Performance In Terms Of Stability Research Articles

Machine Learning Potential Model Based on Ensemble Bispectrum Feature Selection and Its Applicability Analysis

With the continuous improvement of machine learning methods, building the interatomic machine learning potential (MLP) based on the datasets from quantum mechanics calculations has become an effective technical approach to improving the accuracy of classical molecular dynamics simulation. The Spectral Neighbor Analysis Potential (SNAP) is one of the most commonly used machine learning potentials. It uses the bispectrum to encode the local environment of each atom in the lattice. The hyperparameter jmax controls the mapping complexity and precision between the local environment and the bispectrum descriptor. As the hyperparameter jmax increases, the description will become more accurate, but the number of parameters in the bispectrum descriptor will increase dramatically, increasing the computational complexity. In order to reduce the computational complexity without losing the computational accuracy, this paper proposes a two-level ensemble feature selection method (EFS) for a bispectrum descriptor, combining the perturbation method and the feature selector ensemble strategy. Based on the proposed method, the feature subset is selected from the original dataset of the bispectrum descriptor for building the dimension-reduced MLP. As a method application and validation, the data of Fe, Ni, Cu, Li, Mo, Si, and Ge metal elements are used to train the linear regression model based on SNAP for predicting these metals’ atomic energies and forces them to evaluate the performance of the feature subsets. The experimental results show that, compared to the features of SNAP and qSNAP, the training complexity improvement of our EFS method on the qSNAP feature is more effective than SNAP. Compared with the existing methods, when the feature subset size is 0.7 times that of the original features, the proposed EFS method based on the SSWRP ensemble strategy can achieve the best performance in terms of stability, achieving an average stability of 0.94 across all datasets. The training complexity of the linear regression model is reduced by about half, and the prediction complexity is reduced by about 30%.

Glycerol Dehydration to Acrolein Catalyzed by Silicotungstic Acid: Effect of Mesoporous Support

To facilitate value-added chemical production from renewable glycerol, gas-phase glycerol dehydration to acrolein was conducted using supported silicotungstic acid as solid acid catalysts, focusing on the effects of mesoporous catalyst supports on the catalytic performance. One alumina (Al) support with average mesopore size of 30 nm and two silica supports (Si1254 and Si1252) with mesopore size of 6 nm and 11 nm, respectively, were comparatively evaluated in this study. It was found that the Si1254 silica support with the smallest pore size (6 nm) deactivated the fastest, decreasing both the glycerol conversion and acrolein selectivity along the time-on-stream. The other silica support Si1252 with 11 nm pore size provided an acrolein yield comparable to the Al support over the tested 7.5 h time-on-stream (73.9 mol% for Si1252 vs. 74.1 mol% for Al). However, the mechanisms for achieving the comparable yield are different. Si1252 showed higher acrolein selectivity than Al, but it also deactivated faster than Al due to its quicker coking. On the other hand, Al showed more stable performance in terms of glycerol conversion rate and less coking, but it had lower acrolein selectivity and a higher selectivity to byproducts, especially the undesired byproducts of acetaldehyde and propionaldehyde, which posed difficulties in downstream separation.

Cocrystallization of lenvatinib and temozolomide to improve the performance in terms of stability, dissolution, and tabletability

Cocrystallization of two anti-melanoma drugs, lenvatinib and temozolomide, resulted in two drug–drug cocrystal solvates presenting improved performance in terms of stability, dissolution, and tabletability, which show great potential to be developed as a drug combination.

