Improved hydrogen storage performance of Mg(NH2)2/LiH mixture by addition of carbon nanostructured materials

The effect of different carbon nanostructures specifically carbon nanotubes (CNTs) and carbon nanofibers (CNFs) on the improvement of the de/re-hydrogenation characteristics of a Mg(NH₂)₂/LiH mixture have been studied. Amongst CNTs and CNFs, the improvement in the hydrogenation properties for the Mg(NH₂)₂/LiH mixture is higher when CNFs are used as a catalyst. Investigations are also focused on the deployment of two different types of CNF (a) CNF1 (synthesized using a ZrFe₂ catalyst) and (b) CNF2 (synthesized using a LaNi₅ catalyst). The results show that CNF2 is better. The maximum decomposition temperature for the pristine Mg(NH₂)₂/LiH mixture is found to be ∼250 °C, which is reduced to ∼180 and ∼150 °C for the sample mixed with 4 wt% of multi-walled carbon nanotubes (MWCNTs) and CNF2 respectively. The activation energy for the dehydrogenation reaction is found to be 74 and 68 kJ mol⁻¹ for the samples mixed with MWCNT and CNF2 respectively, whereas the activation energy for the dehydrogenation reaction of the pristine Mg(NH₂)₂/LiH mixture is 97 kJ mol⁻¹. The catalytic activity and the de/re-hydrogenation characteristics of the Mg(NH₂)₂/LiH mixture mixed with different carbon nanostructures are described and discussed.     

Robust optimisation of machining conditions with tool life and surface roughness uncertainties

The economics of the multi-pass turning problem is considered, while accounting for tool life uncertainty. The goal is to minimise the expected production cost per part, given the probability distribution for tool life, and with machining parameters being subject to practical constraints. The cost function accounts for machining cost, idling cost, tool changing cost as well as the cost associated with tool failure. A modified version of the particle swarm optimisation (PSO) algorithm, called the dynamic objective PSO (or DOPSO), is used for minimisation of the cost function. The decision variables include not only the machining parameters but also the tool replacement time. The equality constraint that the total desired depth of cut be achieved by an integral number of roughing passes and a single finishing pass is handled in a novel way, and together with including tool replacement time as a decision variable, this leads to lower costs than those cited by other comparable previous works. To handle uncertain constraints that lead to part failure when violated (e.g. desired surface finish), a robust formulation is also suggested through similar incorporation in the cost function, as for tool failure.     

Classification of organic and biological materials with deep ultraviolet excitation

We show that native fluorescence can be used to differentiate classes or groups of organic molecules and biological materials when excitation occurs at specific excitation wavelengths in the deep ultraviolet (UV) region. Native fluorescence excitation-emission maps (EEMs) of pure organic materials, microbiological samples, and environmental background materials were compared using excitation wavelengths between 200-400 nm with emission wavelengths from 270 to 500 nm. These samples included polycyclic aromatic hydrocarbons (PAHs), nitrogen- and sulfur-bearing organic heterocycles, bacterial spores, and bacterial vegetative whole cells (both Gram positive and Gram negative). Each sample was categorized into ten distinct groups based on fluorescence properties. Emission spectra at each of 40 excitation wavelengths were analyzed using principal component analysis (PCA). Optimum excitation wavelengths for differentiating groups were determined using two metrics. We show that deep UV excitation at 235 (+/-2) nm optimally separates all organic and biological groups within our dataset with >90% confidence. For the specific case of separation of bacterial spores from all other samples in the database, excitation at wavelengths less than 250 nm provides maximum separation with >6sigma confidence.     

Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data‐Based Methods

The application of computationally inexpensive modeling methods for a predictive study of powder mixing is discussed. A multidimensional population balance model is formulated to track the evolution of the distribution of a mixture of particle populations with respect to position and time. Integrating knowledge derived from a discrete element model, this method can be used to predict residence time distribution, mean and relative standard deviation of the API concentration in a continuous mixer. Low‐order statistical models, including response surface methods, kriging, and high‐dimensional model representations are also presented. Their efficiency for design optimization and process design space identification with respect to operating and design variables is illustrated.

