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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Energy Efficiency Program Financing

In this technical brief we characterize the programmatic energy efficiency financing market from a quantitative perspective. Financing in this report refers to provision of capital—which is paid back over time—to cover upfront costs of energy efficiency. It does not refer to rebates and other types of incentives. We gather and report data on the volume of capital for energy efficiency financing that originated from five programmatic sources: on-bill programs; other utility financing programs; property assessed clean energy (PACE) programs; state energy office (SEO) revolving loan funds (RLF); and energy savings performance contracting (ESPC) programs. We estimate the amount of investment moving through EE financing programs, the sources of capital they employ, and program availability and activity by geography and market sector (residential and non-residential). We also present information on trends in investment by program type, and on the presence or absence of certain program design features, such as credit enhancements and interest rate buydowns. The result is a much more comprehensive accounting of programmatic energy efficiency financing activity than exists elsewhere.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

An Empirical Quantile Estimation Approach for Chance-Constrained Nonlinear Optimization Problems

We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance constraint as an equivalent quantile constraint to provide stronger signals on the gradient. In this approach, the value of the quantile function is estimated empirically from samples drawn from the random parameters, and the gradient of the quantile function is estimated via a finite-difference approximation on top of the quantile-function-value estimation. We establish a convergence theory of this approach within the framework of an augmented Lagrangian method for solving general nonlinear constrained optimization problems. The foundation of the convergence analysis is a concentration property of the empirical quantile process, and the analysis is divided based on whether or not the quantile function is differentiable. In contrast to the sampling-and-smoothing approach used in the literature, the method developed in this paper does not involve any smoothing function and hence the quantile-function gradient approximation is easier to implement and there are less accuracy-control parameters to tune. Furthermore, we demonstrate the effectiveness of this approach and compare it with a smoothing method for the quantile-gradient estimation. Numerical investigation shows that the two approaches are competitive for certain problem instances.

Applied Probability↗
DOE OSTI2017

Sighten Final Technical Report DEEE0006690 Deploying an integrated and comprehensive solar financing software platform

Over the project, Sighten built a comprehensive software-as-a-service (Saas) platform to automate and streamline the residential solar financing workflow. Before the project period, significant time and money was spent by companies on front-end tools related to system design and proposal creation, but comparatively few resources were available to support the many back-end calculations and data management processes that underpin third party financing. Without a tool like Sighten, the solar financing processes involved passing information from the homeowner prospect into separate tools for system design, financing, and then later to reporting tools including Microsoft Excel, CRM software, in-house software, outside software, and offline, manual processes. Passing data between tools and attempting to connect disparate systems results in inefficiency and inaccuracy for the industry. Sighten was built to consolidate all financial and solar-related calculations in a single software platform. It significantly improves upon the accuracy of these calculations and exposes sophisticated new analysis tools resulting in a rigorous, efficient and cost-effective toolset for scaling residential solar. Widely deploying a platform like Sighten’s significantly and immediately impacts the residential solar space in several important ways: 1) standardizing and improving the quality of all quantitative calculations involved in the residential financing process, most notably project finance, system production and reporting calculations; 2) representing a true step change in terms of reporting and analysis capabilities by maintaining more accurate data and exposing sophisticated tools around simulation, tranching, and financial reporting, among others, to all stakeholders in the space; 3) allowing a broader group of developers/installers/finance companies to access the capital markets by providing an out-of-the-box toolset that handles the execution of running investor capital through a rooftop solar financing program. Standardizing and improving all calculations, improving data quality, and exposing new analysis tools previously unavailable affects investment in the residential space in several important ways: 1) lowering the cost of capital for existing capital providers by mitigating uncertainty and de-risking the solar asset class; 2) attracting new, lower cost investors to the solar asset class as reporting and data quality resemble standards of more mature asset classes; 3) increasing the prevalence of liquidity options for investors through back leverage, securitization, or secondary sale by providing the tools necessary for lenders, ratings agencies, etc. to properly understand a portfolio of residential solar assets. During the project period, Sighten successfully built and scaled a commercially ready tool for the residential solar market. The software solution built by Sighten has been deployed with key target customer segments identified in the award deliverables: solar installers, solar developers/channel managers, and solar financiers, including lenders. Each of these segments greatly benefits from the availability of the Sighten toolset.

