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Study Confirms: By-products from Lithium Production can be used in Cement Production

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Byproducts from Europe’s first lithium converter can compensate for the slowly reducing fly ash from the phasing-out of coal power, effectively reducing CO2 emissions in the construction industry.

Product properties of Portland cement are improved – Patent for production and use has been filed.

Rock Tech Lithium pursues a zero-waste strategy in Guben.

TORONTO, July 22, 2024 /PRNewswire/ – Rock Tech Lithium Inc. (TSXV: RCK) (OTCQX: RCKTF) (FWB: RJIB) (WKN: A1XF0V) (“Rock Tech” or the “Company”) is pleased to announce the findings of a peer-reviewed study published by the German Lithium Institute. The study finds that by-products from Rock Tech’s Lithium conversion process can be used as precursor material in the cement industry. Specifically, it has been confirmed that leached spodumene concentrate (LSC) generated during the production of lithium from spodumene holds substantial industrial potential. The material, primarily composed of aluminosilicates, can be used in the cement industry as an additive for cement, replacing previously used fly ash, a now slowly depleting by-product of coal-fired power generation. This means that the by-products of Rock Tech’s lithium production can ensure the regional supply security of the German cement industry with LSC and help reduce CO2 emissions.

Furthermore, it has been shown that the compressive strength of Portland cement, the most used type of cement worldwide, increases by ten percent when 20 percent LSC is added—regardless of the origin of the spodumene used. The process for producing and utilizing the LSC has been submitted for a patent.

The study was conducted within the Mineralogy and Geochemistry research group at the Martin Luther University Halle-Wittenberg by doctoral candidate and ITEL scholarship holder Julia Woskowski. Dr. Andreas Neumann, a member of the research group, explains: “The phase-out of coal and the transformation of the steel industry will sooner or later lead to changed or disappearing material streams that have been significant for the cement industry in terms of CO2 savings and product portfolio. The LSC from lithium production has the potential to compensate for these depleting material streams in the future.”

Jannik Schmitz, Supply Chain Manager at ITEL shareholder Rock Tech Lithium, adds: “ITEL’s study takes us a big step further on our path to CO2 neutrality and becoming the first zero-waste lithium company worldwide. It is important to note that the suitability of LSC as a cement additive is independent of the origin of the spodumene used. This confirms our choice of production process and our procurement strategy to source spodumene from several sustainably producing sources.”

The study was supported by ITEL’s shareholding companies, Rock Tech Lithium Inc., GP Günter Papenburg AG, and SCHWENK Zement GmbH & Co. KG. SCHWENK offers comprehensive supply of cement, concrete, sand & gravel, and pumping services in Germany. Dr. Thomas Neumann, Head of Research and Development at SCHWENK, explains: “The use of industrial residues from lithium production in cements and concretes significantly contributes to the conservation of valuable natural resources. Through innovative material use, we make an important contribution to achieving our sustainability goals. By integrating these residues, we can not only reduce environmental impact but also decrease CO2 emissions.”

Rock Tech plans to build Europe’s first lithium converter in Guben, Brandenburg. With an annual production capacity of 24,000 tons of lithium hydroxide, the converter can provide material for the construction of 500,000 electric batteries. Thus, the converter forms an important component of the battery value chain. Soon, capacities for material recycling will be developed. Additionally, the company aims to become the first zero-waste lithium company in the world through the complete reuse of byproducts. The company benefits from regional value chains and short distances.

ORIGINAL STUDY: J Woskowski, A Neumann, H Roggendorf, R Wehrspohn, S Stöber, “Properties of low sulfur leached spodumene as supplementary cementitious material in ordinary Portland cement” in Construction and Building Materials, Volume 438, page 137096 (2024), https://doi.org/10.1016/j.conbuildmat.2024.137096; as well as the associated patent application EP 2415 6323 at the European Patent Office.

ABOUT ROCK TECH

Rock Tech’s vision is to supply the electric vehicle and battery industry with sustainable, locally produced lithium, targeting a 100% recycling rate. To ensure resilient supply chains, the company plans to build lithium converters at the doorstep of its customers, beginning with the Company’s proposed Lithium Hydroxide Converter in Guben, Brandenburg, Germany. The second Converter is planned to be built in Red Rock, Ontario, Canada. Rock Tech Lithium plans to source raw material from its own Georgia Lake spodumene project in the Thunder Bay Mining District of Ontario, Canada, and procure from other ESG-compliant mines. Ultimately, Rock Tech’s goal is to create a closed-loop lithium production system. Rock Tech has gathered one of the strongest teams in the industry to close the most pressing gap in the clean mobility story. The Company has adopted strict environmental, social and governance standards and is developing a proprietary refining process to increase efficiency and sustainability further.

NEITHER THE TSX VENTURE EXCHANGE NOR ITS REGULATION SERVICES PROVIDER (AS THAT TERM IS DEFINED IN POLICIES OF THE TSX VENTURE EXCHANGE) ACCEPTS RESPONSIBILITY FOR THE ADEQUACY OR ACCURACY OF THIS RELEASE. 

CAUTIONARY NOTE CONCERNING FORWARD-LOOKING INFORMATION Certain statements contained in this news release constitute “forward-looking information” under applicable securities laws and are referred to herein as “forward-looking statements”. All statements, other than statements of historical fact, which address events, results, outcomes or developments that the Company expects to occur are forward-looking statements. When used in this news release, words such as “expects”, “anticipates”, “plans”, “predicts”, “believes”, “estimates”, “intends”, “targets”, “projects”, “forecasts”, “may”, “will”, “should”, “would”, “could” or negative versions thereof and other similar expressions are intended to identify forward-looking statements. In particular, this press release contains forward-looking information pertaining to expectations concerning the Guben Converter, including the design and features of the Guben Converter, as well as the expected costs, capital expenditures, timing and outcomes thereof; statements regarding the Company’s future plans, estimates, and schedules relating to the Guben Converter, including the anticipated timing of future activities taken in support of the development thereof; Rock Tech’s potential financing arrangements; the expected economic performance of the Guben Converter and anticipated production of battery-grade lithium hydroxide and related processing methods employed; the estimated capital and operating costs of the Guben Converter; the anticipated timing and outcomes of a final investment decision, construction activities and commissioning of the Guben Converter; statements regarding the Company’s sustainability and ESG related goals and strategy, including the benefits and achievement thereof and future actions taken by the Company in relation thereto; expected regulatory processes and final outcomes; expectations regarding the electric vehicle industry, including the demand for and pricing of battery-grade lithium hydroxide and the benefits therefrom, and the development of political and regulatory frameworks especially in Germany and the European Union; Rock Tech’s opinions, beliefs and expectations regarding the Company’s business strategy, development and exploration opportunities and projects; and plans and objectives of management for the Company’s operations and properties. Forward-looking statements by their nature are based on assumptions and involve known and unknown risks, uncertainties and other factors which may cause the actual results to differ materially from the forward-looking statements, including the risks, uncertainties and other factors discussed in the Company’s most recent management’s discussion and analysis and annual information form filed with the applicable securities regulators. No assurances can be given that any of the events anticipated by the forward-looking statements will transpire or occur, and the Company cautions the reader not to place undue reliance upon any such forward-looking statements. The Company does not intend, nor does it assume any obligation to update or revise any of the forward-looking statements, whether as a result of new information, changes in assumptions, future events or otherwise, except to the extent required by applicable law.

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SOURCE Rock Tech Lithium Inc.

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

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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.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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Video: CNPC offers green chemical answer

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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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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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