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Addressing the challenge of sluggish kinetics and limited stability in alkaline oxygen evolution reactions, recent exploration of novel electrochemical catalysts offers improved prospects. To expedite the assessment of these catalysts, a half-cell rotating disk electrode is often favored for its simplicity. However, the actual catalyst performance strongly depends on the fabricated catalyst layers, which encounter mass transport overpotentials. We systematically investigate the role and sequence of electrode drop-casting methods onto a glassy carbon electrode regarding the efficiency of the oxygen evolution reaction. The catalyst layer without Nafion experiences nearly 50% activity loss post stability test, while those with Nafion exhibit less than 5% activity loss. Additionally, the sequence of application of the catalyst and Nafion also shows a significant effect on catalyst stability. The catalyst activity increases by roughly 20% after the stability test when the catalyst layer is coated first with an ionomer layer, followed by drop-casting the catalysts. Based on the half-cell results, the Nafion ionomer not only acts as a binder in the catalyst layer but also enhances the interfacial interaction between the catalyst and electrolyte, promoting performance and stability. This study provides new insights into the efficient and accurate evaluation of electrocatalyst performance and stability as well as the role of Nafion ionomer in the catalyst layer.

Universal access to electricity is beneficial for the socio-economic development of a country and the development of smart communities. Unfortunately, the electrification of remote off-grid areas, especially in developing countries, is rather slow due to geographic and economic barriers. In the Philippines, specifically, many electrified off-grid areas are underserved, with access to electricity being limited to only a few hours a day. This is mainly due to the high dependence on diesel power plants (DPPs) for electrifying these areas. To address these problems, hybrid renewable energy systems (HRESs) have been considered good electrification alternatives and have been extensively studied for their techno-economic and financial feasibility for Philippine off-grid islands. In this work, articles published from 2012 to 2023 focusing on off-grid Philippine rural electrification were reviewed and classified based on their topic. The taxonomical analysis of collected studies shows that there is a saturation of works focusing on the technical and economic aspects of off-grid electrification. Meanwhile, studies focusing on environmental and socio-political factors affecting HRES off-grid electrification are lagging. A bibliographic analysis of the reviewed articles also showed that there is still a lack of a holistic approach in studying off-grid electrification in the Philippines. There are only a few works that extend beyond the typical techno-economic study. Research works focusing on environmental and socio-political factors are also mainly isolated and do not cross over with technical papers. The gap between topic clusters should be addressed in future works on off-grid electrification.

Hybrid renewable energy systems have garnered considerable attention as sustainable power sources for remote off-grid islands in the Philippines. Consequently, they have been the subject of numerous techno-economic investigations. However, comprehensive explorations into the viability of 100 % renewable energy (RE) systems for these areas have been limited due to their exorbitant initial outlays. In this work, we modelled the prospective transition of off-grid island mini-grids in the Philippines from the contemporary status quo in 2020 to a fully integrated 100 % RE system by 2050. Our approach involves the gradual shift towards RE adoption instead of the abrupt deployment of RE systems. This maneuver serves a twofold purpose: firstly, it mitigates the adverse economic repercussions stemming from the substantial upfront costs inherent to RE technologies; secondly, it leverages the declining future costs of these technologies. We collected an energy generation and consumption dataset across 208 mini-grids in Philippine off-grid islands. We then simulate the RE transition based on prevailing technology costs at five-year intervals from 2020 to 2050. Afterwards, different scenarios that may affect the energy transition are simulated. Our results indicate that an energy transition steered solely by market dynamics cannot achieve a 100 % RE penetration; hence, we analysed alternative scenarios promoting RE utilization. The immediate discontinuation of all diesel generators by 2050 will lead to a substantial cost uptick at the end of the transition. Integrating biodiesel yields a more measured progression of costs, although this relies upon a nascent market, rendering it susceptible to feedstock supply risks. Recognizing the intermittent nature of RE technologies, we posit that allowing for a certain degree of unmet load fosters greater RE penetration. Nevertheless, this approach compromises the reliability of the system. Our work demonstrates that a 100 % RE transition in Philippine off-grid islands is technically and economically feasible. However, the energy trilemma or the tradeoff between affordability, reliability, and sustainability encumbers the realization of this transition.

