Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.

Urban building energy modeling (UBEM) seeks to evaluate strategies to optimize building energy use at urban scale to support a city's building energy goals. Prototype building models are usually developed to represent typical urban building characteristics of a specific use type, construction year, and climate zone, as detailed characteristics of individual buildings at urban scale are difficult to obtain. This study investigated the Italian building stock, developing 46 building prototypes, based on construction year, for residential and office buildings. The study included 16 single-family buildings, 16 multi-family buildings, and 14 office buildings. Building envelope properties and heating, ventilation, and air conditioning system characteristics were defined according to existing building energy codes and standards for climatic zone E, which covers about half the Italian municipalities. Novel contributions of this study include (1) detailed specifications of prototype building energy models for Italian residential and office buildings that can be adopted by UBEM tools, and (2) a dataset in GeoJSON format of Italian urban buildings compiled from diverse data sources and national standards. The developed prototype building specifications, the building dataset, and the workflow can be applied to create other building prototypes and to support Italian national building energy efficiency and environmental goals.

Nowadays, collagen hydrogels with both good physicochemical and antibacterial properties for tissue engineering have drawn broad attention. Herein, a biocompatible and antibacterial collagen hydrogel is developed via alginate dialdehyde (ADA) modification and tetracycline hydrochloride (TC) loading based on Schiff's base formation. Fourier transform infrared spectroscopy and X‐ray diffraction spectra suggest the maintenance of collagen structure integrity after ADA modification. The modification significantly contributes to the improved swelling property, resistance against type I collagenase, and strengthens storage modulus of hydrogels with an increase of ADA concentrations. Meanwhile, dynamic release curves of tetracycline hydrochloride (TC)‐loaded hydrogels describe the burst release at the first 15 min then a gradual release, hydrogels act ideally as carriers in antibacterial activity. Furthermore, in vitro biocompatibility and antibacterial properties are successfully confirmed from the fabricated collagen hydrogels. This physicochemical‐ and antibacterial‐property–improved collagen hydrogel would be a potential candidate for wound healing as a scaffold.

Urban microclimate exerts an increasing influence on urban buildings, energy, and sustainability. This study uses 10-year measured hourly weather data at 27 sites in San Francisco, California, to (1) analyze and visualize the urban microclimate patterns and urban heat island effect;(2) simulate annual energy use and peak electricity demand of typical large office buildings and large hotels to investigate the influence of urban microclimate on building performance; (3) simulate indoor air temperature of a single-family house without air-conditioning during the record threeday heatwave of 2017, to quantify the divergence of climate resilience due to urban microclimate effect. Results show significant microclimate effects in San Francisco with up to 11℃ outdoor air temperature difference between the coastal and downtown areas on September 1, 2017, during the record three-day heatwave. The simulated energy results of the prototype large office and large hotel buildings using the 2017 weather data show over 100% difference in annual heating energy use and 65% difference in annual cooling energy use across different stations; as well as up to 30% difference in peak cooling electricity demand. The impacts on annual site or source energy use are minimal (less than 5%) as cooling and heating in a mild climate are a relatively small portion of overall building energy use in San Francisco. Results also show the microclimate effects influence indoor air temperature of unconditioned homes by up to 5℃. Newer buildings and homes are much less affected by microclimate effects due to more stringent performance requirements of the building envelope and energy systems. These findings inform that San Francisco microclimate variations should be considered in urban energy planning, building energy codes and standards, as well as heat resilience policymaking.

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