14 SOLAR ENERGY↗
DOE OSTI2013

Derisking Renewable Energy Investment. A Framework to Support Policymakers in Selecting Public Instruments to Promote Renewable Energy Investment in Developing Countries

This report introduces an innovative framework to assist policymakers to quantitatively compare the impact of different public instruments to promote renewable energy. The report identifies the need to reduce the high financing costs for renewable energy in developing countries as an important task for policymakers acting today. The framework is structured in four stages: (i) risk environment, (ii) public instruments, (iii) levelised cost and (iv) evaluation. To illustrate how the framework can support decision-making in practice, the report presents findings from illustrative case studies in four developing countries. It then draws on these results to discuss possible directions for enhancing public interventions to scale-up renewable energy investment. UNDP is also releasing a financial tool for policymakers to accompany the framework. The financial tool is available for download on the UNDP website.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Unlocking the Value of Deep Energy Retrofits

This publication is based on an extensive study conducted on behalf of the New York State Energy Research and Development Authority (NYSERDA) and the U S Department of Energy (DOE) to explore financial and risk products to accelerate the implementation of deep energy retrofit (DER) solutions to reduce costs These financial products are intended to speed market development via three fundamental themes: reallocating risk from building owners and lenders to insurers, quantifying and monetizing previously unrecognized value associated with DERs, and providing building owners and lenders with confidence in the performance of building systems Findings are based on a comprehensive analysis and characterization of 100+ existing DER case studies, and more than 40 qualitative interviews with industry experts, including insurers, researchers, building owners, and policymakers In addition, a quantitative model of overall project economics with baseline, high, and low cases was developed This data informed the analysis that resulted in three recommended financial product solutions, which were evaluated for their potential to raise projected cash flows and finance DERs: 1) Building System Performance and Energy Savings Guarantee; 2) Trade Credit Insurance; 3) Ancillary Revenue Contracts. This report identifies many value streams associated with DERs and introduces these three potential financial products, which aim to reallocate risks and reduce barriers to the adoption of advanced envelope DERs.

ancillary renenue contracts↗
DOE OSTI2015

SU-D-204-05: Quantitative Comparison of a High Resolution Micro-Angiographic Fluoroscopic (MAF) Detector with a Standard Flat Panel Detector (FPD) Using the New Metric of Generalized Measured Relative Object Detectability (GM-ROD)

Purpose: In endovascular image-guided neuro-interventions, visualization of fine detail is paramount. For example, the ability of the interventionist to visualize the stent struts depends heavily on the x-ray imaging detector performance. Methods: A study to examine the relative performance of the high resolution MAF-CMOS (pixel size 75µm, Nyquist frequency 6.6 cycles/mm) and a standard Flat Panel Detector (pixel size 194µm, Nyquist frequency 2.5 cycles/mm) detectors in imaging a neuro stent was done using the Generalized Measured Relative Object Detectability (GM-ROD) metric. Low quantum noise images of a deployed stent were obtained by averaging 95 frames obtained by both detectors without changing other exposure or geometric parameters. The square of the Fourier transform of each image is taken and divided by the generalized normalized noise power spectrum to give an effective measured task-specific signal-to-noise ratio. This expression is then integrated from 0 to each of the detector’s Nyquist frequencies, and the GM-ROD value is determined by taking a ratio of the integrals for the MAF-CMOS to that of the FPD. The lower bound of integration can be varied to emphasize high frequencies in the detector comparisons. Results: The MAF-CMOS detector exhibits vastly superior performance over the FPD when integrating over all frequencies, yielding a GM-ROD value of 63.1. The lower bound of integration was stepped up in increments of 0.5 cycles/mm for higher frequency comparisons. As the lower bound increased, the GM-ROD value was augmented, reflecting the superior performance of the MAF-CMOS in the high frequency regime. Conclusion: GM-ROD is a versatile metric that can provide quantitative detector and task dependent comparisons that can be used as a basis for detector selection. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Energize New York -- Residential Energy Efficiency Market Transformation in New York

