Skip to content
#small language model Open access

An Edge-AI-Driven Crystal Structure Exploration Tool for Secondary School Chemistry: Design and Implementation

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Materials Science

Abstract

Crystal structure is one of the most abstract topics in secondary school chemistry. Textbookspresent three-dimensional lattices as flat diagrams, and physical models cannot be modified, sostudents often memorize conclusions such as "NaCl has a coordination number of 6" withoutunderstanding how structure determines properties. Professional crystallography software is powerfulbut far too complex for students, while online viewers are mostly read-only and cannot answer"what-if" questions. This project presents Crystallographer, an offline crystal exploration tool built on a four-layerarchitecture: (1) a natural-language understanding layer powered by on-device Gemma 4 E2B, whichtranslates student requests into standard tool calls; (2) a device-independent crystal structurefile layer; (3) a deterministic display and computation layer for 3D views, plane projections,cross-sections, density, packing fraction, coordination number, radius ratio and lattice energy;and (4) a teaching layer with guided task cards. The model is converted locally from HuggingFacesafetensors to GGUF Q4_K_M (3.19 GiB) together with a 940 MB multimodal projector (mmproj), andserved by llama.cpp with Vulkan. Using the OpenAI-compatible function-calling protocol, an agentwith 21 crystal tools builds or edits structures, validates them (electroneutrality, overlap,density, coordination) and self-corrects from the feedback. The system also embeds an offline MP-20 database of 44,217 inorganic crystals searchable bychemical formula, and a camera mode that recognizes Chinese exam questions from photos, reproducesthe unit cell and solves the problem with deterministic tools. Benchmarks on three Vulkan devicesshow that single-GPU inference reaches 1929 t/s prompt processing and 66 t/s generation, whereascross-device layer splitting is significantly slower for small models; the default strategy istherefore performance-first with multi-device options. A deterministic engine verified by 38 unittests matches literature values (e.g., NaCl density 2.163 g/cm3, coordination number 6, radiusratio 0.564), and Playwright end-to-end tests cover the full natural-language workflow.

View source

Similar papers

#small language model Dataset Open access Oct 2026

Socratic guiding questions in synthetic arithmetic data: matched LoRA runs (revision v2)

Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...

O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al. · 465 citations
#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.