Conceptual design of long span steel-UHPC composite network arch bridge

An innovative half-through network arch bridge with a main span of 470 m was proposed and designed using coarse aggregate ultra-high-performance concrete (CA-UHPC) and steel. To effectively resist the tremendous axial forces, we utilized circular hollow section arch ribs with a CA-UHPC outer layer and an inner steel tube in this proposal. To minimize the bending moment of the arch ribs, we arranged the inclined crossed hangers above the deck and similarly the columns below the deck, connecting the arch ribs with the main girder, and adopting a structural system of double-hinged arches. By incorporating the recently developed multi-material bi-directional evolutionary structural optimization method and through various parametric studies, we determined the best configuration for the bridge. We also used finite element analysis to investigate the corresponding structural responses. The numerical analysis demonstrates that the proposed bridge has excellent mechanical performance in terms of stability, overall structural stiffness, stress, and fatigue strength of each component. A comprehensive comparison between the proposed bridge and the more conventional concrete-filled steel tube (CFST) arch bridge under the same conditions reveals that: the construction-related CO2 emissions of the proposed bridge are significantly lower than those of the CFST bridge, while the economic indicators are slightly better. The proposed bridge is simpler, slenderer, and more elegant. Due to its innovative design, the proposed bridge can overcome a series of problems associated with conventional bridges such as the excessive self-weight of long-span concrete arch bridges, the challenges of welding thick steel plates on all-steel arch bridges and the high cost of these structures, as well as the disadvantages of CFST arch bridges.

Development and Application of Similar Materials for Foundation Pit Excavation Model Test of Metro Station

Geomechanical model tests provide an intuitive and convenient method for observing physical phenomenon due to their easy implementation compared to in situ tests and prototype tests. The success of model tests depends heavily on the appropriate selection of model materials and proportions. Therefore, a new similar material is developed by utilizing the orthogonal experimental design method to conduct a series of proportioning tests. The new material is mixed with barite powder, iron ore powder, quartz sand, liquid paraffin, rosin, gypsum powder, and water. The physical and mechanical properties are studied through uniaxial compressive tests, Brazilian splitting tests, and direct shear tests. The influences of various raw material factors on the parameters of the similar material are systematically studied through range analysis. The results demonstrate that the mechanical parameters of similar materials have wide variation ranges; the adjustment range is 42.0–279.0 MPa for the elastic modulus, 0.37–5.37 MPa for the uniaxial compressive strength and 2.23–2.65 g/cm3 for the density. The new similar material has illustrated advantages in terms of performance stability, low price, and convenient production, which can simulate the similar relationship with different geomechanical model tests. The similar material is applied to a 3D geomechanical model test of the foundation pit excavation of Shenzhen metro station, which proves that the similar material can realistically reflect the change of earth pressure in the excavation process. With the deepening of excavation, the earth pressure curve shows significant fluctuations, and as the retaining structure is displaced, the parts with large earth pressure changes should be strengthened. The research methods and results can provide reference for further geological engineering research.

Development of a low-cost system for sampling microplastics in water

The microplastics sampling system in water was developed using low cost materials based on the international standard protocol of the National Oceanic and Atmospheric Administration with the use of a nylon sampling net fixed to a treated wooden structure and with plastic tubes responsible for buoyancy. . Sampling was carried out in marine and fresh water off the coast of Santa Catarina, using boats as trailers in order to collect samples along the coastline. The developed structure presented excellent performances in terms of stability and robustness during the sampling process. The analysis and characterization of microplastics was carried out according to protocol recommendations using separation sieves. The developed system can be used in environmental monitoring involving the sampling of microplastics in water, in addition to its cost-effectiveness and accessibility for professionals in the area.

Microstructure-oriented porcelain stoneware tile composition design

The design of porcelain stoneware tile composition is a very complex and time-consuming task, in the industry. After the long way to accomplish the product, processing, and cost requirements, the microstructure is seldom analyzed. If it is checked, it is not adjusted. The raw materials' chemical composition is one of the most helpful information to design. However, it has certain limitations because the mineralogy information is hidden. The paper approach formulates and optimizes porcelain stoneware compositions regarding raw materials' microstructure and mineralogy. Meta-analysis was applied to build models for mullite formation, firing temperature, and pyroplastic deformation. Kaolinite, illite/muscovite, talc, quartz, and feldspar were used as regressors. The robust microstructure is formed with interconnected mullite crystals. This feature could be numerically correlated to the mullite content ranging from 14% to 17%. Optimization was performed with mullite constrained from 13.5% to 17.5%, firing temperature <1230 °C and pyroplastic deformation <4.8x10−5 cm−1. It was possible to find feasible compositions’ intervals. For instance, kaolinite needs to be between 23% and 37%. The comparison with 34 industrial compositions found that 90% of them have kaolinite content below the robust interval. This means it has opportunities to improve product and process performance in terms of stability, quality, cost, productivity, waste material incorporation, and sustainability.