Energize New York (ENY) is focused on addressing known barriers to widespread energy efficiency (EE) adoption by property owners. In simple terms ENY works to; 1) increase homeowner trust by using known and trusted community leaders to communicate their own positive experiences with EE and ENY, 2) reduce friction points by integrating support staff and creative use of technology that ease a homeowner’s way forward through the EE upgrade process, 3) increase homeowner knowledge and trust of specific EE benefits through access to the ENY energy coach, 4) provide information on available financing options that show benefits (e.g. positive cash flow), and 5) provide tools and mechanisms that give homeowners greater comfort in evaluating and selecting the right contractor. These five fundamental program aspects are supported by a hyper-local communications and outreach model and a “lead by example” philosophy that requires community leaders to step forward and model energy efficiency behavior by example. In the communities where the program has successfully engaged local leadership and “trusted community sources” there has been a significant increase in the uptake of energy efficiency work. Quantitatively this growth translated into an increase of 240% in completed Home Performance projects from the two year pre-pilot period (2009-10) to the two year post-pilot period (2012-13). Additionally, the program has seen measureable increases in the output and performance of contractors who are members of the Energize Comfort Corps, a program innovation which included a subset of the NYSERDA approved and Building Performance Institute accredited home performance contractors. This innovation, launched in the later stages of the pilot, is paired with the Energize Contractor Ratings Index (CRI) and helps frame the provider market by giving homeowners a mechanism to provide and receive feedback on their contractor experience. The data incorporated into the CRI along with the ECC selection process, has measurably reduced a key decision barrier (“which contractor should I use”) for homeowners engaged in the EE decision making process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Addressing Soiling: From Interface Chemistry to Practicality

Natural soiling has reduced the energy output of photovoltaic (PV) systems since the technology was first used. Projecting even a small average annual soiling loss translates to billions of dollars in annual lost revenue worldwide. Production losses due to soiling can be very high in some locations, substantially increasing the levelized cost of electricity (LCOE) due to lost power production, increased operating and maintenance costs, and/or increased finance cost due to the uncertainty. Furthermore, although soiling has been discussed in the literature for more than 70 years, solutions to many problems are still needed. The National Renewable Energy Laboratory (NREL) is working with the PV industry to develop the tools/knowledge so that the effects of soiling can be predicted for different environmental conditions and cost-effective mitigation can be implemented. For this project, NREL performed a number of research and development tasks/subtasks in the following general areas to 1) predict PV module soiling losses based on environmental factors at a PV installation and from its energy production data, 2) quantitatively measure the adhesion forces to understand the physics enabling soiling, and 3) develop related standards on PV module coatings and artificial soiling. At the inception of the project, the PV industry considered these efforts to be the most important and immediate soiling issues that we could address to have the highest impact on LCOE. These focused efforts have led to outstanding accomplishments that have been communicated and very well received by the community.

14 SOLAR ENERGY↗
DOE OSTI2025

CO2 Storage Economic Analysis: CarbonSAFE Use Case

Poster on “CO2 Storage Economic Analysis: CarbonSAFE Use Case” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The cost of designing, permitting, constructing, operating, and closing a CO2 storage project is of vital importance to project developers. The National Energy Technology Laboratory has developed the NRAP/SMART Technoeconomic and Liability Evaluation for Storage (TALES) Model to provide quantitative cost-based insights to support developers planning CO2 injection and storage projects. This study presents a collaborative economic analysis applying TALES with data from the San Juan Basin CarbonSAFE Phase III project led by the New Mexico Institute of Mining and Technology to estimate potential costs incurred during the implementation of a real-world commercial-scale carbon storage project. Scenario analysis was implemented in which different operational and cost attributes were varied and the associated cost implications observed. Key results data and project cost summary metrics, first-year breakeven price of CO2 ($/tonne) and net present value (NPV), are presented for base and alternative cases. Output provides a unique perspective for project stakeholders towards evaluating the influence of different operational strategies and financing approaches on overall project cost and financial viability.

