• Energy Research
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Pakistan is an energy deficient country with depleting energy reserves and increasing energy demand. Due to excessive population growth, the domestic and commercial energy sectors are experiencing rising demand. To meet the requisite demand, renewables are favored rather than conventional counterparts. In this study, we model hybrid power systems using solar, wind and biomass resources for electrifying remote areas. The four locations are chosen for the study around a developing country, Pakistan, where each site is designed according to an isolated microgrid with maximum indigenous resources potential as per the requisite demands. A survey is conducted for the load demand and biomass availability. Optimization is conducted across objectives of minimum levelized cost of the generated energy, least the net present cost and lesser payback period. The optimal results were achieved in-terms of required objectives across southern sites as compared to northern counterparts. The cost of generated energy is comparable to grid electricity and ensures 24 h power supply without cut off and load shedding to the un-electrified rural area. The hybrid power system has a low carbon footprint across emissions due to the use of renewable resources. All the estimated load of rural communities is met with the available resources and mid-career impact has also been conducted across 10 years of the project life to fulfill the increasing load demand of the communities after installation. The results are validated via comparative analysis and show the effectiveness of the proposed study.

Abstract Performance characteristics due to fouling in a vapor compression cycle with integrated mechanical sub-cooling are investigated for various applications. Considering the first set of refrigerants i.e. R134a, R410A and R407C, from a first law standpoint, the COP indicates that R134a always performs better unless only the evaporator is being fouled. From a second law standpoint, the second-law efficiency indicates that R134a performs the best in all cases. Considering the second set of refrigerants i.e. R717, R404A and R290, the COP indicates that R717 always performs better unless only the evaporator is being fouled; however, the second-law efficiency indicates that R717 performs the best in all cases. Furthermore, the performance degradation due to fouling of the evaporator always has a larger effect on cooling load capacity while the performance degradation of the condenser always has an overall larger effect on the sub-cooler compressor power requirement as well as the COP of the system. In light of the data generated, a new performance degradation law, presented earlier, is shown to be applicable for this system as well that can reduce the amount of experimentation and help predict relevant quantities of the refrigeration system.

Abstract The feasible capture and separation of CO2 and N2 from CH4 is an important task for natural gas upgrading and the control of greenhouse gas emissions. Here, we studied the microporous covalent imine networks (CIN) material prepared through Schiff base condensation and exhibited superior chemical robustness under both acidic and basic conditions and high thermal stability. The material possesses a relatively uniform nanoparticle size of approximately 70–100 nm. This network featured permanent porosity with a high surface area (722 m2/g) and micropores. A single-component gas adsorption study showed enhanced CO2 and CH4 uptakes of 3.32 mmol/g and 1.14 mmol/g, respectively, at 273 K and 1 bar, coupled with high separation selectivities for CO2/CH4, CH4/N2, and CO2/N2 of 23, 11.8 and 211, respectively. The enriched Lewis basicity in the porous skeletons favours the interaction of quadrupolar CO2 and polarizable CH4, resulting in enhanced CH4 and CO2 uptake and high CH4/N2, CO2/CH4 and CO2/N2 selectivities. Breakthrough experiments showed high CO2/CH4, CH4/N2 and CO2/N2 selectivities of 7.29, 40 and 125, respectively, at 298 K and 1 bar. High heats of adsorption for CH4 and CO2 (QstCH4; 32.61 kJ mol−1 and QstCO2; 42.42 kJ mol−1) provide the ultimate validation for the high selectivity. To the best of our knowledge, such a versatile adsorbent material that displays both enhanced uptake and selectivity for a variety of binary gas mixtures, including CO2/CH4, CO2/N2 and CH4/N2, has not been extensively explored.

Small band gap molecular semiconductors are of interest for the development of transparent electronics. Here we report two near-infrared (NIR), n-type small molecule semiconductors, based upon an acceptor-donor-acceptor (A-D-A) approach. We show that the inclusion of molecular spacers between the strong-electron-accepting end group, 2,1,3-benzothiadiazole-4,5,6-tricarbonitrile, and the donor core affords semiconductors with very low band gaps down to 1 eV. Both materials were synthesized by a one-pot, 6-fold nucleophilic displacement of a fluorinated precursor by cyanide. Significant differences in solid-state ordering and charge carrier mobility are observed depending on the nature of the spacer, with a thiophene spacer resulting in solution processed organic field-effect transistors (OFETs) exhibiting excellent electron mobility up to 1.1 cm2 V-1 s-1. The use of silver nanowires as the gate electrode enables the fabrication of a semitransparent OFET device with an average visible transmission of 71% in the optical spectrum. ; The authors thank the Engineering and Physical Sciences Research Council (EPSRC) (EP/L016702/1 and EP/T028513/1), Global Research Laboratory Program of the National Research Foundation (NRF-2017K1A1A2013153), the Royal Society, and the Wolfson Foundation (Royal Society Wolfson Fellowship) for funding. M.I.N., M.H., and T.D.A. acknowledge funding from the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award Nos. OSR-2018-CARF/CCF-3079 and OSR-2020-CRG8-4095. F.E. thanks EPSRC for support via a Doctoral Prize Fellowship.