A new decentralized two-stage multi-objective control of secondary network driven hybrid microgrid under variable generation and load conditions

This paper proposes a new decentralized two-stage multi-objectives voltage control technique to ensure the operational stability of the hybrid MG over the variable renewable generations as well as to confirm its reliable operation against various industrial loads by minimizing the mismatch load terminal voltage. The effective operation of hybrid MG under the running of loads reclines on its dynamics which may become non-linear due to the utilization of additional inverter-oriented secondary network or electronics components in their evolution. Also, the efficacy of the secondary network-driven microgrid (SNM) is ascertained by taking the sustained transient response, however, its supremacy can be influenced by the sporadic features of renewable energy sources (RESs). This work introduces a new decentralized hybrid voltage control (DHVC) model to effectively drive the issues raised from the load’s operation and RESs. The proposed hybrid control technique integrates the linear and non-linear control scheme which works enabling a two-level control framework in MG terminal to confirm its enhanced operational stability and minimized unbalance voltage over the various operating conditions. The non-linear control framework of the proposed DHVC is made by utilizing the partial feedback linearization approach in generalized dynamics deriving from the DC–DC converters used with RESs and battery, while the linear control scheme uses a second-order damping (SOD) control framework to regulate the inverter used with load’s network. The controllability of the proposed DHVC is evaluated by measuring the response of the SNM in terms of operational stability and mismatch voltage minimization over the change of meteorological factors of the RESs and various industrial loads. Also, an external parametric uncertainty with the single-phase secondary network dynamics is studied to guarantee the robustness of the proposed DHVC. Additionally, a comparative study is studied to cover the augmented performance of the hybrid microgrid.

Cross‐Encoded Quantum Key Distribution Exploiting Time‐Bin and Polarization States with Qubit‐Based Synchronization

AbstractRobust implementation of quantum key distribution requires precise state generation and measurements, as well as the choice of an optimal encoding to minimize channel disturbance. Time‐bin encoding represent a good candidate for fiber links as birefingence does not perturb this kind of states whereas stable and low‐error encoders and decoders are available for polarization encoding. Here a cross‐encoded scheme where high accuracy quantum states are prepared through a self‐compensating, calibration‐free polarization modulator and transmitted using a polarization‐to‐time‐bin converter is presented. The receiver performs time‐of‐arrival measurements in the key‐generation basis and converts qubits back to polarization encoding for measurements in the control basis. Temporal synchronization between the transmitter and receiver is performed with a qubit‐based method that does not require additional hardware to share a clock reference. The system is tested in a 12‐h run and demonstrates good and stable performance in terms of key and quantum bit error rates. The flexibility of this approach represents an important step toward the development of hybrid networks with both fiber‐optic and free‐space links.

Static CMOS Physically Unclonable Function Based on 4T Voltage Divider With 0.6%–1.5% Bit Instability at 0.4–1.8 V Operation in 180 nm