carbon storage↗
DOE OSTI2021

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗
DOE OSTI2015

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specific anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-41: Regularized PCA Can Model Treatment-Related Changes in Head and Neck Patients Using Daily CBCTs

Purpose: To use daily cone beam CTs (CBCTs) to develop regularized principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients, to guide replanning decisions in adaptive radiation therapy (ART). Methods: Known deformations were applied to planning CT (pCT) images of 10 H&N patients to model several different systematic anatomical changes. A Pinnacle plugin was used to interpolate systematic changes over 35 fractions, generating a set of 35 synthetic CTs for each patient. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CTs and random fraction-to-fraction changes were superimposed on the DVFs. Standard non-regularized and regularized patient-specific PCA models were built using the DVFs. The ability of PCA to extract the known deformations was quantified. PCA models were also generated from clinical CBCTs, for which the deformations and DVFs were not known. It was hypothesized that resulting eigenvectors/eigenfunctions with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: As demonstrated with quantitative results in the supporting document regularized PCA is more successful than standard PCA at capturing systematic changes early in the treatment. Regularized PCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes. To be successful at guiding ART, regularized PCA should be coupled with models of when anatomical changes occur: early, late or throughout the treatment course. Conclusion: The leading eigenvector/eigenfunction from the both PCA approaches can tentatively be identified as a major systematic change during radiotherapy course when systematic changes are large enough with respect to random fraction-to-fraction changes. In all cases the regularized PCA approach appears to be more reliable at capturing systematic changes, enabling dosimetric consequences to be projected once trends are established early in the treatment course. This work is supported in part by a grant from Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

A Research Agenda for Radiation Oncology: Results of the Radiation Oncology Institute's Comprehensive Research Needs Assessment

Purpose: To promote the rational use of scarce research funding, scholars have developed methods for the systematic identification and prioritization of health research needs. The Radiation Oncology Institute commissioned an independent, comprehensive assessment of research needs for the advancement of radiation oncology care. Methods and Materials: The research needs assessment used a mixed-method, qualitative and quantitative social scientific approach, including structured interviews with diverse stakeholders, focus groups, surveys of American Society for Radiation Oncology (ASTRO) members, and a prioritization exercise using a modified Delphi technique. Results: Six co-equal priorities were identified: (1) Identify and develop communication strategies to help patients and others better understand radiation therapy; (2) Establish a set of quality indicators for major radiation oncology procedures and evaluate their use in radiation oncology delivery; (3) Identify best practices for the management of radiation toxicity and issues in cancer survivorship; (4) Conduct comparative effectiveness studies related to radiation therapy that consider clinical benefit, toxicity (including quality of life), and other outcomes; (5) Assess the value of radiation therapy; and (6) Develop a radiation oncology registry. Conclusions: To our knowledge, this prioritization exercise is the only comprehensive and methodologically rigorous assessment of research needs in the field of radiation oncology. Broad dissemination of these findings is critical to maximally leverage the impact of this work, particularly because grant funding decisions are often made by committees on which highly specialized disciplines such as radiation oncology are not well represented.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-D-303-03: Impact of Uncertainty in T1 Measurements On Quantification of Dynamic Contrast Enhanced MRI