Abstract During the past decade, the worldwide demand for energy has continued to increase at a rapid rate. Natural gas has emerged as a primary source of US energy. The technically recoverable natural gas resources in the United States have increased from approximately 1,400 trillion cubic feet (Tcf) to approximately 2,100 trillion cubic feet (Tcf) in 2010. The recent declines in gas prices have created short-term uncertainties and increased the risk of developing natural gas fields, rendering a substantial portion of this resource uneconomical at current gas prices. This paper quantifies the impact of changes in finding and development costs (F&DC), lease operating expenses (LOE), and gas prices, in the estimation of the economically recoverable gas for unconventional plays. To develop our methodology, we have performed an extensive economic analysis using data from the Barnett Shale, as a representative case study. We have used the cumulative distribution function (CDF) of the values of the Estimated Ultimate Recovery (EUR) for all wells in a given gas play, to determine the values of the P10 (10th percentile), P50 (50th percentile), and P90 (90th percentile) from the CDF. We then used these probability values to calculate the technically recoverable resource (TRR) for the play, and determine the economically recoverable resource (ERR) as a function of F&DC, LOE, and gas price. Our selected investment hurdle for a development project is a 20% rate of return and a payout of 5 years or less. Using our methodology, we have developed software to solve the problem. For the Barnett Shale data, at a F&DC of $3 Million, we have found that 90% of the Barnet shale gas is economically recoverable at a gas price of $46/Mcf, 50% of the Barnet shale gas is economically recoverable at a gas price of $9.2/Mcf, and 10% of the Barnet shale gas is economically recoverable at a gas price of $5.2/Mcf. The developed methodology and software can be used to analyze other unconventional gas plays to reduce short-term uncertainties and determine the values of F&DC and gas prices that are required to recover economically a certain percentage of TRR.

This study evaluated the efficacy of enzyme induced calcite precipitation (EICP) in restricting the mobility of heavy metals in soils. EICP is an environmentally friendly method that has wide ranging applications in the sustainable development of civil infrastructure. The study examined the desorption of three heavy metals from treated and untreated soils using ethylene diamine tetra-acetic acid (EDTA) and citric acid (C6H8O7) extractants under harsh conditions. Two natural soils spiked with cadmium (Cd), nickel (Ni), and lead (Pb) were studied in this research. The soils were treated with three types of enzyme solutions (ESs) to achieve EICP. A combination of urea of one molarity (M), 0.67 M calcium chloride, and urease enzyme (3 g/L) was mixed in deionized (DI) water to prepare enzyme solution 1 (ES1); non-fat milk powder (4 g/L) was added to ES1 to prepare enzyme solution 2 (ES2); and 0.37 M urea, 0.25 M calcium chloride, 0.85 g/L urease enzyme, and 4 g/L non-fat milk powder were mixed in DI water to prepare enzyme solution 3 (ES3). Ni, Cd, and Pb were added with load ratios of 50 and 100 mg/kg to both untreated and treated soils to study the effect of EICP on desorption rates of the heavy metals from soil. Desorption studies were performed after a curing period of 40 days. The curing period started after the soil samples were spiked with heavy metals. Soils treated with ESs were spiked with heavy metals after a curing period of 21 days and then further cured for 40 days. The amount of CaCO3 precipitated in the soil by the ESs was quantified using a gravimetric acid digestion test, which related the desorption of heavy metals to the amount of precipitated CaCO3. The order of desorption was as follows: Cd > Ni > Pb. It was observed that the average maximum removal efficiency of the untreated soil samples (irrespective of the load ratio and contaminants) was approximately 48% when extracted by EDTA and 46% when extracted by citric acid. The soil samples treated with ES2 exhibited average maximum removal efficiencies of 19% and 10% when extracted by EDTA and citric acid, respectively. It was observed that ES2 precipitated a maximum amount of calcium carbonate (CaCO3) when compared to ES1 and ES3 and retained the maximum amount of heavy metals in the soil by forming a CaCO3 shield on the heavy metals, thus decreasing their mobility. An approximate improvement of 30% in the retention of heavy metal ions was observed in soils treated with ESs when compared to untreated soil samples. Therefore, the study suggests that ESs can be an effective alternative in the remediation of soils contaminated with heavy metal ions.

Donor–acceptor integral molecules with donor and acceptor units interlinked by nonconjugated flexible linking units can self-assemble into an ideal bulk heterojunction structure for application in highly efficient polymer solar cells are reviewed.

In this paper, we consider the resource-allocation problem for energy efficiency (EE)–spectral efficiency (SE) tradeoff. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or on the achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a tradeoff parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then, we apply the generalized framework of the resource allocation for the EE–SE tradeoff to optimally allocate the subcarriers' power for orthogonal frequency-division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the tradeoff parameter and study the effect of the estimation error, transmission power budget, and channel-to-noise ratio on the multiobjective optimization.