There are few studies focused on the epidemiology of hypertensive crisis at the population level in resource-constrained settings. This study aimed to determine the prevalence and trends over time of hypertensive crisis, as well as the factors associated with this condition among adults. A secondary data analysis was carried out using the Peruvian Demographic and Family Health Survey (ENDES). Hypertensive crisis was defined based on the presence of systolic (≥ 180mmHg) or diastolic (≥ 110mmHg) blood pressure, regardless of previous diagnosis or medication use. The factors associated with our outcome were evaluated using multinomial logistic regression, and the trend of hypertensive crisis was evaluated using the Cochrane-Armitage test. Data from 260,167 participants were analyzed, with a mean age of 44.2 (SD: 16.9) years and 55.5% were women. Hypertension prevalence was 23% (95%CI: 22.7-23.4) and, among them, 5.7% (95%CI: 5.4-5.9) had hypertensive crisis, with an overall prevalence of 1.5% (95%CI: 1.4-1.6). From 2014 to 2022, a significant decrease in the prevalence of hypertensive crisis was observed, from 1.7% in 2014 to 1.4% in 2022 (p = 0.001). In the multivariable model, males, increasing age, living in urban areas, high body mass index, and self-reported type 2 diabetes were positively associated with hypertensive crisis, whereas higher educational level, socioeconomic status, and high altitude were inversely associated. There is a need to improve strategies for the diagnosis, treatment, and control of hypertension, especially hypertensive crisis.

Many people around the world rely on groundwater for drinking and sanitation, however, they are exposed to various health risks from the naturally occurring groundwater arsenic (As). Air-cathode Assisted Iron Electrocoagulation (ACAIE) using Carbon Black Pearls 2000® cathode was previously shown catalyse the removal of groundwater As by producing hydrogen peroxide (H2O2). This work explored Vulcan® XC-72, and Printex® L6 Carbon as alternative cathodes for iron electrocoagulation which are more selective towards the 2-electron oxygen reduction reaction into H2O2 compared to Carbon Black Pearls®. The cathodes were tested in an ACAIE set-up to treat synthetic groundwater spiked with 1,500 μg/L of As at different charge dosage rates (CDR) from 1.56 C/L-min to 100 C/L-min with a total charge dosage of 600 C/L for all set-ups. Although the electrocoagulation energies among the cathodes were similar, the use of Printex® cathode for ACAIE remediated the groundwater for all CDR with final As levels below 10 μg/L. This is in contrast with the less selective Carbon Black Pearls® at low CDR, and the less active Vulcan® Carbon at high CDR where the treated groundwater may still have As levels above 10 μg/L. Future research would explore modifications in the carbon materials and reactor configuration to further optimize ACAIE in removing groundwater As.

The increasing demand for batteries’ application in grid-balancing, electric vehicles, and portable electronics has prompted research efforts on improving their performance and safety features. The improvement of batteries involves the comparison of multiple battery designs and the determination of electrochemical and thermal property distributions at the continuum scale. This is achieved by using multiphysics modeling for investigatory battery research, as conventional experimental approaches would be costly and impractical. The fundamental electrochemical models for these batteries have been established, hence, new models are being developed for specific applications, such as thermal runaway and battery degradation in lithium-ion batteries, gas evolution in lead-acid batteries, and vanadium crossover in vanadium redox flow batteries. The inclusion of new concepts in multiphysics modeling, however, necessitates the consideration of phenomena beyond the continuum scale. This work presents a comprehensive review on the multiphysics models of lithium-ion, lead-acid, and vanadium redox flow batteries. The electrochemical models of these chemistries are discussed along with their physical interpretations and common applications. Modifications of these multiphysics models for adaptation and matching to end applications are outlined. Lastly, we comment on the direction of future work with regards to the interaction of multiphysics modeling with modeling techniques in other length and time scales. Molecular-scale models such as density functional theory and kinetic Monte Carlo can be used to create new multiphysics models and predict transport property correlations from first principles. Nanostructures and pore-level geometries can be optimized and integrated into continuum-scale models. The reduction of multiphysics models via machine learning, mathematical simplification, or regression enables their application in battery management systems and energy systems modeling.

Hybrid renewable energy systems (HRES) have emerged as a promising solution for delivering sustainable energy to off-grid communities. However, the vulnerability of specific regions to extreme weather events has raised concerns about the resilience of these systems. This study undertakes a techno-economic analysis to assess the impact and significance of incorporating storm hardening measures and insurance into an HRES designed for the Busuanga island cluster. Central to our study is introducing a novel cost metric, the probability-averaged levelized cost of electricity (LCOE), which adeptly captures the inherently probabilistic nature of climate-induced damages to HRES energy assets. This metric serves as the linchpin for comparing the economic viability of HRES configurations, considering both scenarios with and without storm hardening or insurance. Our findings unveil a clear trend: for a solar photovoltaic (PV) panel with an annual probability of damage at 1%, insurance emerges as a financially prudent choice, while storm hardening gains merit at a probability of 4%. The weighted average cost of capital (WACC) is pivotal in shaping investment decisions. HRES setups featuring non-hardened solar PV panels become more economically appealing than their insured or hardened counterparts under higher WACC conditions, under the condition that the solar PV panels can maintain functionality for 15 years without impairment. Our study demonstrates the importance of accounting for often overlooked factors such as storm hardening and insurance premiums for solar PV panels in climate-vulnerable areas, which are commonly disregarded in many techno-economic studies. Moreover, our findings and conclusions on the optimal balance between capital costs, insurance premiums, and storm-hardening markups can readily extend to other climate-vulnerable areas.

