> For the complete documentation index, see [llms.txt](https://docs.algenta.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.algenta.ai/physical-and-materials-science.md). # Physical & materials science - [Acoustics, optics & radiative materials](https://docs.algenta.ai/physical-and-materials-science/acoustics-optics-and-radiative-materials-kernels.md): Five independent physics-formula modules for sound and light — decibel levels and room acoustics, medical/industrial ultrasound imaging physics, blackbody and photon radiometry, fiber/optical photonic - [Structural & construction materials](https://docs.algenta.ai/physical-and-materials-science/structural-and-construction-materials-kernels.md): Adhesive bond strength and cure kinetics, fiber-composite mechanics, concrete mix design and curing, ceramic fracture statistics, polymer chain/molecular-weight science, and rubber/elastomer testing, - [Continuum and structural mechanics kernels](https://docs.algenta.ai/physical-and-materials-science/continuum-and-structural-mechanics-kernels.md): Classical point mechanics, beam/column structural analysis, Newtonian pipe-and-body fluid dynamics, non-Newtonian and viscoelastic rheology, and soil engineering split across its geotechnical and agro - [Corrosion & electrochemical materials](https://docs.algenta.ai/physical-and-materials-science/corrosion-and-electrochemical-materials-kernels.md): Corrosion rate and cathodic protection, electrochemical cell and battery equations, classical electrostatics and magnetism, metallurgical strengthening/hardenability, and semiconductor device physics - [Thermal, cryogenic & energy materials](https://docs.algenta.ai/physical-and-materials-science/thermal-and-energy-materials-kernels.md): Cryogenic and permafrost thermal physics, the four classical thermodynamic relations, battery electrochemistry, and solar/wind/photovoltaic energy-yield engineering across seven independent kernel mod - [Nanoscale, plasma & surface-contact engineering](https://docs.algenta.ai/physical-and-materials-science/advanced-nano-and-plasma-materials-kernels.md): Nanoscale surface/transport physics, plasma and fusion parameters, dry and lubricated contact mechanics with wear-corrosion coupling, and antenna/RF link-budget equations across five independent kerne - [Process & organic-materials science](https://docs.algenta.ai/physical-and-materials-science/process-and-organic-materials-science-kernels.md): Small scalar-formula libraries for eight process and organic-materials domains — brewing, bioprocess fermentation, food science, fragrance chemistry, pulp and paper, timber, textiles, and combustion. - [Materials analysis and spectroscopy kernels](https://docs.algenta.ai/physical-and-materials-science/materials-analysis-and-spectroscopy-kernels.md): Generic mechanics-of-materials formulas, chromatographic separation science, optical/analytical spectroscopy, treatment-plant water chemistry, and structural timber engineering across five independent --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.algenta.ai/physical-and-materials-science.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.