This article introduces a novel class of static and monostable CMOS physically unclonable functions (PUFs) for hardware security applications. The PUF bitcell is based on a sub-threshold four-transistor (4T) voltage divider as the core block, along with an inverter as the output stage. The 4T voltage divider consists of two series-connected and nominally identical PMOS-only two-transistor (2T) circuits. This allows inherently random bit generation assisted by mismatch while also ensuring inherent robustness against environmental variations. A 180-nm test chip was characterized to validate our solution. Measurements of the 4T bitcell core prove its capability to generate random voltages with high dispersion (i.e., close to either ground or supply voltage levels) and high stability across a wide range of environmental conditions. The statistical PUF performance was evaluated on an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times32$ </tex-math></inline-formula> bitcell array without applying any post-silicon stability-enhancement technique. Raw measurements reveal a bit instability of only ~0.6% at golden key (GK) conditions (1.8 V and 25 °C), which increases up to 1.5% at 0.4 V and room temperature. When compared to prior art, our solution shows competitive performance in terms of stability, uniqueness (mean normalized inter-PUF Hamming distance (HD) of 0.493), and reproducibility (mean normalized intra-PUF HD of 0.0016), at the cost of more area-hungry design (~7200-F <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> bitcell area).

Quaternized polyepichlorohydrin-based membrane as high-selective CO2 sorbent for cost-effective carbon capture

A trimethylammonium-functionalized polyepichlorohydrin membrane (TPp) was synthesized using inexpensive, eco-friendly raw materials and easy synthetic steps and evaluated as CO2 sorbent. The polymeric membrane exhibited satisfactory sorbent performance in terms of stability, rapid adsorption, high selectivity and working capacity. The peak capture capability of 1.34 mmol g-1 was achieved at 25 °C under simulated flue gas condition (humidified 10% CO2, 20% RH). The quaternary ammonium groups enable superior amine efficiency (0.95 mmol CO2/mmol N at 25 °C), well exceeding the highest value reported to date for low-temperature CO2 sorbents under simulated flue gas conditions, and reversible trap-release of CO2. De facto, the TPp sorbent can be completely regenerated under mild conditions (50 °C in pure N2 for 20 min), with only 64.8 kJ mol-1 consumed during sorbent regeneration. The low cost, versatility and ease of preparation make the TPp membrane a promising sorbent for scalable and cost-effective CO2 capture.

Multilayer-coated hydrogel membranes with comprehensive fouling resistance and stability for wastewater treatment

Organic fouling was one of the most fatal weakness for membranes applied in water treatment. Aiming at overcoming the defect of liable to contamination and achieving efficient circulation and long-term stable operation, it was reported a kind of multilayer-loaded hydrogels membranes with superior antifouling property. Hydrogel coating mixture were coated onto PES substrate layer by layer and then cross-linked by ambient free radical blending polymerization reaction endowing the membrane with interpenetrating network structure and super hydrophilic surface. The FT-IR, FESEM, and AFM were used to character the structure and morphology of obtained membranes. Dynamic contact Angle, BET and membrane performance evaluation instrument were used to evaluate the membrane performance. Compared with quantitative single layer-coated membrane, the four layers-coated hydrogel membrane exhibited more excellent and stable performance in terms of flux, rejection and fouling resistance. In particular, the water flux of the four layers-coated hydrogel membrane increased by about 25%. When 0.5 g/L BSA was selected as simulated protein contamination liquid, flux recovery rate (FRR) of four layers-coated hydrogel membranes was up to 86.33%, indicating excellent long-term tolerance and resistance to proteins. It must be pointed out that four layers were the maximum loading number of the ambient self-crosslinking hydrogel CQAS casting solution within the limit air-cured time. On the whole, the multi-layer coated hydrogel membranes showed practical application value in the field of water treatment.

