Download site/understand/limits.html from Babu09/MEIDNet: direct link, hf CLI and curl.
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https://huggingface.co/spaces/Babu09/MEIDNet/resolve/main/site/understand/limits.html
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hf download hf://spaces/Babu09/MEIDNet/site/understand/limits.html
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curl -L -o limits.html https://huggingface.co/spaces/Babu09/MEIDNet/resolve/main/site/understand/limits.html
47.2 kB
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| Learn | |
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| Learn multimodality | |
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| Architectures | |
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| Recipes by problem | |
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| Scope, limitations and roadmap | |
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| Table of contents | |
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| Limitations | |
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| What a dataset needs | |
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| Current capabilities | |
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| Not yet supported | |
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| Roadmap (in order of likely value) | |
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| The ecosystem | |
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| MEIDNet Benchmarks | |
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| Benchmark compatibility | |
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| Perov-5: alignment across seeds | |
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| Perov-5: what the runs show | |
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| Perov-5: choose a model and generate | |
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| MP-20 | |
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| Carbon-24 | |
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| <h1 id="scope-limitations-and-roadmap">Scope, limitations and roadmap<a class="headerlink" href="#scope-limitations-and-roadmap" title="Permanent link">¶</a></h1> | |
| <p>These pages document the released package, meidnet 2.3.1. MEIDNet Matter, the applied companion, runs a development | |
| snapshot of the engine and states the measured limits of its five case studies on its | |
| <a href="https://babu09-meidnet-matter.hf.space/limits">Scope and limits page</a>.</p> | |
| <h2 id="limitations">Limitations<a class="headerlink" href="#limitations" title="Permanent link">¶</a></h2> | |
| <ul> | |
| <li><strong>A candidate is a proposal.</strong> It is a composition placed on a family prototype, with properties predicted by the | |
| model. Nothing in the package runs DFT. <code>meidnet screen</code> relaxes candidates with MACE-MP-0 and applies a | |
| formation-energy filter (at most 0.10 eV/atom against the elemental phases): a first filter, not stability on the | |
| convex hull (<a href="../recipes/screen.html">screening</a>).</li> | |
| <li><strong>The published model knows one chemistry.</strong> It was trained on Perov-5, its test split included: cubic ABX₃ cells | |
| of five atoms whose anion sites hold oxygen and nitrogen, with fluorine and sulfur only in mixed sets. Perov-5 has no | |
| Cl, Br, I or Se, and La is its only lanthanide, so halide and lanthanide candidates from this model are | |
| extrapolations; the demo and the Studio nevertheless start from the halide variant.</li> | |
| <li><strong>Its property predictions are rough.</strong> On Perov-5's test split, which was part of its training data, the band gap | |
| read from a structure alone misses by 2.79 eV on average, against 0.17 eV for always predicting the training mean | |
| (1.68 against 2.14 eV on the non-zero gaps); the formation enthalpy does better than the mean (0.40 against | |
| 0.57 eV/atom). See the <a href="../benchmarks/perov5.html">Perov-5 leaderboard</a>.</li> | |
| <li><strong>What has been validated.</strong> Only Perov-5 has a benchmark protocol. Its inverse-design score combines the | |
| formation-energy filter, uniqueness, novelty and a DFT check that is possible only where Perov-5 holds the same sites, | |
| in practice for oxides: the published model met the band-gap target in 1 of 18 such checks, and its ΔHf·U·N (0.611) | |
| is below both baselines (0.778 and 0.852). MP-20 and Carbon-24 have no protocol yet. Nothing has been tested | |
| experimentally.</li> | |
| <li><strong>Which crystal structures.</strong> Both built-in families are cubic: Pm-3m ABX₃, and Fm-3m A₂BB′X₆ in its rhombohedral | |
| primitive cell. A family file may use a general cell (<code>a, b, c, alpha, beta, gamma</code>); it is scaled from one edge with | |
| its shape fixed, needs a model trained on structures of that prototype, and its rules must be written for it, since | |
| the tolerance and octahedral factors are perovskite rules. No non-cubic family ships or has been tested, and the | |
| hosted Studio takes the built-in families only.</li> | |
| <li><strong>The rules are approximations.</strong> The tolerance and octahedral factors use ionic radii averaged over every oxidation | |
| state pymatgen lists, which shrinks every anion except oxygen: with the built-in bounds, CsPbBr₃ (octahedral factor | |
| 1.27) and CsPbCl₃ (1.44) fail the 0.90 limit. Read halide and nitride results with this in mind; a fix will use the | |
| radius of the oxidation state that balances charge.</li> | |
| </ul> | |
| <h2 id="what-a-dataset-needs">What a dataset needs<a class="headerlink" href="#what-a-dataset-needs" title="Permanent link">¶</a></h2> | |
