Paramus HKL Viewer
UI (Human) Applications MIT (Free)
About
Crystallographic reflection data viewer for .hkl files. Visualize reflection intensity distributions and resolution shells during structure determination.
Key Features
- Native .hkl file viewer
- Reflection intensity plotting
- Resolution shell statistics
- Workbench file-association integration
- Read-only viewer (no edits)
Frequently Asked Questions
What is Paramus HKL Viewer?
Paramus HKL Viewer is a ui (human) applications application available in the Paramus App Store. Crystallographic reflection data viewer for .hkl files. Visualize reflection intensity distributions and resolution shells during structure determination.
Is Paramus HKL Viewer free to use?
Yes. Paramus HKL Viewer is distributed under the MIT (Free) license and is available at no cost through the Paramus App Store.
How do I install Paramus HKL Viewer?
Paramus HKL Viewer is installed through Paramus Chemistry OS, an on-premise Windows platform for computational chemistry. Open the Paramus App Store in your local installation and select Paramus HKL Viewer for one-click deployment.
What are the key features of Paramus HKL Viewer?
Key features of Paramus HKL Viewer include: Native .hkl file viewer; Reflection intensity plotting; Resolution shell statistics; Workbench file-association integration.
What type of application is Paramus HKL Viewer?
Paramus HKL Viewer belongs to the “UI (Human) Applications” category in the Paramus App Store. It runs on Paramus Chemistry OS and can also be accessed through Paramus Cloud for supported workflows.
What platform does Paramus HKL Viewer run on?
Paramus HKL Viewer runs on Paramus Chemistry OS, a Windows-based on-premise platform that provides local compute power for demanding simulations. It requires a Paramus OS installation with appropriate hardware resources.
Can Paramus HKL Viewer be automated or integrated with AI workflows?
Yes. Paramus HKL Viewer is available as part of the Paramus ecosystem which supports MCP (Model Context Protocol) tools for AI-driven automation. This enables integration with large language models and automated research pipelines.