Amyloid-based carbon aerogels for water purification

Water scarcity is a worldwide concern with various implications, such as widespread pollution with heavy metals and organic pollutants, resulting in global threats to the environment and human health, and calling for innovative remediation strategies. We show here that the capability of protein-based carbon aerogels for removing contaminants from water can be greatly improved by transforming proteins into amyloids before their hydrothermal carbonization. Amyloid fibrils were prepared from whey protein isolate, a by-product of the dairy industry, and upon addition to different carbohydrates, the ensued mixtures were used for carbon aerogels production. Furthermore, the generality of the approach for producing carbon aerogels was demonstrated using vegetable amyloids from soy protein. The carbon aerogels are able to adsorb Au(III), Pt(II), Fe(III), and Ag(I) with excellent removal efficiencies. Moreover, the amyloid whey lactose carbon aerogel has an adsorption capacity of 650.08 mg/g for Au(III), significantly higher than that of a carbon aerogel derived from monomer whey lactose. The reusability of the carbon aerogel is also proven over three continuous adsorption/regeneration cycles, with a stable performance in terms of removal efficiency indicating good long-term use. Taken together, the results demonstrate amyloid carbon aerogels’ capability as an efficient, sustainable, and inexpensive solution for water purification.

Integration of distributed generations by coordinating electric vehicle charging station in medium voltage network by Swarm intelligence

PurposeNotable energy losses and voltage deviation issues in low-voltage radial distribution systems are a major concern for power planners and utility companies because of the integration of electric vehicles (EVs). Electric vehicle charging stations (EVCSs) are the key components in the network where the EVs are equipped to energize their battery. The purpose of this paper is coordinating the EVCS and distributed generation (DG) so as to place them optimally using swarm-based elephant herding optimization techniques by considering energy losses, voltage sensitivity and branch current as key indices. The placement and sizing of the EVCS and DG were found in steps.Design/methodology/approachThe IEEE 33-bus test feeder and 52-bus Indian practical radial networks were used as the test system for the network characteristic analysis. To enhance the system performance, the radial network is divided into zones for the placement of charging stations and dispersed generation units. Balanced coordination is discussed with three defined situations for the EVCS and DG.FindingsThe proposed analysis shows that DG collaboration with EVCS with suitable size and location in the network improves the performance in terms of stability and losses.Research limitations/implicationsStability and loss indices are handled with equal weight factor to find the best solution.Social implicationsThe proposed method is coordinating EVCS and DG in the existing system; the EV integration in the low-voltage side can be incorporated suitably. So, it has societal impact.Originality/valueIn this study, the proposed method shows improved results in terms EVCS and DG integration in the system with minimum losses and voltage sensitivity. The results have been compared with another population-based particle swarm optimization method (PSO). There is an improvement of 18% in terms of total power losses and 9% better result in minimum node voltage as compared to the PSO technique. Also, there is an enhancement of 33% in the defined voltage stability index which shows the proficiency of the proposed analysis.

Advancing the stability and efficiency of quantum dot-sensitized solar cells through a novel, green, and water-based thixotropic biopolymer/ordered nanopores silica designed quasi-solid-state gel electrolytes

The practical application of liquid electrolyte-constructed quantum-dot sensitized solar cells (QDSSCs) is far from satisfactory due to the short-term performance, poor TiO2 penetration, leakage, and volatilization of liquid electrolytes. In this respect, three of the most critical problems with QDSSCs are addressed in this research: (i) low open-circuit voltage (VOC); (ii) low fill factor (FF), thereby, low efficiency; and, (iii) the device's poor performance stability over time. Herein, a simple approach to fabricate water-based quasi-solid-state gel electrolytes (QSSGE) designed QDSSCs by combining guar gum (GG) biopolymer and ordered nanopores silica (SBA) is reported. For the first time, SBA is being employed as an electrolyte additive to catalyze the reduction of polysulfide electrolyte more efficiently. The resultant SBA/GG gel electrolytes system offers several advantages including (i) passivating the surface trap states between TiO2/QD/electrolyte interfaces; (ii) providing a three-dimensional (3D) porous structure for the free migration of ions; (iii) its surface rich hydroxyl groups establish good contact with the photoanode. The Cu-In-S sensitized devices with SBA/GG gel electrolytes demonstrated superior power conversion efficiencies (PCE) of 9.14% in one full sunlight. This photovoltaic performance is considered to be one of the highest for copper-based QDSSCs. The outstanding PCE with gel electrolyte-constructed QDSSCs are reflected from simultaneous augmentation in VOC and FF that initiated by the synergistic interaction between SBA and GG for controlled interfacial electron-hole recombination dynamics. Moreover, gel electrolyte-constructed QDSSCs outperformed both SBA and liquid electrolyte-constructed QDSSCs in terms of performance stability, lasting up to 168 h instead of 120 or 72 h, respectively. The primary goal of this research is to develop biopolymer-based QSSGEs that are both efficient and stable while also being environmentally beneficial.

Rationally designed bilayer heterojunction electrode to realize multivalent ion intercalation in bifunctional devices: Efficient aqueous aluminum electrochromic supercapacitor with transparent nanostructured TiO2/MoO3

Bifunctional electrochromic energy storage devices are of great potential in energy-efficient technologies. Present electrochromic capacitors utilize monovalent ion intercalation, and switching to a multivalent ion such as Al3+ is sought to sustainably overcome the prevailing performance limitations. However, the realization of such a bifunctional device has remained a challenge, owing to the strong electrostatic interaction of multivalent ions with the electrode material. To cross this hurdle, we present here a nanostructured transparent anatase TiO2/α-MoO3 bi-layer electrode having a host with wide lattice spacing and forming a type II heterojunction at the interface. The favourable features offered by MoO3 and the built-in potential at the heterojunction interface resulted in a superior and stable performance in terms of coloration efficiency (128 cm2/C), transmittance change (54%), switching time (∼1s) and areal capacitance (218.8 mF/cm2). Thus, a new approach of electrode design for achieving multivalent ion intercalation in bifunctional devices is exemplified with an aqueous aluminum electrochromic supercapacitor, and the best-in-class bifunctional performance of the TiO2/MoO3 bilayer heterojunction electrode proves its potential to be used in energy-saving technologies of the future.

Self-Organizing mmWave MIMO Cell-Free Networks With Hybrid Beamforming: A Hierarchical DRL-Based Design

In a cell-free wireless network, distributed access points (APs) jointly serve all user equipments (UEs) within their coverage area by using the same time/frequency resources. In this paper, we develop a novel downlink cell-free multiple-input multiple-output (MIMO) millimeter wave (mmWave) network architecture that enables all APs and UEs to dynamically self-partition into a set of independent cell-free subnetworks in a time-slot basis. For this, we propose several network partitioning algorithms based on deep reinforcement learning (DRL). Furthermore, to mitigate interference between different cell-free subnetworks, we develop a novel hybrid analog beamsteering-digital beamforming model that zero-forces interference among cell-free subnetworks and at the same time maximizes the instantaneous sum-rate of all UEs within each subnetwork. Specifically, the hybrid beamforming model is implemented by using a novel mixed DRL-convex optimization method in which analog beamsteering between APs and UEs is conducted based on DRL while digital beamforming is modeled and solved as a convex optimization problem. The DRL models for network clustering and hybrid beamsteering are combined into a single hierarchical DRL design that enables exchange of DRL agents&#x2019; experiences during both network training and operation. We also benchmark the performance of DRL models for clustering and beamsteering in terms of network performance, convergence rate, and computational complexity. Results show a significant rate enhancement due to the proposed hybrid beamforming scheme compared to its conventional all-digital counterpart. This performance enhancement becomes more significant as the number of network partitions increases. For DRL-based network clustering, the policy gradient (PG) algorithm offers the best possible performance in terms of stability and convergence rate while the state-action-reward-state-action (SARSA) algorithm suffers from significant variance, slower convergence, and slightly inferior performance than other algorithms. For DRL-based beamsteering, the soft actor-critic (SAC) algorithm with continuous action space shows the best performance. Also, online training of the agents with varying channel state information (CSI) is observed to increase the variance of the Q-values and decrease the convergence rate, with no significant effect on the average reward. The simulation codes are available at: <monospace><uri>https://github.com/yasser-aleryani/mmWaveCellFree.git</uri></monospace>