     

Dynamic optimization of a dividing-wall column using model predictive control

Dividing-wall column (DWC) is one of the best examples of process intensification, as it can bring significant reduction in the capital invested as well as savings in the operating costs. Conventional ternary separations progressed from the (in-)direct sequences to thermally coupled columns such as Petlyuk configuration, and later to the DWC compact design that integrates the two distillation columns into a single shell. Nevertheless, this integration leads also to changes in the control and operating mode due to the higher number of degrees of freedom.In this work we explore the dynamic optimization and advanced control strategies based on model predictive control (MPC), coupled or not with PID. These structures were enhanced by adding an extra loop controlling the heavy component in the top of the feed side of the column, using the liquid split as manipulated variable, thus implicitly achieving energy minimization. To allow a fair comparison with previously published references, this work considers as a case-study the industrially relevant separation of the mixture benzene–toluene–xylene (BTX) in a DWC.The results show that MPC leads to a significant increase in performance, as compared to previously reported conventional PID controllers within a multi-loop framework. Moreover, the optimization employed by the MPC efficiently accommodates the goal of minimum energy requirements – possible due to the addition of an extra loop – in a transient state. The practical benefits of coupling MPC with PID controllers are also clearly demonstrated.     

Classification of Sunflower Oil Blends Stabilized by Oleoresin Rosemary (Rosmarinus officinalis L.) Using Multivariate Kinetic Approach

The sunflower oil–oleoresin rosemary (Rosmarinus officinalis L.) blends (SORB) at 9 different concentrations (200 to 2000 mg/kg), sunflower oil–tertiary butyl hydroquinone (SO_TBHQ) at 200 mg/kg and control (without preservatives) (SO_control) were oxidized using Rancimat (temperature: 100 to 130 °C; airflow rate: 20 L/h). The oxidative stability of blends was expressed using induction period (IP), oil stability index and photochemiluminescence assay. The linear regression models were generated by plotting ln IP with temperature to estimate the shelf life at 20 °C (SL₂₀; R² > 0.90). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to classify the oil blends depending upon the oxidative stability and kinetic parameters. The Arrhenius equation adequately described the temperature‐dependent kinetics (R² > 0.90, P < 0.05) and kinetic parameters viz. activation energies, activation enthalpies, and entropies were calculated in the range of 92.07 to 100.50 kJ/mol, 88.85 to 97.28 kJ/mol, ?33.33 to ?1.13 J/mol K, respectively. Using PCA, a satisfactory discrimination was noted among SORB, SO_TBHQ, and SO_control samples. HCA classified the oil blends into 3 different clusters (I, II, and III) where SORB₁₂₀₀ and SORB₁₅₀₀ were grouped together in close proximity with SO_TBHQ indicating the comparable oxidative stability. The SL₂₀ was estimated to be 3790, 6974, and 4179 h for SO_control, SO_TBHQ, and SORB₁₅₀₀, respectively. The multivariate kinetic approach effectively screened SORB₁₅₀₀ as the best blend conferring the highest oxidative stability to sunflower oil. This approach can be adopted for quick and reliable estimation of the oxidative stability of oil samples.     

ZnO thin films,surface embedded with biologically derived Ag/Au nanoparticles,for efficient photoelectrochemical splitting of water

ZnO thin films, showing nano-ridges at the surface and the top layer embedded with metal (Ag/Au) nanoparticles (MNP), were obtained by sol-gel synthesis, using zinc acetate dihydrate [(CH₃.COO)₂Zn.2H₂O] as precursor. The method involved prior synthesis of Ag and Au nanoparticles via biological reduction of AgNO₃ and HAuCl₄, respectively, using algae Spirulina platensis. The XRD analysis indicated dominant evolution of wurtzite ZnO phase. Low-angle shift in peaks, seen with nanoparticles embedded films, indicated partial diffusion of metals into ZnO lattice. Band gap energy was least affected and lied in the expected range. AFM and SEM analysis revealed the surface topography and morphology, while EDX analysis confirmed the elemental stoichiometry and existence of Ag/Au nanoparticles in samples. Significant gain in photoelectrochemical current using MNP embedded films is largely accountable to the improvement in electrical conductance and the role played by metal nanoparticles in charge-carrier separation, collection and transport.     

