ABSTRACT
Metal-organic frameworks (MOFs) featuring composition and bandstructure diversity, are an emerging class of photoresponsive disinfectants. In this study, we demonstrated the superiority of core–shell arranged photoactive MOFs (prussian blue (PB) and zeolitic imidazolate framework (ZIF-8)) for pathogen inactivation in terms of biocidal efficiency and broad-spectrum sensitivity. Reactive oxygen species (ROS) production was significantly promoted after the integration of PB due to the photosensitization effect and initiation of in situ Fenton reaction. Favorably, another inactivation channel was also opened owing to the unique photothermal effect of PB. Attributed to the facilitated ROS intracellular penetration by heat, the composite outperforms not only individual component but anatase TiO2 in pathogen elimination. Specifically, the Staphylococcus aureus (S. aureus) inactivation efficiency of the composite (6.6 log) is 2, 1.8 and 5.1 times higher than that of PB (3.3 log), ZIF-8 (3.7 log) and TiO2 (1.3 log) over 45 min of simulated sunlight illumination. Significantly, the infectivity of Bacillus anthracis and murine coronavirus in droplets on composite-coated filter surface could be greatly reduced (approximately 3 log reduction in colony number/coronavirus titer) within few minutes of solar exposure, indicative of the great potential of MOF composites toward life-threatening microbial infection prevention. © 2022 Elsevier B.V.
ABSTRACT
To support building operations in reaching ultra-low energy targets, this paper proposes a data-informed building energy management (DiBEM) framework to improve energy efficiency systematically and continuously at the operation stage. Specifically, it has two key features including data-informed energy-saving potential identification and data-driven model-based energy savings evaluation. The paper demonstrates the proposed DiBEM with a detailed case study of an office and living laboratory building located in Cambridge, Massachusetts called HouseZero. It focuses on revealing the performance of the energy-efficient interventions from two-years' building performance monitoring data, as well as evaluating energy savings from the interventions based on the data-driven approach. With Year 1 as baseline, several interventions are proposed for Year 2 including improvements to controls and operation settings, encouragement of occupants' behavior for energy savings, and hardware retrofitting. These were deployed to heating/cooling, domestic hot water, lighting, plug and other loads, and photovoltaic (PV) systems. To quantify the impacts of different interventions on energy end uses, several data-driven models are developed. These models utilize linear regression, condition model, and machine learning techniques. Consequently, the heating/cooling energy consumption that was already ultra-low in Year 1 (12.8 kWh/m2) is further reduced to 9.7 kWh/m2 in Year 2, while the indoor thermal environment is well maintained. The domestic hot water energy is reduced from 2.3 kWh/m2 to 1.2 kWh/m2. The lighting energy is only increased from 0.3 kWh/m2 in pandemic operations without occupancy in Year 1 to 0.8 kWh/m2 in partial normal operations in Year 2, while the indoor illuminance level meets occupants' requirements. Combined with other relatively constant loads and the reduction of plug and other loads due to COVID building operation restrictions, the total energy use intensity is thereby reduced from 54.1 kWh/m2 to 42.8 kWh/m2, where 5.4 kWh/m2 of energy reduction for Year 2 is estimated to be contributed by the energy-efficient interventions. PV generation is 36.1 kWh/m2, with an increase of 1.4 kWh/m2 from a new inverter. In summary, this paper demonstrates the use of DiBEM through a detailed case study and long-term monitoring data as evidence to achieve ultra-low energy operations. © 2022 Elsevier B.V.
ABSTRACT
BACKGROUND: Recent advances in CRISPR-based diagnostics suggest that DETECTR, a combination of reverse-transcriptase loop-mediated isothermal amplification (RT-LAMP) and subsequent Cas12 bystander nuclease activation by amplicon-targeting ribonucleoprotein complexes, could be a faster and cheaper alternative to quantitative reverse-transcription polymerase chain reaction (qRT-PCR) without sacrificing sensitivity and/or specificity. METHODS: In this study, we compare DETECTR with qRT-PCR to diagnose coronavirus disease 2019 on 378 patient samples. Patient sample dilution assays suggest a higher analytical sensitivity of DETECTR compared with qRT-PCR; however, this was not confirmed in this large patient cohort, where we report 95% reproducibility between the 2 tests. RESULTS: These data showed that both techniques are equally sensitive in detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) providing additional value of DETECTR to the currently used qRT-PCR platforms. For DETECTR, different guide ribonucleic acids can be used simultaneously to obviate negative results due to mutations in N-gene. Lateral flow strips, suitable as a point-of-care test, showed a 100% correlation to the high-throughput DETECTR assay. More importantly, DETECTR was 100% specific for SARS-CoV-2 relative to other human coronaviruses. CONCLUSIONS: Because there is no need for specialized equipment, DETECTR could be rapidly implemented as a complementary technically independent approach to qRT-PCR thereby increasing the testing capacity of medical microbiological laboratories and relieving the existent PCR platforms for routine non-SARS-CoV-2 diagnostic testing.