# A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research
## 3 Results  
This section discusses the results obtained from analyzing the pool of 22 relevant studies after carefully applying the previously defined taxonomy. A list of studies with respect to the key points investigated is provided in Tables 3 and 4. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Authors** & **Domain** & **Application** & **Technique** & **Task** \\ \hline [PERSON] et al. (2017) & General framework & Chemistry & Tree-based regression & Assistance in robustness estimation \\ \hline [PERSON] et al. (2018) & General framework & Chemistry & BO & Optimization of experimental constraints \\ \hline [PERSON] et al. (2019) & Chemistry & Optimization of different terminal alkynes’ reaction routes & BO & Selecting experiments and optimizing experimental design \\ \hline [PERSON] et al. (2011) & Materials science & Nano-manufacturing of lead-free metal halide perovskite nanocrystals & BO & Selecting experiments and optimizing experimental design \\ \hline [PERSON] et al. (2020) & Materials science & Microfluidic material synthesis & Single-period RL + surrogate model (Naive classifier + GPR) & Surrogate model determines the feasibility of experimental parameters and predicts output; RL selects experiments \\ \hline [PERSON] et al. & Biology & Extraction of cannabinoids & RF & Prediction of experimental yields under different experiment conditions; assistance in decision-making \\ \hline [PERSON] et al. (2022) & Chemistry & Reduction of reaction screening & AL: ENN; single-trained models with MC dropout masks & Selecting experiments and optimizing experimental design \\ \hline [PERSON] et al. (2016) & Materials science & Composition-structure phase mapping & BO & Selecting experiments and optimizing experimental design assisted by humans \\ \hline [PERSON] et al. (2023) & Materials science & Carbon nanotube growth & AL: Jump regression surrogate & Selecting experiments and optimizing experimental design \\ \hline [PERSON] et al. (2024) & Materials science & High-throughput electrical conductivity optimization and discovery of doped conjugated polymers & RF classifier + LASSO regression & Classifier excludes low conductivity material; regressor predicts experimental output \\ \hline [PERSON] et al. (2025) & Fabrication & Quality control for probe precision forming in semiconductor manufacturing & GA (fitness function: PLSR) & Selecting experiments and optimizing experimental design \\ \hline [PERSON] et al. (2026) & Materials science & Catalyst design and optimization & LLM + BO & LLM extracts process data; BO selects experiments and optimizes experimental design \\ \hline [PERSON] et al. (2027) & Chemistry & Temporal analysis of products & Model-based design of experiments & Selecting experiments and optimizing experimental design \\ \hline [PERSON] et al. (2028) & Chemistry & Sustainable chemistry processes & MOBO, AL: RF & Selecting experiments and optimizing experimental design \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Overview of the analyzed papers regarding domains, applications, techniques, and tasks.