Aligned Data Centers has opened a new Advanced Cooling Lab at its Phoenix campus to accelerate the development of high-density data center cooling technologies. The lab serves as a testing ground for Aligned’s patented Delta Cube™ air cooling and patent-pending DeltaFlow~™ liquid cooling systems, designed to handle the rising thermal loads of next-generation GPUs and AI accelerators.
The facility is engineered to simulate hybrid cooling environments, enabling seamless transitions between air-cooled and liquid-cooled infrastructure within the same data hall. This flexibility supports Aligned’s broader Adaptive Modular Infrastructure (AMI) framework, which allows hyperscale and enterprise customers to future-proof their data center investments as compute density continues to rise. The company has positioned the lab as a centerpiece for R&D to address the evolving needs of high-performance computing and AI workloads.
With a decade-long track record in sustainable infrastructure innovation, Aligned is focused on maintaining high operational efficiency and low Power Usage Effectiveness (PUE). The new lab reflects the company’s strategic commitment to R&D as it scales its infrastructure portfolio to meet the surging demands of AI training and inference environments.
- Location: Phoenix, Arizona
- Features hybrid Delta Cube™ (air) and DeltaFlow~™ (liquid) cooling systems
- Supports live transitions from air- to liquid-cooling as density increases
- Purpose-built to accommodate next-gen GPUs and AI/HPC accelerators
- Integrated into Aligned’s Adaptive Modular Infrastructure (AMI)
- Enables rapid deployment of scalable and sustainable cooling for hyperscalers
“The Advanced Cooling Lab is a testament to our commitment to delivering cutting-edge data center solutions and our passion for innovation,” said Michael Welch, Chief Technology Officer at Aligned Data Centers. “By investing in research and development, we can continue to provide our customers with the most flexible and advanced infrastructure available, capable of handling the dynamic demands of AI workloads.”
