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Energy efficient functional retrofitting of buildings helps in reducing the energy and resource consumption of a building. This translates into cost benefits which are achieved during the operational phase of the building in post-retrofit scenario. However, the net benefit received has to be analysed by considering the entire life cycle of the building. Hence, this paper investigates the actual cost benefits achieved and its impact on the financial viability of an energy efficient functional retrofitting project, by analysing actual cases of functional retrofitting of buildings (for achieving greater operational efficiency) in Indian context. Cost analysis in this study includes the parameters of net present value, internal rate of return, payback period, and equivalent annual cost for comparing the considered cases for post-retrofit scenarios of building. The results are then correlated to the initial cost of functional retrofitting for each case in order to identify the inter-relationship and trend with respect to the level of intervention opted for the cases.

A wireless sensor network is a network of nodes spread across the application field with sensors attached to them, helping them sense the environmental parameters and transmit the data to the base station for further computation. Because of low battery power of sensor nodes, energy efficient routing in the sensor nodes is very important for a good network lifetime and throughput. Clustering of nodes by formation of groups is an effective routing technique which involves transmission of data from the nodes to the head of the cluster and then the transmission of the accumulated data from that cluster head to the base station. In this paper, a new clustering based routing protocol is proposed which shows significant improvement in the network lifetime, stability of network, throughput of the network and the average energy of the network as compared to the conventional clustering based routing algorithms. The nodes in the network field have been deployed according to the gauss function instead of a random distribution. Also, the base station has been made mobile and it’s movement is according to the sigmoid function. Initial energy and current energy of nodes along with average energy of network have been taken into consideration in several computations to modify the conventional clustering routing algorithm. This proposed protocol i.e. Gauss-sigmoid based clustering routing (GSCR) protocol is compared with SEP, LEACH and DEEC protocols for performance evaluation and for exhibiting its improvement in the performance parameters. Significant improvement is exhibited in terms of network lifetime, throughput, stability period and the average energy of the network.

Nanoplasmonic sensors based on surface-enhanced spectroscopies carry profound promise toward ultrasensitive detection of biomolecular analytes within miniaturized measurement footprints. High sensitivity in these sensors is achieved by intense electromagnetic (EM) enhancements at hot spots and colocalization of analytes with such hot spots. However, EM hot spots exhibiting high EM enhancements often present confined areas that render them inaccessible to large analytes such as biomolecules. Addressing this requires rational engineering of a nanoplasmonic interface that factors in the analyte surface concentrations and how they are distributed with respect to the EM hot spots. Here we demonstrate combination of metal-enhanced fluorescence (MEF) with a quartz crystal microbalance (QCM) through fabrication of highly resolved plasmonic nanoarrays directly on the QCM sensor. QCM and MEF are simultaneously employed to monitor in situ, real-time binding of fluorescently labeled protein to receptor-functionalized plasmonic arrays. The correlation between the QCM and MEF responses is used to quantify surface density of protein that contributes to the MEF signal intensities and obtain analyte distribution with respect to the EM hot spots by geometric modeling. Results further reveal the MEF assays to be sensitive down to ∼2 zmol of protein within measurement footprints that are 8 orders of magnitude smaller than that of the QCM.

High sensitivity in plasmon-enhanced spectroscopies results not only from high electromagnetic (EM) field enhancements at the vicinity of nanostructured metal surfaces but also the ability to leverage on these enhancements via analyte colocalization with the EM hot spots. However, promising configurations for EM hot spots such as metal nanogaps are spatially restrictive for adsorption of larger analytes such as proteins. This results in an adverse spatial trade-off in the design of EM hot spots, viz., increasingly confined geometries sought to drive high EM enhancements and space necessary to accommodate binding of large biomolecular analytes. In this direction, we demonstrate gold nanoparticle cluster arrays (NCAs) exhibiting interparticle (<1 nm wide) and intercluster (<10 nm wide) EM hot spots, with cluster size and densities engineered to enhance the leverage of biomolecular analytes over EM hot spots. Surface-enhanced Raman and fluorescence assays of streptavidin–dye conjugates on biotinylated NCAs show higher sensitivity to be achieved using NCA geometry exhibiting greater density of intercluster hot spots. Quartz crystal microbalance measurements reveal the higher sensitivity to be achieved despite lower nanoparticle as well as analyte surface densities as compared to less sensitive NCA geometries. The results are aligned with the expectation that the large dimensions of protein analytes allow better leverage of intercluster rather than interparticle hot spots and consequently be detected with better sensitivity on NCAs presenting higher intercluster hot-spot densities. The investigation supports the need to factor in the size of the analyte into the design of the EM hot spots to achieve high sensitivity in plasmon-enhanced spectroscopic sensors.

Electromagnetic hot-spots at ultranarrow plasmonic nanogaps carry immense potential to drive detection limits down to few molecules in sensors based on surface-enhanced Raman or fluorescence spectroscopies. However, leveraging the EM hot-spots requires access to the gaps, which in turn depends on the size of the analyte in relation to gap distances. Herein, we leverage a well-calibrated process based on self-assembly of block copolymer colloids on a full-wafer level to produce high-density plasmonic nanopillar arrays exhibiting a large number (>1010cm–2) of uniform interpillar EM hot-spots. The approach allows convenient handles to systematically vary the interpillar gap distances down to a sub-10 nm regime. The results show compelling trends of the impact of analyte dimensions in relation to the gap distances toward their leverage over interpillar hot-spots and the resulting sensitivity in SERS-based molecular assays. Comparing the detection of labeled proteins in surface-enhanced Raman and metal-enhanced fluorescence configurations further reveal the relative advantage of fluorescence over Raman detection while encountering the spatial limitations imposed by the gaps. Quantitative assays with limits of detection down to picomolar concentrations are realized for both small organic molecules and proteins. The well-defined geometries delivered by a nanofabrication approach are critical to arriving at realistic geometric models to establish meaningful correlation between the structure, optical properties, and sensitivity of nanopillar arrays in plasmonic assays. The findings emphasize the need for the rational design of EM hot-spots that takes into account the analyte dimensions to drive ultrahigh sensitivity in plasmon-enhanced spectroscopies.

Intense electromagnetic (EM) hot-spots arising at the junctions or gaps in plasmonic nanoparticle assemblies can drive ultrahigh sensitivity in molecular detection by surface-enhanced spectroscopies. Harnessing this potential however requires access to the confined physical space at the EM hot-spots, which is a challenge for larger analytes such as biomolecules. Here, we demonstrate self-assembly derived gold nanoparticle cluster arrays (NCAs) on gold substrates exhibiting controlled interparticle (<1 nm wide) and intercluster (<10 nm wide) hot-spots as highly promising in this direction. Sensitivity of the NCAs toward detection of small (<1 nm) or large (protein–receptor interactions) analytes in surface-enhanced Raman and metal-enhanced fluorescence assays is found to be strongly impacted by the size of the cluster and the presence of reflective substrates. Experiments supported by numerical simulations attribute the higher sensitivity to higher EM field enhancements at the hot-spots, as well as greater analyte leverage over EM hot-spots. The best-performing arrays could push the sensitivity down to picomolar detection limits for sub-nanometric organic analytes as well as large protein analytes. The investigation paves the way for rational design of plasmonic biosensors and highlights the unique capabilities of a molecular self-assembly approach toward catering to this objective.