Potential Energy Research Articles

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed > 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

Preference of Afternoon Precipitation Over Dry Soil in the North China Plain During Warm Seasons

AbstractThe influence of soil moisture (SM) on atmospheric precipitation has been extensively studied, but few of these studies have considered the role of land‐atmosphere (L‐A) coupling in afternoon precipitation events (APEs) at a sub‐daily timescale. Here, using in‐situ observations and reanalysis data sets, we investigated the effect of the soil moisture anomaly (SMA) on warm seasons' afternoon precipitation in the North China Plain (NCP), identified as a strong L‐A coupling region. APEs were separated from all precipitation events in the NCP during the warm seasons of 2010–2019. It follows from a comparative analysis that an APE is more likely to be initiated on drier soil, which has little dependence on the thresholds used for identifying an APE. However, no affirmative relationship is found between precipitation amount in the first hour of an APE (APE1hour) and the SMA. Further analyses indicate that larger amounts of APE1hour result from higher convective available potential energy (CAPE), higher moist static energy (MSE), or weaker vertical shear of horizontal wind. When considering the joint effects of SMA and atmospheric variables, APEs tend to occur on drier (wetter) soil with lower (higher) lower‐tropospheric stability, CAPE, or MSE. This study highlights the significant roles of L‐A interactions on local atmospheric precipitation, especially the joint roles of SM and atmospheric variables on precipitation.

Effectiveness of injection protocols for hydraulic stimulation in enhanced geothermal systems

To harness the immense potential of geothermal energy for non-intermittent baseload power, low-permeability crystalline hot rocks need to be hydraulically stimulated to create Enhanced Geothermal Systems (EGS) that enable economically profitable fluid flow rates. However, hydraulic stimulation is usually associated with seismic activity that has led to project cancellation in a few occasions. To improve our understanding of the coupled hydro-mechanical (HM) processes behind stimulation during both injection and post-injection stages (after shut-in), we numerically analyze three different stimulation protocols: constant-rate, step-rate, and cyclic injection with and without bleed-off after shut-in (and between cycles for the cyclic protocol). Simulation results show that the injection protocol has a higher influence on the HM response of the fracture than the total volume of injected water, which challenge scaling laws that relate the injection volume with the expected maximum magnitude of the induced earthquakes. The trade-off between maximizing permeability enhancement, while minimizing induced seismicity is not straightforward. In particular, bleeding-off the well after injection restricts induced seismicity, but at the expenses of limiting permeability enhancement. When considering stimulation of a single fault, all protocols yield comparable slip rates and, thus, magnitude of the induced earthquake, with the constant-rate injection being the fastest to induce the largest earthquake. The small differences in the HM response to hydraulic stimulation do not permit identifying a protocol that performs better than the others.

A novel additive for enhancing biomass energy production from agro-industrial wastes: synthesis of hydrophobic nanoporous silica aerogel and its effect on methane production

AbstractAnaerobic digestion (AD) is one of the most preferred processes for the treatment of organic waste. However, additional processes such as co-digestion, pretreatment, and additive addition continue to be explored to remove the limits on the applicability of AD. This study investigated the effects of hydrophobic nanoporous silica aerogel (NpSA) synthesized from waste rice husks on the anaerobic co-digestion (AnCD) of the mixture consisting of sewage sludge and fruit processing industry wastes. All bioreactors containing NpSA-free, 0.1 g, 0.2 g, 0.5 g, and 1 g NpSA (0.03–0.3 gNpSA/gVSadded) were operated in a mesophilic-batch process. Biogas and methane yields increased from 346 mL/gVS (NpSA-free) to 387 mL/gVS and from 231 mL/gVS (NpSA-free) to 288 mL/gVS, respectively, with 0.1 g NpSA addition. NpSA additive increased biogas production in all bioreactors compared to the blank. However, biogas production rate and methane content increased faster at lower doses of NpSA. Maximum soluble chemical oxygen demand (sCOD), protein, carbohydrate, and volatile solid (VS) reductions were between 45–71%, 35–54%, 44–65%, and 34–91% for NpSA added mixtures, respectively. The hydrophobic NpSA additive was effective in improving the AnCD performance and biogas/methane production. Experimental results fit the kinetic models frequently preferred in such AD processes. In addition, the possible energy and financial potential of the produced methane were also discussed, and it was determined that the direct sale of methane gas produced by the addition of NpSA in the global market could provide 1.4 $/Lmixture more financial gain than the mixture NpSA-free. Graphical Abstract

Outlook for Offshore Wind Energy Development in Mexico from WRF Simulations and CMIP6 Projections

This study presents a comprehensive assessment of the offshore wind energy potential in Mexico across 40 years (1979–2018) of numerical simulations using the Weather Research and Forecasting (WRF) model and data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The WRF identifies three regions with moderate to good wind potential: off the north coast of Tamaulipas (Zone I), the northwest coast of Yucatan (Zone II), and the Gulf of Tehuantepec (Zone III). The analysis involves comparing 47 CMIP6 climate models with the WRF results and selecting the best performing models to obtain future projections for the short term (2040–2069) and the long term (2070–2099). Two ensemble-based strategies were implemented. The first one, which uses an intersection approach from which four CMIP6 models were considered, reveals positive percentage differences in Zone II for both future projections, especially for the long-term one. In Zones I and III, positive values are also observed near the coast, mainly for the long-term projection, but they are considerably lower compared to those in Zone II. The second ensemble strategy uses weight assignment through the Mean Absolute Percentage Error, so that a greater weight is given to the model that performed better in each particular zone, potentially providing more accurate results. The findings suggest the likelihood of increased offshore wind energy in these three zones of Mexico, for both short- and long-term future projections, with positive percentage differences of up to 10% in certain areas.

ERA5‐Based Significant Tornado Environments in Canada Between 1980 and 2020

AbstractThis study uses ERA5 close‐proximity soundings and associated convective parameters to characterize significant tornadic storm (F/EF2+) environments between 1980 and 2020 in parts of Canada. It is shown that ERA5 convective parameters are suitable to represent observed parameters, based on radiosonde comparisons. Results indicate that the eastern Canadian Prairies have nearly double the lifted condensation level with higher level of free convection compared to eastern Canada (southern Ontario/Quebec). Eastern Canada has more a humid boundary layer and free troposphere that can lead to warmer cold pools, favoring tornadogenesis. Central Canada (Manitoba) has the largest mixed‐layer (ML) convective available potential energy (CAPE) mainly due to a combination of regional differences in low level moisture and steeper mid‐level lapse rates in western Canada. Central continental U.S. and Canadian regions appear to have the highest (most negative) convective inhibition, leading to more explosive initiation. Mean bulk wind shear and storm relative helicity (SRH) increases from west to east, with eastern regions being significantly larger. The supercell composite and significant tornado parameters are generally less than U.S. magnitudes, particularly in western Canada, and would require recalibration for more practical use in Canada. Overall, western Canada significant tornadic storms are associated with more low‐level looping hodographs and dominated by thermodynamic influences compared to larger wind influences in eastern regions. This is likely due to more spring, late summer, and autumn events that typically have well‐developed synoptic systems (stronger wind shear) with overall less buoyant energy in eastern regions.

One-Dimensional Non-coplanar Nitrogen Chains in Manganese Tetranitride under High Pressure.

Transition metal nitrides have great potential applications as incompressible and high energy density materials. Various polymeric nitrogen structures significantly affect their properties, contributing to their complex bonding modes and coordination conditions. Herein, we first report a new manganese polynitride MnN4 with bifacial trans-cis [N4]n chains by treating with high-pressure and high-temperature conditions in a diamond anvil cell. Our experiments reveal that MnN4 has a P-1 symmetry and could stabilize in the pressure range of 56-127 GPa. Detailed pressure-volume data and calculations of this phase indicate that MnN4 is a potential hard (255 GPa) and high energy density (2.97 kJ/g) material. The asymmetric interactions impel N1 and N4 atoms to hybridize to sp2-3, which causes distortions of [N4]n chains. This work discovers a new polynitride material, fills the gap for the study of manganese polynitride under high pressure, and offers some new insights into the formation of polymeric nitrogen structures.

Soft Actor-Critic and Risk Assessment-Based Reinforcement Learning Method for Ship Path Planning

Ship path planning is one of the most important themes in waterway transportation, which is deemed as the cleanest mode of transportation due to its environmentally friendly and energy-efficient nature. A path-planning method that combines the soft actor-critic (SAC) and navigation risk assessment is proposed to address ship path planning in complex water environments. Specifically, a continuous environment model is established based on the Markov decision process (MDP), which considers the characteristics of the ship path-planning problem. To enhance the algorithm’s performance, an information detection strategy for restricted navigation areas is employed to improve state space, converting absolute bearing into relative bearing. Additionally, a risk penalty based on the navigation risk assessment model is introduced to ensure path safety while imposing potential energy rewards regarding navigation distance and turning angle. Finally, experimental results obtained from a navigation simulation environment verify the robustness of the proposed method. The results also demonstrate that the proposed algorithm achieves a smaller path length and sum of turning angles with safety and fuel economy improvement compared with traditional methods such as RRT (rapidly exploring random tree) and DQN (deep Q-network).

Density Functional Theory Study on the Mechanism of Nickel-Catalyzed 3,3-Dialkynylation of 2-Aryl Acrylamides Via Double Vinylic C-H Bond Activation.

The mechanisms of Ni-catalyzed 3,3-dialkynylation of 2-aryl acrylamide have been investigated by using density functional theory calculations. The result shows that this reaction includes double alkynylation, which involves sequential key steps of vinylic C-H bond activation, successive oxidative addition, and reductive elimination, with the second C-H bond activation being the rate-determining step. C-H and N-H bond activation occurs via the concerted metalation-deprotonation mechanism. The calculations show that no transition state exists in the first reductive elimination process, and a negative free energy barrier in the second reductive elimination process though a transition state is identified, indicating that the nickel-catalyzed vinylic C(sp2)-C(sp) bond formation does not require activation energy. Z-E isomerization is the prerequisite for the second alkynylation. In addition, our spin-flip TDDFT (SF-TDDFT) computational result discloses that the actual process of Z-E isomerization occurs on the potential energy surface of the first excited singlet state S1.

Dual-Channel Imine-Amine Photoisomerization in a Benzoimidazole and Benzothiazole Coupled System: Photophysics and Applications.

A molecule, namely 2-(1H-benzo[d]imidazol-2-yl)-6-(benzo[d]thiazol-2-yl)-4-bromophenol (BIBTB), having a two-way proton transfer unit of thiazole and imidazole moieties was synthesized and characterized by NMR, electrospray ionization mass spectrometry (ESI-MS), and single-crystal diffraction studies. Steady state and time-resolved spectral studies of BIBTB support excited state intramolecular proton transfer (ESIPT), causing imine-amine tautomerization through a two-way 6-membered H-bonded ring, where the N atoms of benzothiazole and the benzoimidazole unit are involved as proton acceptor sites. Interestingly, in a nonpolar and moderately polar solvent, photoisomerization in BIBTB is found to be favored toward the thiazole ring, whereas in a highly polar solvent, it is favored toward the imidazole ring. A spectral comparison of BIBTB with judicially designed molecules 2-(benzo[d]thiazol-2-yl)-4-bromophenol (HBT) and 2-(1H-benzo[d]imidazol-2-yl)-4-bromophenol (BIB) supports these inferences. Theoretical calculation using the Density Functional Theory (DFT) at CAM-B3LYP/6-311+G(d,p) level supports the existence of two low-energy 6-membered hydrogen-bonded planar conformers in the ground state in the gas phase and in solvents of different dielectrics. The potential energy curves (PECs) calculated along the proton transfer (PT) coordinate are found to have a high energy barrier in the ground state and to be barrierless or have a low energy barrier in the excited state for both the forms. The calculated vertical excitation and the emission energy from the relaxed excited and PT states show good correlation with the experimental spectral data. Aggregation of BIBTB in water with red shifted emission was established from X-ray single-crystal structure analysis, solid state emission, and Dynamic Light Scattering (DLS) measurement. The molecule BIBTB also acts as a fluorescence probe for sensing the explosive picric acid in the subnano scale and can be used to determine the proportion of water in dimethyl sulfoxide (DMSO) solvent.

Inhibition of Vanadium Cathode Dissolution in Zinc‐Ion Batteries on Thermodynamics and Kinetics by Guest Pre‐Intercalation

AbstractAqueous zinc‐ion batteries (AZIBs), recognized for their safety and environmental friendliness, hold significant promise for large‐scale energy storage. However, the rapid capacity degradation resulting from the dissolution of active cathode materials hampers the advancement of AZIBs. Here, Ru0.2V2O5∙0.41H2O (RuVO) is synthesized with remarkable capacity retention (98.2% over 5000 cycles at 10 A g−1). The pre‐intercalation of Ru3+ enhances the stability of both intrinsic and cycling structures, elevating the Gibbs free energy and suppressing V‐dissolution thermodynamically. Additionally, Ru3+ intercalation modulates the potential energy surface of Zn2+ migration, leading to the dominance of Zn2+ in the insertion/extraction mechanism, thereby kinetically impeding the dissolution reaction. This study elucidates the dissolution thermodynamics and kinetics of V‐based cathodes through a combination of experiments, mechanism analyses, and density functional theory (DFT) calculations.

Unified deep learning network for enhanced accuracy in predicting thermal conductivity of bilayer graphene, hexagonal boron nitride, and their heterostructures

In this research, we utilized density functional theory (DFT) computations to perform ab initio molecular dynamics simulations and static calculations on graphene, hexagonal boron nitride, and their heterostructures, subjecting them to strains, perturbations, twist angles, and defects. The gathered energy, force, and virial information informed the creation of a training set comprising 1253 structures. Employing the Neural Evolutionary Potential framework integrated into Graphics Processing Units Molecular Dynamics, we fitted a machine learning potential (MLP) that closely mirrored the DFT potential energy surface. Rigorous validation of lattice constants and phonon dispersion relations confirmed the precision and dependability of the MLP, establishing a solid foundation for subsequent thermal transport investigations. A further analysis of the impact of twist angles uncovered a significant reduction in thermal conductivity, particularly notable in heterostructures with a decline exceeding 35%. The reduction in thermal conductivity primarily stems from the twist angle-induced softening of phonon modes and the accompanying increase in phonon scattering rates, which intensifies anharmonic interactions among phonons. Our study underscores the efficacy of the MLP in delineating the thermal transport attributes of two-dimensional materials and their heterostructures, while also elucidating the micro-mechanisms behind the influence of the twist angle on thermal conductivity, offering fresh perspectives for the design of advanced thermal management materials.

Calculating Potential Energy Surfaces with Quantum Computers by Measuring Only the Density Along Adiabatic Transitions.

We show that chemically accurate potential energy surfaces (PESs) can be generated from quantum computers by measuring only the density along an adiabatic transition between different molecular geometries. In lieu of using phase estimation, the energy is evaluated by performing line-integration using the inverted real-space time-dependent density functional theory Kohn-Sham (KS) potential obtained from the geometry-varying densities of the full wave function. The accuracy of this method depends on the validity of the adiabatic evolution itself and the potential inversion process (which is theoretically exact but can be numerically unstable), whereas the total evolution time is the defining factor for the precision of phase estimation. We examine the method with a one-dimensional system of two electrons for both the ground and first triplet states in first quantization, as well as the ground state of three- and four-electron systems in second quantization. It is shown that few accurate measurements can be utilized to obtain chemical accuracy across the full potential energy curve, with a shorter propagation time than may be required using phase estimation for a similar accuracy. We also show that an accurate potential energy curve can be calculated by making many imprecise density measurements (using a few shots) along the time evolution and smoothing the resulting density evolution. Finally, it is important to note that the method is able to classically provide a check of its own accuracy by comparing the density resulting from a time-independent KS calculation using the inverted potential with the measured density. This can be used to determine whether longer adiabatic evolution times are required to satisfy the adiabatic theorem.

Aerosol influence on cloud macrophysical and microphysical properties over the Tibetan Plateau and its adjacent regions.

This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan Plateau and its adjacent regions. The study regions are divided as the western part of the Tibetan Plateau (WTP), the Indo-Gangetic Plain (IGP), and the Sichuan Basin (SCB). All three regions show significant cloud effects under low aerosol loading conditions. In WTP, under low aerosol loading conditions, the effective radius of liquid cloud particles (LREF) decreases with the increase of aerosol loading, while the effective radius of ice cloud particles (IREF) and cloud top height (CTH) increase during the cold season. Increased aerosol loading might inhibit the development of warm rain processes, transporting more cloud droplets above the freezing level and promoting ice cloud development. During the warm season, under low aerosol loading conditions, both the cloud microphysical (LREF and IREF) and macrophysical (cloud top height and cloud fraction) properties increase with the increase of aerosol loading, likely due to higher dust aerosol concentration in this region. In IGP, both LREF and IREF increase with the increase in aerosol loading during the cold season. In SCB, LREF increases with the increase in aerosol loading, while IREF decreases, possibly due to the higher hygroscopic aerosol concentration in the SCB during the cold season. Meteorological conditions also modulate the aerosol-cloud interaction. Under different convective available potential energy (CAPE) and relative humidity (RH) conditions, the influence of aerosol on clouds varies in the three regions. Under low CAPE and RH conditions, the relationship between LREF and aerosol in both the cold and warm seasons is opposite in the WTP: LREF decreases with the increase of aerosol in the cold season, while it increases in the warm season. This discrepancy may be attributed to a difference in the moisture condition between the cold and warm seasons in this region. In general, the influence of aerosols on cloud properties in TP and its adjacent regions is characterized by significant nonlinearity and spatial variability, which is likely related to the differences in aerosol types and meteorological conditions between different regions.

Net-zero produced water strategy on gas production in marine gas hydrate bearing sediment

Gas hydrates, commonly found in deep marine sediments, have been considered a potential long-term energy source. Recent field trials demonstrated that well depressurisation, converting solid gas hydrates into fluid in situ, is the most efficient method for gas production. However, this process involves continuously pumping a large volume of water from the ocean that cannot be simply disposed of due to environmental concerns. The produced water, with temperature, salinity and residues different from those of shallower seawater, could impact marine species, habitats and ecosystems if directly discharged into the sea. Storing or transporting this water for treatment is economically impractical. Furthermore, as hydrate dissociation increases sediment permeability, water production rates rise over time. Therefore, re-injecting produced water into gas hydrate reservoirs emerges as a promising net-zero produced water strategy. This study investigates the effects of produced water re-injection on gas productivity and sediment deformation through coupled thermo-hydro-chemo-mechanical numerical analysis. The results indicate that re-injecting the water could improve gas productivity but may cause heave and differential displacement near the injection well. This highlights the importance of considering thermo-hydro-chemo-mechanical processes in comprehensively evaluating energy production strategies and suggests that further studies are necessary for future commercial gas production from gas hydrate reservoirs.

Microscopic analyses and performance characteristics of granite powder blended cement

This research investigates the characteristics of Granite Powder (GrP) and its potential use as a partial replacement for cement in mortar production. The GrP samples were analyzed via microscopic techniques. The effects of GrP Blended Cement (GrPBC) were examined on the workability and mechanical characteristics by partially replacing Ordinary Portland Cement (OPC) with 0–40 wt% GrP in 4 wt% increments. Life cycled assessment in terms of Embodied Energy (EE) and Global Warming Potential (GWP) of GrPBC-based mortar were assessed based on cradle-to-gate boundaries and the sustainability and economic indexes were determined at 28 days compressive strength. The study proposed new models to predict the compressive strength of GrPBC with respect to Water to Binder (W/B) ratio. The presence of active minerals depicts GrP as pozzolanic materials. The optimum replacement level of GrP in the blended mix, based on the fresh and hardened properties of GrPBC, is 20 wt% to achieve 75% of the strength activity index. GWP and EE declined as the GrP in the mixtures rose. The best sustainable and economic prospects were attained at the 25 wt% GrP replacement level. The compressive strength and the W/B ratio are highly correlated. Thus, GrP has proven to be a sustainable construction material in the construction sector.

OH-Formation following vibrationally induced reaction dynamics of H2COO.

The reaction dynamics of H2COO to form HCOOH and dioxirane as first steps for OH-elimination is quantitatively investigated. Using a machine learned potential energy surface (PES) at the CASPT2/aug-cc-pVTZ level of theory vibrational excitation along the CH-normal mode νCH with energies up to 40.0 kcal mol-1 (∼5νCH) leads almost exclusively to HCOOH which further decomposes into OH + HCO. Although the barrier to form dioxirane is only 21.4 kcal mol-1 the reaction probability to form dioxirane is two orders of magnitude lower if the CH-stretch mode is excited. Following the dioxirane-formation pathway is facile, however, if the COO-bend vibration is excited together with energies equivalent to ∼2νCH or ∼3νCOO. For OH-formation in the atmosphere the pathway through HCOOH is probably most relevant because the alternative pathways (through dioxirane or formic acid) involve several intermediates that can de-excite through collisions, relax via internal vibrational relaxation (IVR), or pass through loose and vulnerable transition states (formic acid). This work demonstrates how, by selectively exciting particular vibrational modes, it is possible to dial into desired reaction channels with a high degree of specificity.

Tuning the Oxygen Reduction Reactivity of Layered Perovskites Using the Jahn-Teller Effect.

Compositional tuning of layered perovskite oxides provides a means of systematically studying how local distortions affect fundamental aspects of electrochemical reaction pathways. Structural analysis of a family of samples La1.2Sr0.8Ni1-yCoyO4 shows that Ni-rich compositions have an expanded crystalline c axis, which is anisotropically compressed by systematic Co incorporation. Raman spectra reveal the strong growth of a symmetry forbidden mode, which suggests that Co acts through localized distortions. Crystallographic and spectroscopic parameters describing this structural distortion correlate to the measured Tafel slopes for the oxygen reduction reaction for all Ni-containing samples, which is attributed to the distortion of potential energy surfaces by the Jahn-Teller expansion of d7 Ni(III) cations. Incorporation of Co not only minimizes the distortion but alters the apparent selectivity of the oxygen reduction reaction away from H2O2 and toward H2O. Rotating ring-disk electrochemical measurements, however, indicate that the apparent change in selectivity is due to activation of a first-order chemical disproportionation of H2O2 that is activated by Co in the lattice. These outcomes will support efforts to design electrocatalysts and reactors for the electrochemical synthesis of H2O2.

Dissociation Constant of Di‐ and Tri‐Basic Solvents Based on Piperazine and Its Derivatives for Post‐Combustion CO2 Capture

AbstractAmine solvents remain popular in the industries for post combustion carbon dioxide (CO2) capture. Dissociation constant of basic amine solvents plays significant role to influence the CO2 absorption. It is thus important to study the dissociation of new amine solvents for assessing their viability for CO2 capture. In the present work, potentiometric titration method is employed to determine the dissociation constants of dibasic (e. g., Piperazine (PZ), 1‐methyl piperazine (1‐MPZ) and tribasic amines (1‐(2‐aminoethyl‐piperazine) (AEPZ) which could be promising for formulating blended solvent system towards enhancing the rate of CO2 absorption. The estimated dissociation constants for the PZ and 1‐MPZ while match well with reported results, the dissociation constants for AEPZ has been determined newly here within the temperature range 298—318 K. In addition, the structural geometric parameters and Natural Bond Order (NBO) calculations of the amine solvents are performed based on Density Functional Theory (DFT). The NBO calculations predict charge distribution on the nitrogen and other elements, and envisage its effect on the pKa values of the amines. Further, potential energy surface (PES) scanning calculations are performed for AEPZ to explain it's ring inversion which is responsible for obtaining a single pKa value in experimental studies.

Generalizability of empirical correlations for predicting higher heating values of biomass

ABSTRACT Designing efficient biomass energy systems requires a thorough understanding of the physicochemical, thermodynamic, and physical properties of biomass. One crucial parameter in assessing biomass energy potential is the higher heating value (HHV), which quantifies its energy content. Conventionally, HHV is determined through bomb calorimetry, but this method is limited by factors such as time, accessibility, and cost. To overcome these limitations, researchers have proposed a diverse range of empirical correlations and machine-learning approaches to predict the HHV of biomass based on proximate and ultimate analysis results. The novelty of this research is to explore the universal applicability of the developed empirical correlations for predicting the Higher Heating Value (HHV) of biomass. To identify the best empirical correlations, nearly 400 different biomass feedstocks were comprehensively tested with 45 different empirical correlations developed to use ultimate analysis (21 different empirical correlations), proximate analysis (16 different empirical correlations) and combined ultimate-proximate analysis (8 different empirical correlations) data of these biomass feedstocks. A quantitative and statistical analysis was conducted to assess the performance of these empirical correlations and their applicability to diverse biomass types. The results demonstrated that the empirical correlations utilizing ultimate analysis data provided more accurate predictions of HHV compared to those based on proximate analysis or combined data. Two specific empirical correlations including coefficients for each element (C, H, N) and their interactions (C*H) demonstrate the best HHV prediction with the lowest MAE (~0.49), RMSE (~0.64), and MAPE (~2.70%). Furthermore, some other empirical correlations with carbon content being the major determinant also provide good HHV prediction from a statistical point of view; MAE (~0.5–0.8), RMSE (~0.6–0.9), and MAPE (~2.8–3.8%).