## 6 Conclusions and Future Work  
The findings from regression analysis enable engineers to make data-driven decisions about which TPMS structures and parameters to select based on specific application needs. This research is a data-driven prediction of performance outcomes where the influence of two parameters such as lattice thickness and cell size on both surface area to volume ratio and temperature difference are quantified. This is conducted for five TPMS structures providing specific information about which TPMS can be uniquely tunable and offer more flexibility. The ability to optimize trade-offs between surface area to volume ratio and thermal performance is critical for improving AWG efficiency.  
Furthermore, the use of a response optimizer with different sensitivity allows deviation of choices based on the importance of either or both responses. By applying this strategy, designers can fine-tune lattice geometry based on specific performance priorities such as energy efficiency or water collection rates. The approach in this study is more practical and simpler that can be utilized in new manufacturing processes, where the process is complex and might have insufficient data. In cases like this, the data are helpful to estimate process parameters such as manufacturability, and lead time, and to minimize the budget for processing. This is a methodological framework that demonstrates a systematic approach for navigating trade-offs of limited datasets for solving engineering problems. This tool can be useful for engineers solving problems in thermal management, sustainable design, and advanced manufacturing. Finally, this study enables innovation in atmospheric water harvesting, heat exchangers, biomimicry in the context of AWG, and complex 3D design structures that represent practical design choices from simulation data.  
In the next step, the best-suited models for the AWG application would be manufactured using additive/subtractive/hybrid methods for further experimentation. Todetermine the most viable outcomes, a thorough examination of material selection and manufacturing processes will be undertaken. This step is crucial in ensuring that the chosen condensation surface not only performs optimally in terms of efficiency but is also feasible for real-world applications. The goal is to identify the best-performing condensation surface with the feasibility of materials, processes, and geometry. This integrated approach will pave the way for innovative advancements in AWG technology, addressing the critical global issue of freshwater scarcity.  
Conceptualization, F.T.Z. and B.A.; methodology, F.T.Z.; software, F.T.Z.; validation, F.T.Z.; formal analysis, F.T.Z.; investigation, F.T.Z.; resources, F.T.Z.; data curation, F.T.Z.; writing--original draft preparation, F.T.Z.; writing--review and editing, F.T.Z. and B.A.; visualization, F.T.Z.; supervision, B.A.; project administration, B.A.; funding acquisition, B.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the US Department of Agriculture (USDA), grant number 2020-38422-33097.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} AWG & Atmospheric Water Generation \\ TPMS & Triply Periodic Minimal Surface \\ TAR & thermoacoustic refrigeration \\ ABS & acrylonitrile butadiene styrene \\ SA/V\({}_{\text{S}}\) & ratio of the surface area to the volume of solid \\ C & cell type \\ T & lattice thickness \\ X & cell size \\ \(\Delta\Gamma\) & temperature difference \\ \end{tabular}