| <p>What the rows contain matters more than how many there are. Measured on MEIDNet Matter's case studies:</p> | |
| <table> | |
| <thead> | |
| <tr> | |
| <th>to do this</th> | |
| <th>what it needs</th> | |
| <th>measured</th> | |
| </tr> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>predict a property from structure</td> | |
| <td>a well-posed property: continuous, few zero values, few materials sharing one property profile</td> | |
| <td>166 training structures read a band gap with r 0.97 and a 0.65 eV error (34 test structures); 897 with 35 % zero gaps fell short on telling metals from non-metals</td> | |
| </tr> | |
| <tr> | |
| <td>screen an enumerated family</td> | |
| <td>data that fit one family, and a property model that passes</td> | |
| <td>166 to 897 training structures</td> | |
| </tr> | |
| <tr> | |
| <td>generate</td> | |
| <td>one prototype, and hundreds of distinct compositions per element for the decoder</td> | |
| <td>Perov-5 generates; data with 11 to 48 compositions per element went to screening</td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <p>A few hundred structures train a property model, not a generator. The package's own checks: <code>meidnet check</code> warns | |
| below 200 usable rows; the training report's note below 500 training materials is a rule of thumb, not a measurement; | |
| training needs at least <code>batch_size</code> materials (16 by default); the validation split is a random 10 %, and there is | |
| none below 10 rows. The published model cannot be fine-tuned on new properties yet, so a small dataset trains a model | |
| from scratch. <a href="../start/what-data.html">What data do I need?</a></p> | |
| <h2 id="current-capabilities">Current capabilities<a class="headerlink" href="#current-capabilities" title="Permanent link">¶</a></h2> | |
| <table> | |
| <thead> | |
| <tr> | |
| <th></th> | |
| <th></th> | |
| </tr> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td><strong>Structures</strong></td> | |
| <td>any CIF with up to <code>max_sites</code> atoms (default 20); any elements</td> | |
| </tr> | |
| <tr> | |
| <td><strong>Properties</strong></td> | |
| <td>any number of scalar columns</td> | |
| </tr> | |
| <tr> | |
| <td><strong>Training</strong></td> | |
| <td>your data, your properties; the published settings by default</td> | |
| </tr> | |
| <tr> | |
| <td><strong>Generation</strong></td> | |
| <td>prototype families: a fixed arrangement of sites whose occupants and cell size are chosen. Built in: cubic ABX₃, A₂BB′X₆; write your own in YAML</td> | |
| </tr> | |
| <tr> | |
| <td><strong>Rules</strong></td> | |
| <td>charge balance, tolerance and octahedral factors, bond windows, minimum distance, predicted-property windows, element filters, and your own Python rules</td> | |
| </tr> | |
| <tr> | |
| <td><strong>Explanations</strong></td> | |
| <td>reports for data, training and generation; the Studio for live what-if</td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <p>On the hosted Studio: up to 1,500 rows and 8 MB per upload, 30 training epochs, 20 atoms per cell | |
| (<a href="../use/studio.html">the Studio</a>).</p> | |
| <h2 id="not-yet-supported">Not yet supported<a class="headerlink" href="#not-yet-supported" title="Permanent link">¶</a></h2> | |
| <ul> | |
| <li><strong>New atomic arrangements.</strong> The decoder's positions are not used to create geometry; candidates are | |
| compositions placed on the family prototype. Generating free geometry needs a decoder trained to produce it | |
| (the published decoder receives the true positions during training). MEIDNet Matter runs a development snapshot of | |
| the engine, meidnet 2.4.0.dev4, whose symmetry decoder, trained on MP-20, builds new cells without a family and | |
| samples at the target's anchor instead of optimising the latent point. It is not in a release of this package yet; | |
| its measured limits (on MP-20 more than half of the relaxed cells collapse, and a delivered gap is good to about | |
| ±0.7 eV) are on <a href="https://babu09-meidnet-matter.hf.space/limits">Matter's Scope and limits page</a>.</li> | |
| <li><strong>Spectra, images, text as modalities.</strong> The property modality is a vector of scalars. Binned XRD or DOS | |
| could be added as a vector modality with its own encoder; it is designed for but not implemented.</li> | |
| <li><strong>Large cells.</strong> <code>max_sites</code> can be raised, but memory and time grow with the square of it, and the | |
| published model was trained on 5-atom cells.</li> | |
| <li><strong>Fine-tuning the published model on new properties.</strong> Its property head has two outputs; train a new model.</li> | |
| </ul> | |
| <h2 id="roadmap-in-order-of-likely-value">Roadmap (in order of likely value)<a class="headerlink" href="#roadmap-in-order-of-likely-value" title="Permanent link">¶</a></h2> | |
| <ol> | |
| <li>Vector modalities (XRD, DOS) with a shared-latent encoder each.</li> | |
| <li>A <code>training.init_from</code> option to continue training from a checkpoint with the same properties.</li> | |
| <li>A geometry-generating decoder variant (trained from prototype positions instead of true positions — | |
| <code>model.decoder_coordinate_input: prototype</code> is the first step and is available as an experimental setting).</li> | |
| <li>More built-in families (spinel, Heusler, rocksalt/zincblende, MXene M₂XT₂).</li> | |
| <li>Ionic radii from the charge-balancing oxidation state in the tolerance and octahedral factors.</li> | |
| </ol> | |
| <p>Contributions of family files and rules are the easiest way to help; see the GitHub repository.</p> | |
| </article> | |
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