Density functional theory was used to investigate the effects of doping alkaline earth metal atoms (beryllium, magnesium, calcium and strontium) on graphene. Electron transfer from the dopant atom to the graphene substrate was observed and was further probed by a combined electron localization function/non-covalent interaction (ELF/NCI) approach. This approach demonstrates that predominantly ionic bonding occurs between the alkaline earth dopants and the substrate, with beryllium doping having a variant characteristic as a consequence of electronegativity equalization attributed to its lower atomic number relative to carbon. The ionic bonding induces spin-polarized electronic structures and lower workfunctions for Mg-, Ca-, and Sr-doped graphene systems as compared to the pristine graphene. However, due to its variant bonding characteristic, Be-doped graphene exhibits non-spin-polarized p-type semiconductor behavior, which is consistent with previous works, and an increase in workfunction relative to pristine graphene. Dirac half-metal-like behavior was predicted for magnesium doped graphene while calcium doped and strontium doped graphene were predicted to have bipolar magnetic semiconductor behavior. These changes in the electronic and magnetic properties of alkaline earth doped graphene may be of importance for spintronic and other electronic device applications.

In regions heavily affected by recurrent typhoons, the need for more resilient electricity infrastructure is pressing. This emphasizes the importance of integrating resilience assessment, including incorporating resilience metrics, into the planning process of power distribution systems against any disruptive events. Although standardized metrics exist for assessing distribution system reliability, the absence of formalized resilience metrics hampers informed investments in critical infrastructure such as microgrid development. In this work, a set of resilience metrics is proposed by reconceptualizing reliability metrics. The metrics were formulated to account for both the type of extreme event and its specific impact on loads with varying levels of criticality. The effectiveness of the proposed metrics is demonstrated through a Philippine microgrid case study. A Monte Carlo framework incorporating an extreme event model, component fragility model, and system response model was used to quantify the resilience improvement before and after stand-alone microgrid operation of the power distribution system. Results show that the proposed metrics can effectively evaluate resilience enhancement and highlight the value of a holistic approach of considering critical loads and types of extreme events to strengthen societal and community resilience, making a compelling case for strategic investments in infrastructure upgrades such as microgrids.

Designing and manufacturing transformers often involves variations in heights and thicknesses of windings. However, such geometric asymmetry introduces a significant impact on the magnitude of stray transformer losses. This study examines the effects of asymmetric coils on the generation of stray losses within core clamps and transformer tank walls. A model has been introduced to ascertain the dispersion magnetic field’s value at a specific distance from the coil. The analysis extends to characterising the dispersion magnetic field reaching the tank walls by using electromagnetic simulation by a finite element method. It explores strategies to diminish stray losses, including the placement of magnetic shunts as protective shields for the tank walls. It delves into the efficacy of employing a transformer shell-type configuration to mitigate the magnetic dispersion field. The findings revealed that achieving greater symmetry in transformer coils can minimise stray losses. Specifically, the incorporation of magnetic shunts has the potential to reduce additional losses by 40%, while the adoption of a shell-type configuration alone can lead to a 14% reduction. This work provides valuable insights into optimising transformer designs, contributes a user-friendly tool for estimating additional tank losses, thereby enhancing the knowledge base for transformer manufacturers.

An increasing acceptance of microgrid systems is primarily driven by emission reduction, resilience, reliability, and stability of energy systems. This work proposes a utility-scale grid-connected microgrid generation and network planning for a distribution network based on its available local resources and potential for distributed energy resource (DER) generator installation. Enabling distribution utilities to operate as a microgrid allows their systems to function as stand-alone in worst-case transmission grid scenarios. The main steps include identifying planning objectives, generation planning, and network planning. Results of a case study in Kalinga, Philippines show that the distribution utility can lower the levelized cost of electricity (LCOE) by 0.032 USD/kWh (21.38 %) by adding additional renewable energy capacities into the mix to meet its load demand. Results also show resilience and stability improvements with microgrid operation. Additional requirements for the existing distribution network to operate as a microgrid include additional network switches and line reinforcement upgrades.

