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Quantum Computing in Chemistry Market Size to Grow USD 108.5 Million by 2030 at a CAGR of 10.5% | Valuates Reports

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BANGALORE, India, June 11, 2024 /PRNewswire/ — Quantum Computing in Chemistry Market is Segmented by Type (Quantum Hardware, Quantum Software), by Application (Chemical Plant, Research Institute, Other): Global Opportunity Analysis and Industry Forecast, 2024-2030.

The global Quantum Computing in Chemistry market was valued at USD 54 Million in 2023 and is anticipated to reach USD 108.5 Million by 2030, witnessing a CAGR of 10.5% during the forecast period 2024-2030.

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Major Factors Driving the Growth of Quantum Computing in Chemistry Market:

The growth of the quantum computing in chemistry market is driven by the technology’s potential to revolutionize molecular simulations and chemical analysis, offering unprecedented accuracy and speed. Quantum computers can handle complex calculations and simulations that are infeasible for classical computers, enabling detailed modeling of chemical reactions, material properties, and drug interactions at a quantum level. This capability accelerates the discovery of new materials, pharmaceuticals, and chemical processes, making quantum computing a valuable tool for research and development in the chemical industry. Additionally, increasing investments in quantum computing technology and collaborations between tech companies and chemical research institutions are propelling the market’s expansion.

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TRENDS INFLUENCING THE GROWTH OF QUANTUM COMPUTING IN CHEMISTRY MARKET:

Because it allows for sophisticated simulations and modeling that traditional computers are unable to perform effectively, quantum software at research institutions is a major factor in the growth of the quantum computing industry in chemistry. This program makes it possible for scientists to precisely model chemical reactions and molecular interactions at the quantum level, which is essential for the development of novel substances, materials, and chemical processes. The accuracy and speed of quantum calculations make it easier to address challenging chemical issues like protein folding, catalyst design, and reaction dynamics, which can result in previously unthinkable discoveries. Research institutes are utilizing quantum software to advance chemical research, draw funding, promote cooperation, and quicken the creation of useful quantum computer applications for the chemical sector.

One key element propelling the development of quantum computing in the chemical industry is the progress made in quantum hardware. Recent advances in quantum gate operations, coherence times, error correction, and qubit design have greatly improved the efficiency and dependability of quantum computers. More qubits may be included into quantum systems with improved hardware, boosting their computing capacity and enabling more intricate chemical simulations. Various innovations, including topological qubits, trapped ions, and superconducting qubits, provide different ways to construct scalable quantum computers. The advancement of hardware technology lowers the entrance barrier for high-fidelity quantum simulations, hence increasing the accessibility and practicality of quantum computing for chemists and researchers working in the field.

The intricacy of the issues that need to be solved in chemistry is one of the main causes propelling the development of quantum computing in that field. The exponential increase in complexity that comes with modeling molecular structures and chemical reactions is a challenge for conventional computing techniques, such as classical computers. Superposition and entanglement are two concepts that quantum computers may use to process and simulate these complicated systems more effectively. Because quantum computing can handle several variables and interactions at once, it is ideally suited to address complex chemical processes that would otherwise be computationally prohibitive. For example, it becomes possible to comprehend intricate catalytic reaction pathways and precisely anticipate the behavior of massive macromolecules, which opens up new avenues for chemical study and development.

The need for novel compounds and medications is one of the main forces behind quantum computing in chemistry. Industries including manufacturing, energy, and medicines are always looking for creative ways to create new chemicals, materials, and medications. Through better insights into molecular interactions and the ability to build more powerful medications and sophisticated materials, quantum computing holds the potential to completely transform various sectors of the economy. Quantum simulations, for instance, can be used to find new compounds with certain qualities or to improve catalysts for chemical reactions that use less energy. The capacity to efficiently and precisely simulate intricate chemical systems expedites the process of research and development, satisfying the increasing need for state-of-the-art advancements in these vital domains.

The introduction of quantum computing in chemistry is mostly being driven by the need for a competitive edge. Businesses that use quantum computing technology can outperform their rivals by cutting expenses, speeding up research and development, and improving the accuracy of their chemical analysis. Faster discovery cycles and more effective chemical process optimization are made possible by quantum computing, which shortens the time it takes for new goods to reach the market. This edge over competitors is especially important in sectors like medicines, where being first to market may yield large financial rewards. By strategically using quantum computing, businesses may maintain their competitive edge in innovation, draw in top personnel, and maintain their leadership positions in the chemical sector.

