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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,738 papers · 148 categories

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6 results for “perovskite”

ABO3 Perovskites' Formability Prediction and Crystal Structure Classification using Machine Learningcond-mat.mtrl-sci

Machine learning predicts perovskite formability and classifies crystal structures.

problem Predicting and classifying perovskite formability and crystal structures.

method Machine learning, specifically Random Forest, with 5-fold cross-validation.

result 98.57% accuracy in predicting perovskite formability and 90.53% in classifying crystal structures.

perovskite formability machine learning crystal structure classification

2022-02-21abs ↗pdf ↗

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networkscond-mat.mtrl-sci

Leveraging new data sources is a key step in accelerating the pace of materials design and discovery. To complement the strides in synthesis planning driven by historical, experimental, and computed data, we present an automated method for connecting scientific literature to synthesis insights. Starting from natural la…

2018-12-31abs ↗pdf ↗

Simultaneous Optimization of Efficiency and Degradation in Tunable HTL-Free Perovskite Solar Cells with MWCNT-Integrated Back Contact Using a Machine Learning-Derived Polynomial Regressorcs.LG

Study optimizes HTL-free PSCs with MWCNTs, improving efficiency and stability.

problem Optimizing efficiency and degradation in HTL-free perovskite solar cells.

method Machine learning-driven framework integrating experimental validation and numerical simulations.

result Achieved RMSEs of 0.0179 and 0.0117 for efficiency and degradation, respectively.

Perovskite solar cells HTL-free Machine learning Degradation Efficiency

2025-05-24abs ↗pdf ↗

A cohomology-based Gromov-Hausdorff metric approach for quantifying molecular similaritymath.AT

New method uses cohomology to quantify molecular similarity.

problem Quantifying structural dissimilarity in molecular data.

method Gromov-Hausdorff ultrametric based on simplicial complexes and cohomology.

result Demonstrates effectiveness in clustering organic-inorganic halide perovskite structures.

cohomology Gromov-Hausdorff molecular similarity perovskite topology

2024-11-21abs ↗pdf ↗

Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledgestat.ML

Gryffin optimizes categorical variables in materials design, leveraging expert knowledge.

problem Optimizing categorical variables in complex design choices like molecule selection.

method Bayesian optimization with smooth approximations to categorical distributions, incorporating expert knowledge.

result Gryffin accelerates discovery of promising molecules and materials, highlighting relevant correlations.

Bayesian optimization categorical variables materials design expert knowledge organic solar cells

2020-03-26abs ↗pdf ↗

Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulationstat.ML

Gemini uses inexpensive measurements to correct biases in expensive property evaluations.

problem Accurate estimation of materials properties using expensive measurements is hindered in scientific discovery campaigns.

method Gemini is a data-driven model that corrects systematic biases between property evaluation methods using inexpensive measurements.

result Gemini reduces the number of expensive evaluations needed for Bayesian optimization in materials discovery.

Bayesian optimization autonomous experimentation molecular simulation systematic bias correction regression tasks

2021-03-05abs ↗pdf ↗