Environmental Microbial Biotechnology

Sukla, Lala Behari; Pradhan, Nilotpala; Panda, Sandeep; Mishra, B.K.

doi:10.1007/978-3-319-19018-1

Cited by 8 publications

(3 citation statements)

References 396 publications

(523 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Its working principle is linked to three main components: a biological recognition system (bioreceptor), a physical-chemical transducer, and an electronic system that processes and displays the signal [46,155]. The first recognition interface guarantees different selectivity and accuracy according to the detection method/biological element (e.g., enzymes, antibodies, DNA, microorganisms, receptors, cells) [44,49,50,55]. The bioreceptor interacts with the target analyte, resulting in a biochemical reaction.…”

Section: Application Of the Functionalized Bnc In Biosensors And Futu...mentioning

confidence: 99%

“…Biosensors combine a biological recognition layer with a physicochemical transduction layer and an electronic signal processing device that can be employed as an analytical tool to detect an analyte in a wide range of environments [54]. As hybrid devices, they play an essential role by achieving rapid and selective quantitative or semiquantitative analysis when compared to conventional detection methods, such as chromatography and spectroscopy, which are usually costly and time consuming [47,55]. Furthermore, biosensors are low-cost devices that do not require extensive instrumentation and have relatively fast response times due to their chemical redox response [35,51,52,56].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Review of Bacterial Nanocellulose-Based Electrochemical Biosensors: Functionalization, Challenges, and Future Perspectives

et al. 2023

View full text Add to dashboard Cite

Electrochemical biosensing devices are known for their simple operational procedures, low fabrication cost, and suitable real-time detection. Despite these advantages, they have shown some limitations in the immobilization of biochemicals. The development of alternative materials to overcome these drawbacks has attracted significant attention. Nanocellulose-based materials have revealed valuable features due to their capacity for the immobilization of biomolecules, structural flexibility, and biocompatibility. Bacterial nanocellulose (BNC) has gained a promising role as an alternative to antifouling surfaces. To widen its applicability as a biosensing device, BNC may form part of the supports for the immobilization of specific materials. The possibilities of modification methods and in situ and ex situ functionalization enable new BNC properties. With the new insights into nanoscale studies, we expect that many biosensors currently based on plastic, glass, or paper platforms will rely on renewable platforms, especially BNC ones. Moreover, substrates based on BNC seem to have paved the way for the development of sensing platforms with minimally invasive approaches, such as wearable devices, due to their mechanical flexibility and biocompatibility.

show abstract

Section: Application Of the Functionalized Bnc In Biosensors And Futu...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Review of Bacterial Nanocellulose-Based Electrochemical Biosensors: Functionalization, Challenges, and Future Perspectives

et al. 2023

View full text Add to dashboard Cite

show abstract

“…1,8 Bioleaching is also referred to as the dissolution of metals from ores and concentrates by the application of microorganisms like bacteria and fungi. [9][10][11] Mostly this process is carried out by mesophilic (30-45 • C), thermophilic (45-60 • C) bacteria which are also acidophilic in nature. Predominant bacteria are iron-oxidising and sulfur-oxidizing bacteria Acidithiobacillus ferrooxidans, sulfur-oxidizing Acidithiobacillus thiooxidans, Acidithiobacillus caldus, iron-oxidizing Leptospirillum ferrooxidans, and Leptospirillum ferriphilum.…”

Section: Abstract Electronic Waste Printed Circuit Boards Bimentioning

confidence: 99%

Neural network prediction of bioleaching of metals from waste computer printed circuit boards using Levenberg‐Marquardt algorithm

Annamalai

Gurumurthy

2020

Computational Intelligence

View full text Add to dashboard Cite

The applicability of artificial neural network (ANN) to predict the bioleaching of metals using from computer printed circuit boards (CPCB) and the influence of process parameters were studied. The influence of process parameters initial pH (1.6-2.4), pulp density (2%-13%), and the initial volume of Inoculum (5%-25%) were investigated on the rate of bioleaching of metals from CPCB. Network inputs were fed as initial pH, pulp density, and inoculum volume and with the extraction of Cu, Ag, and Au as output. The ANN was developed using the Levenberg-Marquardt algorithm and trained for modeling and prediction. The most fitting architectures for Cu, Ag, and Au were [

show abstract