquired composition data and the characteristic data.
12. A storage medium storing a program which, when executed by a computer, implements the stages of:
a target characteristic acquisition step of acquiring target characteristic data indicating characteristics of a target photosensitive resin composition;
a target characteristic supply step of supplying the target characteristic data acquired by the target characteristic acquisition step to a model for outputting recommended composition data representing a recommended composition of the photosensitive resin composition in response to input of the target characteristic data; and
a recommended composition acquisition phase of acquiring the recommended composition data output by the model in response to the supply of the target characteristic data to the model.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2018-211805 | 2018-11-09 | ||
| JP2018211805A JP7174599B2 (en) | 2018-11-09 | 2018-11-09 | Apparatus, method, program, method for producing photosensitive resin composition, and method for producing photosensitive resin laminate |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111310911A true CN111310911A (en) | 2020-06-19 |
| CN111310911B CN111310911B (en) | 2023-08-25 |
Family
ID=70725052
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911090042.8A Active CN111310911B (en) | 2018-11-09 | 2019-11-08 | Apparatus, method, medium, photosensitive resin composition, and method for producing laminate |
Country Status (2)
| Country | Link |
|---|---|
| JP (1) | JP7174599B2 (en) |
| CN (1) | CN111310911B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2021004933A (en) * | 2019-06-25 | 2021-01-14 | 旭化成株式会社 | Device, method, program, method for producing photosensitive resin composition and method for producing photosensitive resin laminate |
| JP2021051141A (en) * | 2019-09-24 | 2021-04-01 | 旭化成株式会社 | Device, method, program, method for producing photosensitive resin composition and method for producing photosensitive resin laminate |
| WO2022080443A1 (en) | 2020-10-16 | 2022-04-21 | 味の素株式会社 | Information processing device, information processing method, and program |
| EP4398257A1 (en) | 2021-08-31 | 2024-07-10 | Resonac Corporation | Property prediction device, property prediction method, and program |
| JP7088399B1 (en) * | 2021-12-17 | 2022-06-21 | Dic株式会社 | Novolac-type phenolic resin search method, information processing device, and program |
| WO2023120290A1 (en) | 2021-12-20 | 2023-06-29 | 株式会社レゾナック | Design support device, design support method, and program |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000235257A (en) * | 1999-02-15 | 2000-08-29 | Fuji Yakuhin Kogyo Kk | Production of laminated sheet for forming photoresist using dry film |
| US20080090162A1 (en) * | 2006-10-12 | 2008-04-17 | Samsung Electronics Co., Ltd. | Binder resin composition of toner, toner composition and preparation method thereof |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0865890A4 (en) * | 1996-08-08 | 1999-05-26 | Bridgestone Corp | Method of designing multicomponent material, optimization analyzer and storage medium on which multicomponent material optimization analysis program is recorded |
| US6485872B1 (en) * | 1999-12-03 | 2002-11-26 | Mks Instruments, Inc. | Method and apparatus for measuring the composition and other properties of thin films utilizing infrared radiation |
| JP4581039B2 (en) * | 2000-09-11 | 2010-11-17 | オプト技研株式会社 | Grade identification method for polymer materials |
| JP2007101681A (en) * | 2005-09-30 | 2007-04-19 | Fujifilm Corp | Pattern forming material, pattern forming apparatus and pattern forming method |
| KR101805239B1 (en) * | 2010-10-18 | 2017-12-05 | 미쯔비시 케미컬 주식회사 | Copolymers for lithography and method for producing same, resist composition, method for producing substrate with pattern formed thereupon, method for evaluating copolymers, and method for analyzing copolymer compositions |
| JP2018013418A (en) * | 2016-07-21 | 2018-01-25 | ヤンマー株式会社 | Wavelength selection method, manufacturing method of object substance content estimation device, and object substance content estimation device |
-
2018
- 2018-11-09 JP JP2018211805A patent/JP7174599B2/en active Active
-
2019
- 2019-11-08 CN CN201911090042.8A patent/CN111310911B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000235257A (en) * | 1999-02-15 | 2000-08-29 | Fuji Yakuhin Kogyo Kk | Production of laminated sheet for forming photoresist using dry film |
| US20080090162A1 (en) * | 2006-10-12 | 2008-04-17 | Samsung Electronics Co., Ltd. | Binder resin composition of toner, toner composition and preparation method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2020077346A (en) | 2020-05-21 |
| JP7174599B2 (en) | 2022-11-17 |
| CN111310911B (en) | 2023-08-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111310911B (en) | Apparatus, method, medium, photosensitive resin composition, and method for producing laminate | |
| JP7340581B2 (en) | Photosensitive resin composition | |
| JP5387894B2 (en) | Conductive transfer film and method of forming conductive pattern using the same | |
| KR20140148379A (en) | Photosensitive resin composition, method for manufacturing processed glass substrate using same, and touch panel and method for manufacturing same | |
| TW201823878A (en) | Improved method for computer modeling and simulation of negative-tone-developable photoresists | |
| JP2010249884A (en) | Photopolymerizable resin composition and photosensitive film using the same | |
| JP5437072B2 (en) | Photosensitive resin composition and laminate thereof | |
| US7093226B2 (en) | Method and apparatus of wafer print simulation using hybrid model with mask optical images | |
| JP2021004933A (en) | Device, method, program, method for producing photosensitive resin composition and method for producing photosensitive resin laminate | |
| TW474969B (en) | Photopolymerizable composition | |
| KR102522749B1 (en) | Photosensitive resin laminate and method for producing resist pattern | |
| TW202307700A (en) | Computing system and method for estimating solubility | |
| JP2006259095A (en) | Photo-crosslinkable resin composition | |
| US11142620B2 (en) | Photosensitive resin composition, etching method and plating method | |
| JP2021051141A (en) | Device, method, program, method for producing photosensitive resin composition and method for producing photosensitive resin laminate | |
| TW201401965A (en) | A method for photoimaging a substrate | |
| JP2018202634A (en) | Pattern forming method to curved surface | |
| JP2011017976A (en) | Method for forming light shielding film | |
| JPH11174667A (en) | Photopolymerized resin composition and layered product | |
| TWI730173B (en) | Substrate bonding method and manufacturing method of laminated body | |
| KR20040040625A (en) | Method and system for controlling wafer of photo spinner | |
| JP2022127585A (en) | photosensitive dry film | |
| US9275449B2 (en) | Methods and systems for determining a dose-to-clear of a photoresist | |
| JPH0553319A (en) | Film resist for direct plotting and etching method using this film resist | |
| JP2016102828A (en) | Photosensitive resin composition for plating |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |