ArticleJournal of the American Chemical Society2023
Predictive Synthesis of Copper Selenides Using a Multidimensional Phase Map Constructed with a Data-Driven Classifier.
Article in Journal of the American Chemical Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
12 citing papers in PubMed.
- Solution Synthesis of Actinide Chalcogenide and Oxychalcogenide Nanoparticles.Angewandte Chemie (International ed. in English) · 2026Article
- Unlocking Klockmannite: Formation of Colloidal Quasi-2D CuSe Nanocrystals and Photo-Physical Properties Arising From Crystal Anisotropy.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Copper Selenides via Anion Exchange versus Direct Growth - The Role of Diorganyl Diselenides.Inorganic chemistry · 2025Article
- Prospects of Nanoscience with Nanocrystals: 2025 Edition.ACS nano · 2025Review
- Band Gap Engineering and Metastable Phase Discovery in CuJournal of the American Chemical Society · 2025Article
- Data-Driven Mapping of the Cesium Cadmium Bromide Phase Space Utilizing a Soft-Chemistry Approach.Inorganic chemistry · 2025Article
- A Holistic Data-Driven Approach to Synthesis Predictions of Colloidal Nanocrystal Shapes.Journal of the American Chemical Society · 2025Article
- Colloidal AInSeACS nanoscience Au · 2024Article
- Rational Phase Control in the Synthesis of Cobalt Sulfides.Chemistry of materials : a publication of the American Chemical Society · 2024Article
- Controlling Phase in Colloidal Synthesis.ACS nanoscience Au · 2024Review
- Multivariate Bayesian Optimization of CoO Nanoparticles for COJournal of the American Chemical Society · 2024Article
- Using Data-Driven Learning to Predict and Control the Outcomes of Inorganic Materials Synthesis.Inorganic chemistry · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Copper selenides are an important family of materials with applications in catalysis, plasmonics, photovoltaics, and thermoelectrics. Despite being a binary material system, the Cu-Se phase diagram is complex and contains multiple crystal structures in addition to several metastable structures that are not found on the thermodynamic phase diagram. Consequently, the ability to synthetically navigate this complex phase space poses a significant challenge. We demonstrate that data-driven learning can successfully map this phase space in a minimal number of experiments. We combine soft chemistry (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.