用多保真度方法加速氧化物半导体掺杂筛选，显著降低计算成本。
Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel
- 结合廉价预测与分层验证，减少81%的DFT计算量
- 在529个候选中精准找到最优的铜钇共掺锌氧化物（带隙1.84 eV）
- 适用于材料设计、高通量筛选及开放共享的基准测试
通过掺杂调控氧化物半导体的带隙对光催化和光电应用至关重要，但掺杂元素、取代位点及共掺组合的组合空间远超典型密度泛函理论（DFT）计算预算。本研究在五种氧化物基体（ZnO、TiO₂、SrTiO₃、SnO₂、MgO）中筛选掺杂候选，完成529个锌氧化物共掺方案，识别出含铜的共掺体系可稳定实现可见光范围带隙（1.0–1.8 eV），其中Y₂Cu₂共掺锌氧化物为最优候选（1.84 eV）。三级验证流程（PBE、PBE+U、离子弛豫）表明单一理论层级不足以准确评估：钒掺杂锌氧化物在加入Hubbard U后由近金属性转为宽禁带，而铜掺杂锶钛酸盐仅在纠正d电子局域化后才进入可见光响应区。为提升效率，提出多保真度筛选策略，将81%的DFT评估替换为低成本代理预测，使529候选闭环量子表达（Quantum ESPRESSO）任务从预计440小时降至62小时，且在50次独立试验中100%找到全局最优解（与随机筛选相比p=5.0e-8，Wilcoxon符号秩检验）。跨基体分析揭示掺杂性能仅受两个隐含化学维度支配，可预测未见基体中的排序。所有583次DFT计算、筛选代码与稳定性证明均开源发布，构成开放基准。
原文摘要 · Abstract (English)
Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant elements, substitution sites, and co-doping combinations far exceeds typical density functional theory (DFT) budgets. We screen doped candidates across five oxide hosts (ZnO, TiO2, SrTiO3, SnO2, MgO), culminating in a 529-candidate ZnO co-doping campaign, and identify Cu-containing co-doped ZnO systems as consistently achieving visible-light-range band gaps (1.0-1.8 eV), with Y2Cu2 co-doped ZnO as the optimal candidate (1.84 eV). A three-tier validation funnel (PBE, PBE+U, ionic relaxation) reveals that no single level of theory suffices: V-doped ZnO shifts from near-metallic to wide-gap upon Hubbard U correction, while Cu-doped SrTiO3 enters the visible-light window only after correcting for d-electron localization. To make this screening tractable, we introduce a multi-fidelity screening strategy that replaces 81% of DFT evaluations with computationally inexpensive surrogate predictions, reducing a 529-candidate closed-loop Quantum ESPRESSO campaign from an estimated 440 to 62 CPU-hours while finding the global optimum in 100% of 50 independent trials (p = 5.0e-8 versus random screening, Wilcoxon signed-rank). Cross-host analysis of the dopant-host interaction matrix reveals that dopant performance is governed by just two latent chemical dimensions, enabling prediction of rankings in unseen hosts. All 583 DFT calculations, screening code, and stability proofs are released as an open benchmark.
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