Iron doped nanostructured TiO2 for photoelectrochemical generation of hydrogen

This paper describes the photoelectrochemical studies on nanostructured iron doped titanium dioxide (TiO₂) thin films prepared by sol-gel spin coating method. Thin films were characterized by X-ray diffraction, Raman spectroscopy, spectral absorbance, atomic force microscopy and photoelectrochemical (PEC) measurements. XRD study shows that the films were polycrystalline with the photoactive anatase phase of TiO₂. Doping of Fe in TiO₂ resulted in a shift of absorption edge towards the visible region of solar spectrum. The observed bandgap energy decreased from 3.3 to 2.89 eV on increasing the doping concentration upto 0.2 at.% Fe. 0.2 at.% Fe doped TiO₂ exhibited the highest photocurrent density, ∼0.92 mA/cm² at zero external bias. Flatband potential and donor density determined from the Mott–Schottky plots were found to vary with doping concentration from −0.54 to −0.92 V/SCE and 1.7 × 10¹⁹ to 4.3 × 10¹⁹ cm⁻³, respectively.     

Hydrogen energy in changing environmental scenario: Indian context

This paper deals with how the Hydrogen Energy may play a crucial role in taking care of the environmental scenario/climate change. The R&D efforts, at the Hydrogen Energy Center, Banaras Hindu University have been described and discussed to elucidate that hydrogen is the best option for taking care of the environmental/climate changes. All three important ingredients for hydrogen economy, i.e., production, storage and application of hydrogen have been dealt with. As regards hydrogen production, solar routes consisting of photoelectrochemical electrolysis of water have been described and discussed. Nanostructured TiO₂ films used as photoanodes have been synthesized through hydrolysis of Ti[OCH(CH₃)₂]₄. Modular designs of TiO₂ photoelectrode-based PEC cells have been fabricated to get high hydrogen production rate (10.35 lh⁻¹ m⁻²). However, hydrogen storage is a key issue in the success and realization of hydrogen technology and economy. Metal hydrides are the promising candidates due to their safety advantage with high volume efficient storage capacity for on-board applications. As regards storage, we have discussed the storage of hydrogen in intermetallics as well as lightweight complex hydride systems. For intermetallic systems, we have dealt with material tailoring of LaNi₅ through Fe substitution. The La(Ni_l − xFe_x)₅ (x = 0.16) has been found to yield a high storage capacity of 2.40 wt%. We have also discussed how CNT admixing helps to improve the hydrogen desorption rate of NaAlH₄. CNT (8 mol%) admixed NaAlH₄ is found to be optimum for faster desorption (3.3 wt% H₂ within 2 h). From an applications point of view, we have focused on the use of hydrogen (stored in intermetallic La–Ni–Fe system) as fuel for Internal Combustion (IC) engine-based vehicular transport, particularly two and three-wheelers. It is shown that hydrogen used as a fuel is the most effective alternative fuel for circumventing climate change.     

Recycled waste paper—A new source of raw material for electric double-layer capacitors

For the first time, a new carbon–carbon composite electrode material for supercapacitors is prepared by simple KOH activation of waste newspaper. The amorphous nature and surface morphology of the carbon composite are investigated by X-ray diffraction (XRD), N₂ adsorption/desorption and scanning electron microscopy. The surface area and pore diameter are 416 m² g⁻¹ and 5.9 nm, respectively. Electrochemical characteristics are evaluated by cyclic voltammetry (CV) and charge–discharge tests in 6.0 M KOH at a 1 mA cm⁻² current density. The CV results reveal a maximum specific capacitance of 180 F g⁻¹ at a 2 mV s⁻¹ scan rate and the data explore a development of new use for waste paper into a valuable energy storage material.