Tailoring the antimicrobial response of cationic nanocellulose-based foams through cryo-templating

FAPESP – FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOLNNANO - BRAZILIAN NANOTECHNOLOGY NACIONAL LABORATORYTo shed light on novel sustainable materials with antimicrobial functionality, in this contribution, we describe the use of cationic nanocellulose to produce foams featuring antibacterial activity against the powerful human pathogen Escherichia coli. Dialdehyde cellulose was cationized with Girard’s reagent T (GRT), mechanically disintegrated into nanofibrillated cellulose (NFC), and shaped into foams through different protocols. All steps were carried out in aqueous media and in the absence of hazardous chemicals. While evaporative drying led to compact films (density of 1.3 g cm–3), freeze-casting (i.e., freezing and freeze-drying) produced monolithic cryogels with low densities (<50 mg cm–3) and porosities of ca. 98%. Although highly porous, the cryogels obtained through rapid freezing remarkably presented smaller pores than those that were previously frozen in a slow fashion. The quaternary ammonium groups of GRT-cationized NFC removed E. coli to different extents depending upon sample morphology. We demonstrated in an innovative manner that porosity, which is directly associated with surface area, and pore size play an essential role on the antimicrobial performance. This outcome arises from the inaccessibility of bacterial cells to cationic surfaces inside monoliths composed of small pores. We herein present an uncomplicated, environmentally friendly protocol for fine-tuning the porosity and pore size of all-cellulose materials through cryo-templating. Controlling these morphometric parameters allowed us to achieve a ca. 85% higher anti-E. coli activity when comparing samples made up of the very same material (i.e., the same NFC concentration and degree of substitution) but presented as dense films. These findings bear clear implications for the pursuit of sustainable materials presenting multifunctionality2519751986FAPESP – FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOLNNANO - BRAZILIAN NANOTECHNOLOGY NACIONAL LABORATORYFAPESP – FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOLNNANO - BRAZILIAN NANOTECHNOLOGY NACIONAL LABORATORY2017/07013-1; 2017/01167-7; 2015/25406-

Non-Hardware-Based Non-Technical Losses Detection Methods: A Review

Non-Technical Losses (NTL) represent a serious concern for electric companies. These losses are responsible for revenue losses, as well as reduced system reliability. Part of the revenue loss is charged to legal consumers, thus, causing social imbalance. NTL methods have been developed in order to reduce the impact in physical distribution systems and legal consumers. These methods can be classified as hardware-based and non-hardware-based. Hardware-based methods need an entirely new system infrastructure to be implemented, resulting in high investment and increased cost for energy companies, thus hampering implementation in poorer nations. With this in mind, this paper performs a review of non-hardware-based NTL detection methods. These methods use distribution systems and consumers’ data to detect abnormal energy consumption. They can be classified as network-based, which use network technical parameters to search for energy losses, data-based methods, which use data science and machine learning, and hybrid methods, which combine both. This paper focuses on reviewing non-hardware-based NTL detection methods, presenting a NTL detection methods overview and a literature search and analysis