Company patents

Chiyoda Corporation

Chiyoda Corporation's patent strategy reveals a surprising shift towards computing, with Electronic Design Automation (CAD/EDA) emerging as a significant focus, growing by 200.0% in 2025, now representing 18.4% of its portfolio, while traditional strengths like Catalysts & Reactors have seen a sharp decline of 100.0% in 2025, indicating a strategic pivot away from certain materials-related innovations.

Patent Trend by Technology Area

Yearly patent publications since 2023

Product themes

Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.

49 US filings (since 2023) · 12 categories · 17 themes

Hydrogen Production Catalysis

Catalytic processes and novel catalyst materials designed to efficiently produce hydrogen gas from various feedstocks, including hydrocarbons (e.g., methane, natural gas) and ammonia.

Electrolysis & ElectrochemistryNon-metallic Inorganic Compounds
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13since 2023
-50.0%YoY
Industrial Organic Synthesis

Methods and apparatus for the efficient and selective production of organic compounds, including amines, acids, and esters, often involving catalytic or continuous processes and purification steps.

Acyclic / Carbocyclic Compounds
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9since 2023
-50.0%YoY
Component Performance Optimization

Using computational design and simulation to optimize the performance characteristics of specific components or materials within a larger engineering system.

Electronic Design Automation (CAD/EDA)
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8since 2023
+300.0%YoY
AM Process Monitoring & Control

Systems and methods for real-time sensing, modeling, and closed-loop control of additive manufacturing parameters to ensure part quality, consistency, and process efficiency. This includes thermal management, atmospheric regulation, and precise material deposition.

Industrial Control Systems
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7since 2023
+400.0%YoY
CO2 Electroreduction Catalysts

Development of catalytic materials and membrane electrode assemblies (MEAs) specifically designed for the electrochemical reduction of carbon dioxide (CO2) or carbon monoxide (COx) into valuable chemicals or fuels.

Electrolysis & Electrochemistry
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6since 2023
0.0%YoY
Hydroprocessing & Desulfurization

Chemical processes that utilize hydrogen to remove impurities like sulfur, nitrogen, and oxygen from hydrocarbon feedstocks, or to saturate aromatic compounds, often employing specific catalysts and process conditions.

Petroleum / Hydrocarbon Refining
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6since 2023
0.0%YoY
Carbon Dioxide Capture & Conversion

Technologies and materials for capturing carbon dioxide from gas streams and subsequently converting it into valuable chemical products or materials, rather than simply storing it.

Acyclic / Carbocyclic Compounds
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5since 2023
0.0%YoY
Waste Plastic Pyrolysis & Upgrading

Technologies focused on converting waste plastics, residual polymers, or aromatic waste streams into valuable hydrocarbon liquids, gases, or chemical feedstocks through thermal or catalytic pyrolysis, followed by upgrading and separation processes.

Petroleum / Hydrocarbon Refining
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5since 2023
0.0%YoY
AI/ML for Industrial Process Optimization

Applying machine learning and artificial intelligence models to analyze industrial data, predict system behavior, and optimize control strategies for improved efficiency, quality, or environmental compliance in manufacturing and operations.

Industrial Control Systems
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5since 2023
-50.0%YoY
Electrochemical Chemical Synthesis

Utilization of electrochemical processes to synthesize a variety of chemical products, materials, or to treat waste streams, by selectively promoting redox reactions of specific feedstocks beyond hydrogen or CO2 reduction.

Electrolysis & Electrochemistry
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4since 2023
0.0%YoY
Catalytic Cracking & Regeneration

Processes and reactor designs for breaking down heavier hydrocarbon feedstocks into lighter, more valuable products using catalysts, including methods for regenerating spent catalysts through coke burning or other means.

Petroleum / Hydrocarbon Refining
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3since 2023
new
Predictive Maintenance & Anomaly Detection

Utilizing sensor data, historical performance, and analytical models to anticipate equipment failures, diagnose faults, and estimate remaining useful life, thereby enabling proactive maintenance and reducing downtime.

Industrial Control Systems
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2since 2023
0.0%YoY
Novel Catalyst Materials

Development and synthesis of catalysts with unique compositions or structures, such as medium entropy alloys, metal foam-supported catalysts, layered catalytic articles, or high-entropy oxides, to enhance activity, selectivity, or stability in chemical reactions.

Catalysts & Reactors
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2since 2023
n/a
Photolithography Process Modeling

Computational methods for modeling and simulating photolithography processes, including mask design, aerial image generation, and defect prediction for semiconductor manufacturing.

Electronic Design Automation (CAD/EDA)
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1since 2023
new
Bio-derived Chemical Production

Methods for producing organic chemicals from biomass or through fermentation processes, often focusing on carbohydrates or fatty acid derivatives for food, health, or industrial applications.

Acyclic / Carbocyclic Compounds
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1since 2023
n/a
Electrolyzer Cell Components

Design and engineering of non-catalytic parts within an electrolysis cell or stack, such as separators, gaskets, flow fields, porous transport layers, and manifold devices, to improve efficiency, sealing, or gas management.

Electrolysis & Electrochemistry
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1since 2023
n/a
Solid-State Battery Manufacturing

Process and equipment for producing solid-state battery cells, including solid electrolyte synthesis (sulfide/oxide/polymer), thin-film deposition, lamination, sintering, dry-electrode fabrication, and stacking under controlled atmosphere.

Batteries & Fuel Cells
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1since 2023
n/a

Patents

Showing 1-10 of 70

Page 1 of 7
US 20260127490 A1APPLICATION
G06N20/00

METHOD FOR CREATING MACHINE LEARNING MODEL FOR ESTIMATING STATE OF FLUID IN TANK, AND METHOD FOR ESTIMATING STATE OF FLUID IN TANK USING MACHINE LEARNING MODEL

Filed:2023-10-18Pub:2026-05-07
Applicant:CHIYODA CORPORATION

[Problem] To provide a method for creating a machine learning model that allows for a quick and accurate estimation of a state of a fluid in a tank. [Solution] The method for creating a machine learning model for estimating a state of a fluid in a tank, wherein the fluid contains a plurality of substances, the method comprising: creating a plurality of parameter sets, each set comprising tank information including at least a shape and size of the tank, operating conditions of the tank, and substance information including at least an amount, and one or more physical properties of each of the plurality of substances, wherein the plurality of parameter sets are created by varying the parameters of the operating conditions and the substance information; performing a numerical fluid dynamics analysis based on the plurality of parameter sets to provide a plurality of calculation results based on fluid information including distributions of physical quantities related to the fluid and/or an amount of each of the plurality of substances; and creating the machine learning model by a machine learning operation which involves training the machine learning model with teaching data including the plurality of parameter sets and the corresponding plurality of calculation results.