arXiv subjects

Forrest Meggers

Publications and source records attributed to Forrest Meggers.

3 recordsLinked to original sources

arXiv2026

Laser-Architected Surface Wetting

Technologies that require surface wetting or evaporative cooling require the ability to efficiently spread fluids across large areas, as increased wetted surface area increases evaporative flux. However, the intrinsic surfacial and bulk properties of most engineered materials substantially limit the rate and magnitude of surface wetting and lack control of flow direction, preventing them from rapidly wetting large surfaces. Here, we introduce our approach for rapid and controlled wetting of surfaces by laser-engraving channel networks that provide pathways for rapid, long-distance (cm-dm scale) capillary fluid propagation across the area, while the intrinsic material properties enable slow, short-distance (mm-cm scale) surface wetting. We investigated this approach on hardened cement paste and showed that laser engraving is a fabrication-friendly, scalable, and reproducible solution for creating channels with properties conducive to capillary fluid propagation. We demonstrate that the rate and direction of surface wetting can be controlled by tuning the channel network density, channel network anisotropy, and supplied fluid flow rate. The integration of laser-engraved channel networks demonstrated significantly greater wetting performance (up to 10-fold greater wetted area and up to 180-fold greater wetting performance when wetted area is adjusted for fluid use efficiency) and greater evaporative cooling (up to 1.8 {\deg}C cooler surfaces) compared to control (hardened cement paste without laser-engraved channel networks).

physics.app-ph↗

arXiv2026

How do sub-bandgap reflectors affect the performance of PV modules?

Sub-bandgap reflectors (SBR) can reduce the temperature of photovoltaic (PV) modules by reflecting the near-infrared region of the solar spectrum with photon energies smaller than the electronic bandgap of the solar cell absorber material. We consider an ideal SBR, which reflects 100 % of non-harvestable low-energy photons but does not alter the reflectivity of the PV module for usable high-energy photons, and estimate how reducing the module temperature with the SBR affects the annual and the cumulative energy yield of silicon PV modules for six locations in North America and Europe. An ideal SBR would increase the annual energy yield between 1.0 % and 1.5 % for open-rack mounted modules and between 1.6 % and 2.4 % for close-roof mounted PV modules. Whether a non-ideal SBR provides a benefit in actual deployments strongly depends on the location and the optical properties of the coating. Beyond effects on the instantaneous power conversion efficiency and hence the annual energy yield, reducing the temperature by a SBR might also reduce the degradation and increase the overall lifetime of the PV module. By describing degradation using a simple Arrhenius approach using typical activation energies between 0.4 eV and 0.8 eV, we find that an ideal SBR increases the cumulative energy yield over 30 years between 2.2 % and 4.0 % for an open-rack mounted PV module in Princeton, New Jersey, USA.

physics.app-ph↗

arXiv2020

The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition

This paper describes an open data set of 3,053 energy meters from 1,636 non-residential buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 measurements per meter resulting in approximately 53.6 million measurements). These meters were collected from 19 sites across North America and Europe, with one or more meters per building measuring whole building electrical, heating and cooling water, steam, and solar energy as well as water and irrigation meters. Part of these data were used in the Great Energy Predictor III (GEPIII) competition hosted by the ASHRAE organization in October-December 2019. GEPIII was a machine learning competition for long-term prediction with an application to measurement and verification. This paper describes the process of data collection, cleaning, and convergence of time-series meter data, the meta-data about the buildings, and complementary weather data. This data set can be used for further prediction benchmarking and prototyping as well as anomaly detection, energy analysis, and building type classification.

stat.AP↗