As climate change is slowly materialising, the importance of alternative fuels has been magnified to aid in reducing carbon emissions. One of the most promising clean alternative fuels is green hydrogen which is produced via water electrolysis powered by renewable energy sources. The solar and wind power potential of the Philippines has been explored in published studies; however, the economic viability of green hydrogen production has not yet been evaluated. In this work, an assessment of the levelized cost of hydrogen (LCOH) produced from solar and wind power in the Philippines was performed. Representative locations within a province were selected based on the annual average resource availability for solar global horizontal irradiance (GHI) and wind speed. LCOH calculations identified the favourable locations for green H2 production by calculating the net present cost (NPC) of solar- and wind-powered electrolysis plants with deionised water as feedstock. Uncertainty analysis was performed via Monte Carlo simulations by perturbing component costs, feedstock water price, and discount rate. Additionally, LCOH calculations and Monte Carlo simulations showed the disparity of resource availability between solar and wind in the Philippines – supported by the calculated capacity factors. It was also shown that favourable conditions such as high solar GHI and high wind speed tend to have a narrower distribution and lower LCOH values – implying less economic risks in developing over these locations. Calculations identified that policy instruments such as subsidies and tax exemptions are still vital in commissioning green hydrogen plants, as LCOH values are generally higher than the cost of grey hydrogen.

The continued increase in national energy demand pushes oil and petroleum price prediction efforts for the net oil-importing Philippines to ensure adequate supply. These prices are commonly modeled by data-driven Machine Learning (ML) methods to encompass their extrinsic and volatile nature. However, recent studies have found that new features specific to COVID-19 and the Russia-Ukraine geopolitical conflict have significantly contributed to overseas oil price ML prediction. This work investigated the impact of these factors on seven pump prices in Manila, Philippines, from December 2019 until July 2022. Three ML regression models were chosen to extend the existing literature and ensure price model accuracy: Multiple Linear Regression (MLR), Support Vector Regression (SVR), and Random Forest Regression (RFR). Features were listed based on related literature and underwent data preprocessing using p-value testing and Principal Component Analysis. Models were then trained, tested, and optimized using nested splits and hyperparameter tuning. Mean Absolute Percent Error (MAPE) was used to evaluate accuracy. Generated models had MAPE values within the range 3.13 % - 12.67 %, which is within the range of MAPE values in oil and petroleum price prediction literature, 0.131 % - 19.2 %. MLR and SVR models generally exhibited the highest accuracy for each pump price. This study proves that period-specific features may be used for local pump price modeling. Future works may explore other ML models and geographic location effects and investigate newly identified period-specific features.

With the growing popularity of electric vehicles, longer lasting batteries are necessary for better mileage. Battery chemistries with larger energy densities compared to Lithium-Ion Batteries (LIB) need to be developed. Lithium-Sulfur Battery (LSB) is a good alternative due to its high theoretical and practical energy densities. However, commercialization of LSBs has yet to be realized due to shorter lifetimes caused by non-ideal battery processes such as polysulfide shuttling. Through multiphysics modeling, the effects of shuttling can be observed. Additionally, cost analysis can determine the feasibility of LSBs for mass production and its competitiveness against LIBs. In this work, energy density optimization and LSB cost estimation were done using combined multiphysics modeling and cost modeling approaches. Using COMSOL Multiphysics®, the energy densities of the batteries with and without shuttling were optimized by changing the thickness and porosity of the cathode and separator. Then, a bottom-up cost analysis of the optimized battery cell was conducted using the BatPaC model. It was observed that shuttling leads to a lower optimized energy density. To compensate for the shuttling-induced capacity loss, the model’s optimized battery dimensions had a separator porosity increase by 22.08 % and a cathode thickness and porosity decrease by 23.72 % and 16.21 %. Additionally, shuttling increases battery material costs by 13.35 % because of the larger and more expensive current collectors must compensate for the size of the smaller electrodes. Future works may explore various C-rates and use cases to identify optimal battery parameters for each.

Abstract The feeding habits of Chironomidae in hill streams in the pampean region have not been described. In this study, we analyzed the gut contents of this insect family with an aim at establishing their diet in an intermittent stream in the Ventania-Hill system. We sampled three sites with different habitat characteristics (i. e., altitude, substrate type, and current velocity). Of the total of nine taxa were recorded, the only one present at all sites was Corynoneura sp. 1. The food items found were detritus, diatoms, filamentous chlorophytes, euglenophytes, vascular plants, fungi, and animal remains. Most of the taxa could be classified as gathering collectors, with those having a higher proportion of detritus in the gut contents although the guts of Pentaneura nr. cinerea, Cricotopus sp. 1, and Onconeura analiae included high proportions of animal remains. No differences in the feeding habits were attributable to the location in the stream. This research contributes to our understanding of the trophic habits of Chironomidae in an intermittent hill stream system of South America.