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QUANTUM COMPUTING IN CHEMISTRY MARKET SHARE ANALYSIS:

North America is a market leader for quantum computing in chemistry, especially the United States. Both the governmental and commercial sectors have made significant expenditures in quantum technology, which is the reason for its supremacy. To encourage research and development in quantum computing, the US government has started a number of noteworthy projects, such as the National Quantum Initiative Act. Leading computer giants with American headquarters, like IBM, Google, and Microsoft, have set up specialized laboratories for quantum research, propelling the development of quantum hardware and software. Furthermore, universities and research centers in North America are leading the way in quantum chemistry research and collaborating with business to create useful applications. A vibrant market is created by the region’s robust venture capital environment, which helps firms that focus on quantum computing.

Key Players:

D-Wave SolutionsRigetti ComputingIntelAnyon Systems Inc.Cambridge Quantum Computing LimitedOrigin Quantum Computing TechnologyQuantum Circuits, Inc.

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DISCOVER MORE INSIGHTS: EXPLORE SIMILAR REPORTS!

–  The global market for Quantum Cryptography was estimated to be worth USD 3695.1 Million in 2023 and is forecast to a readjusted size of USD 16360 Million by 2030 with a CAGR of 23.4% during the forecast period 2024-2030.

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–  The global Quantum Computers market was valued at USD 101 Million in 2023 and is anticipated to reach USD 527.9 Million by 2030, witnessing a CAGR of 26.8% during the forecast period 2024-2030.

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–  The global Quantum Control Software market was valued at USD 65 Million in 2023 and is anticipated to reach USD 157.1 Million by 2030, witnessing a CAGR of 5.6% during the forecast period 2024-2030.

–  The global Quantum Dot (QD) Display market was valued at USD 4428 Million in 2023 and is anticipated to reach USD 5507.7 Million by 2030, witnessing a CAGR of 3.1% during the forecast period 2024-2030.

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–  The quantum photonics market was valued at USD 0.30 Billion in 2022, and is estimated to reach USD 5.3 Billion by 2032, growing at a CAGR of 33.2% from 2023 to 2032.

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–  Automotive Quantum Computing Market was valued at USD 103 Million in 2022 and is anticipated to reach USD 1127.1 Million by 2029, witnessing a CAGR of 49.0% during the forecast period 2023-2029.

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–  The global Cadmium Free Quantum Dot market is projected to reach USD 10620 Million in 2029, increasing from USD 3842 Million in 2022, with the CAGR of 15.7% during the period of 2023 to 2029.

–  The global High-performance Computing System market is projected to reach USD 64890 Million in 2029, increasing from USD 31970 Million in 2022, with the CAGR of 10.7% during the period of 2023 to 2029.

–  The global Cloud High Performance Computing (HPC) market was valued at USD 6862.1 Million in 2023 and is anticipated to reach USD 14620 Million by 2030, witnessing a CAGR of 11.3% during the forecast period 2024-2030.

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–  The global market for High Bandwidth Memory (HBM) was estimated to be worth USD 767.1 Million in 2023 and is forecast to a readjusted size of USD 4902.4 Million by 2030 with a CAGR of 25.5% during the forecast period 2024-2030.

–  The global Chemistry 4.0 market was valued at USD 68220 Million in 2023 and is anticipated to reach USD 145280 Million by 2030, witnessing a CAGR of 11.3% during the forecast period 2024-2030.

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–  The global Benchtop Clinical Chemistry Analyzers market was valued at USD 718.5 Million in 2023 and is anticipated to reach USD 1078.3 Million by 2030, witnessing a CAGR of 5.9% during the forecast period 2024-2030.

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–  The global Daily Chemical Grade Peach Aldehyde market was valued at USD 519.3 Million in 2023 and is anticipated to reach USD 635.9 Million by 2030, witnessing a CAGR of 3.2% during the forecast period 2024-2030.

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–  The global Lead Chemicals Market revenue was USD 1394.9 Million in 2022 and is forecast to a readjusted size of USD 1517.9 Million by 2029 with a CAGR of 1.2% during the forecast period (2023-2029).

–  The wet chemicals market was valued at USD 3.2 Billion in 2021, and is estimated to reach USD 5.9 Billion by 2031, growing at a CAGR of 6.3% from 2022 to 2031.

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Technology

JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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58 minutes ago

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July 24, 2026

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

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Video: CNPC offers green chemical answer

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July 24, 2026

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

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SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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July 24, 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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