Purpose: Quantification of dynamic contrast enhanced (DCE) MRI requires native longitudinal relaxation time (T1) measurement. This study aimed to assess uncertainty in T1 measurements using two different methods. Methods and Materials: Brain MRI scans were performed on a 3T scanner in 9 patients who had low grade/benign tumors and partial brain radiotherapy without chemotherapy at pre-RT, week-3 during RT (wk-3), end-RT, and 1, 6 and 18 months after RT. T1-weighted images were acquired using gradient echo sequences with 1) 2 different flip angles (50 and 150), and 2) 5 variable TRs (100–2000ms). After creating quantitative T1 maps, average T1 was calculated in regions of interest (ROI), which were distant from tumors and received a total of accumulated radiation doses < 5 Gy at wk-3. ROIs included left and right normal Putamen and Thalamus (gray matter: GM), and frontal and parietal white matter (WM). Since there were no significant or even a trend of T1 changes from pre-RT to wk-3 in these ROIs, a relative repeatability coefficient (RC) of T1 as a measure of uncertainty was estimated in each ROI using the data pre-RT and at wk-3. The individual T1 changes at later time points were evaluated compared to the estimated RCs. Results: The 2-flip angle method produced small RCs in GM (9.7–11.7%) but large RCs in WM (12.2–13.6%) compared to the saturation-recovery (SR) method (11.0–17.7% for GM and 7.5–11.2% for WM). More than 81% of individual T1 changes were within T1 uncertainty ranges defined by RCs. Conclusion: Our study suggests that the impact of T1 uncertainty on physiological parameters derived from DCE MRI is not negligible. A short scan with 2 flip angles is able to achieve repeatability of T1 estimates similar to a long scan with 5 different TRs, and is desirable to be integrated in the DCE protocol. Present study was supported by National Institute of Health (NIH) under grant numbers; UO1 CA183848 and RO1 NS064973.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-42: Association of Radiomic and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme

Purpose: High-throughput extraction of imaging and metabolomic quantitative features from MRI and MR Spectroscopy Imaging (MRSI) of Glioblastoma Multiforme (GBM) results in tens of variables per patient. In radiotherapy (RT) of GBM, the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl Aspartate (NAA) and Choline (Cho). Corresponding Clinical Target Volumes (CTVs) for RT planning are based on Contrast Enhancing T1-weighted MRI (CE-T1w) and T2-weighted/Fluid Attenuated Inversion Recovery (FLAIR) MRI. The objective is to build a framework for investigation of associations between imaging, CTV, and MTV features better understanding of the underlying information in the CTVs and dependencies between these volumes. Methods: Necrotic portions, enhancing lesion and edema were manually contoured on T1w/T2w images for 17 GBM patients. CTVs and MTVs for NAA (MTV{sub NAA}) and Cho (MTV{sub Cho}) were constructed. Tumors were scored categorically for ten semantic imaging traits by neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and RT/MTV features were visualized as heat maps. Associations between MTV{sub NAA}, MTV{sub Cho} and imaging features were studied using Spearman correlation. Results: 39 imaging features were computed per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. 21 features were extracted from MTVs/CTVs. There were a high number (43) of significant correlations of imaging with CTVs/MTV{sub NAA} while very few (10) significant correlations were with CTVs/MTV{sub Cho}. MTV{sub NAA} was found to be closely associated with MRI volumes, MTV{sub Cho} remains elusive for characterization with imaging. Conclusion: A framework for investigation of co-dependency between MRI and RT/metabolic features is established. A series of semantic imaging traits were replaced with automatically extracted continuous variables. The approach will allow for exploration of relationships between sizes and intersection of imaging features of tumors, RT volumes, metabolite concentrations and comparing those to therapy outcome, quality of life evaluation and overall survival rate. This publication was supported by Grant 10BN03 from Bankhead Coley Cancer Research Program, R01EB000822, R01EB016064, and R01CA172210 from the National Institutes of Health, and Indo-US Science & Technology Forum award #20-2009. Bhaswati Roy received financial assistance from University Grant Commission, New Delhi, India.

60 APPLIED LIFE SCIENCES↗