Dual sites modulating MoO2 nanospheres for synergistically enhanced electrocatalysis of water oxidation

Oxygen evolution reaction (OER) is of critical importance in the area of electrocatalysis as it is frequently involved in a diversity of electrochemical devices. Molybdenum-based materials, thanks to their metallic character induced high conductivity, have been widely studied as catalysts for a variety of reactions but few reports for oxygen evolution reaction (OER). Herein, we report a dual-sites modifying strategy to modulate electrocatalytic properties of metallic MoO2 nanospheres toward OER, which is implemented by a one-pot synthesis process to prepare nickel and iron co-doped molybdenum oxide (Mo0.9Ni0.05Fe0.05O2). The introduction of dual sites (i.e., Ni and Fe) on MoO2 nanospheres surface can tune the surface electronic structure and local-chemical environment with generation of high-valence Mo and hydroxyl-rich surface, synergistically contributing to the improved electrocatalytic performance in terms of stability and activity. Density functional theory (DFT) calculation indicates Fe-doping site favors for enhancing the turnover efficiency (TOF) while the Ni-doping site facilitates the first proton coupled electron transfer (PCET) upon electrocatalysis of OER. The Mo0.9Ni0.05Fe0.05O2 requires only 249 mV of overpotential to reach a current density of 10 mA cm−2 with excellent stability for 80 h. This study expands the research on molybdenum-based OER catalysts and gains insight into the origin of both the activity and stability of Ni/Fe-doping reactive sites.

Bimetallic (Pt-Ni) La-hexaaluminate catalysts obtained from aluminum saline slags for the dry reforming of methane

This work describes the synthesis of platinum-nickel/lanthanum hexaaluminates (PtNi/LHA) and their performance in terms of stability and catalytic activity in the dry reforming of methane (DRM) at 973 K. An Al solution (9.40 g/L) obtained from an Al saline slag waste by acid extraction was used to synthesize the hexaaluminate by mixing with a stoichiometric amount of lanthanum nitrate and methanol/Peg400/PegMn400 under hydrothermal conditions at 493 K for 16 h. After calcination at 1473 K for 2 h, the presence of LHA was confirmed. Wet impregnation of the synthesized support was used to obtain an initial Ni/LHA catalyst (10 wt% NiO) and the modified PtNi/LHA catalysts (0.2–1 wt% Pt). The support and catalysts were characterized by X-ray diffraction (XRD), N2 adsorption at 77 K, temperature-programmed reduction (TPR), scanning electron microscopy (SEM) and transmission electron microscopy (HR-TEM). The analysis of the TPR patterns for the catalysts allowed the type of metal support interaction and NiO species to be determined, with a weak interaction with the support being observed in all cases. The presence of Pt promoted NiO reducibility. The PtNi/LHA catalysts synthesized were found to be active and very stable in the DRM reaction after reaction for 50 h. The catalytic behavior was evaluated from the CO2 and CH4 conversions, as well as the H2/CO selectivity, with values of between 89% and 92% in almost all the time range evaluated. The presence of Pt improved the stability and catalytic performance of Ni/LHA thus improving resistance to coke formation.

A critical review on the two-stage biohythane production and its viability as a renewable fuel

With over 130 countries signing the net-zero coalition treaty to reduce the global warming, the interest to replace fossil-fuels is constantly increasing. Also, there exists an increased concern to reduce the pollution load from waste biomass. Though the socio-economic benefits of biomethane production from these wastes have been an enticing study of the recent past, a sequential biohydrogen and biomethane production is said to offer more in terms of operational stability, energy yield, and cleaner by-products. This review thus tries to provide insights to have a better understanding on the process of biohydrogen production and subsequent biomethane production and the challenges associated with upscaling. With over 40% reduction in carbon monoxide and carbon dioxide emissions, the viability of Hythane as a clean and renewable fuel are also discussed.