Heavy Ion Research Articles

Enhanced performance of amine and thiol chemically modified graphene oxide for effective removal of Hg(II), Pb(II), and Cr(VI) from aqueous solution

This study describes a novel adsorbent with a multidentate ligand that was facilely fabricated by covalently bonding 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole on graphene oxide (AHMT-PRGO). The AHMT-PRGO nano-adsorbent was used for the effective removal of Hg(II), Pb(II), and Cr(VI) from wastewater. The AHMT-PRGO nano-adsorbent was synthesized by a nucleophilic substitution reaction between GO acyl chloride and AHMT chelating ligand in the presence of tetrabutyl-ammonium bromide as a catalyst. The successful modifications were confirmed via several spectroscopic and electron microscopy instrumentations including UV–Vis, FTIR, Raman, XRD, XPS, SEM, and TEM. The maximum adsorption capacities of Hg(II), Cr(VI), and Pb(II) on the AHMT-PRGO nano-adsorbent were 370.0, 136.2, and 109.6 mg/g, respectively, exceeding those of most previously reported adsorbents. Additionally, the equilibrium contact times for Hg(II), Pb(II), and Cr(VI) were 60, 30, and 400 min, respectively. In a mixture of nine heavy metal ions containing 250 ppm of each ion, the AHMT-PRGO nano-adsorbent exhibited high selectivity for Hg(II) ions. Furthermore, the AHMT-PRGO nano-adsorbent showed high stability over five adsorption–desorption cycles. Additionally, the AHMT-PRGO nano-adsorbent was successfully applied to remove heavy metal ions from real water samples. The novelty of AHMT-PRGO lies in the combination of a multidentate ligand for strong and selective binding with the high surface area and stability offered by covalently bonded graphene oxide. This combination offers potential advantages over traditional adsorbents in terms of adsorption capacity, selectivity, and reusability.

Mixed-matrix membrane designed with water channels and sieving effect for effective removal of heavy metals

The challenge of eliminating heavy metal ions from water has been addressed using Polysulfone (PSf) membranes, which have demonstrated significant potential in treating contaminated solutions. This research aimed to improve the permeability and separation performance of PSf membranes by incorporating Al2SiO6 into their structure. The introduction of Al2SiO6 into the membrane matrix was achieved through the nonsolvent-induced phase separation (NIPS). The resulting mixed-matrix membrane (MMM) exhibited improved efficiency in water filtration. The inclusion of Al2SiO6 led to desirable changes in membrane properties such as hydrophilicity, contact angle and porosity, thereby enhancing the performance of heavy metal ion removal capability. Under a pressure of 2 bar, the mixed matrix membranes achieved rejections exceeding 95 % for lead and 70 % for arsenic. Furthermore, the occurrence of Al2SiO6 enhanced the anti-fouling assets of the PSf membrane by increasing its hydrophilic nature and facilitating the development of a hydration layer, which tends to prevent the interactions between the membrane surface and foulant. These properties make these membranes suitable candidates for separating toxic ions from water.

QCD equation of state and thermodynamic observables from computationally minimal Dyson-Schwinger equations

We study the QCD equation of state and other thermodynamic observables including the isentropic trajectories and the speed of sound. These observables are of eminent importance for the understanding of experimental results in heavy ion collisions and also provide a QCD input for studies of the timeline of heavy-ion-collisions with hydrodynamical simulations. They can be derived from the quark propagator whose gap equation is solved within a minimal approximation to the Dyson-Schwinger equations (DSEs) of QCD at finite temperature and density. This minimal approximation aims at a combination of computational efficiency and simplification of the truncation scheme while maintaining quantitative precision. This minimal DSE scheme is confronted and benchmarked with results for correlation functions and observables from lattice QCD at vanishing density and quantitative functional approaches at finite density. Published by the American Physical Society 2024

Unveiling microstructural damage for leakage current degradation in SiC Schottky diode after heavy ions irradiation under 200 V

Single-event burnout and single-event leakage current (SELC) in silicon carbide (SiC) power devices induced by heavy ions severely limit their space application, and the underlying mechanism is still unclear. One fundamental problem is lack of high-resolution characterization of radiation damage in the irradiated SiC power devices, which is a crucial indicator of the related mechanism. In this Letter, high-resolution transmission electron microscopy (TEM) was used to characterize the radiation damage in the 1437.6 MeV 181Ta-irradiated SiC junction barrier Schottky diode under 200 V. The amorphous radiation damage with about 52 nm in diameter and 121 nm in length at the Schottky metal (Ti)–semiconductor (SiC) interface was observed. More importantly, in the damage site the atomic mixing of Ti, Si, and C was identified by electron energy loss spectroscopy and high-angle annular dark-field scanning TEM. It indicates that the melting of the Ti–SiC interface induced by localized Joule's heating is responsible for the amorphization and the possible formation of titanium silicide, titanium carbide, or ternary phases. The mushroom-like hillock in the Ti layer can be attributed to Rayleigh–Taylor instability, as another evidence for ever-happened localized melting near the Schottky interface. These modifications at nanoscale in turn cause localized degradation of the Schottky contact, resulting in permanent increase in leakage current. This experimental study provides very valuable clues for a thorough understanding of the SELC mechanism in SiC diodes.

Waste to treasure: porous manganese oxides derived from the waste liquid for heavy metal ion adsorption

Waste to treasure: porous manganese oxides derived from the waste liquid for heavy metal ion adsorption

Metal‐Free Modification Overcomes the Photocatalytic Limitations of Graphitic Carbon Nitride: Efficient Production and In Situ Application of Hydrogen Peroxide

AbstractGraphitic carbon nitride (g‐C3N4) assisted photocatalytic production of hydrogen peroxide (H2O2 has already attracted the interest of many researchers due to its environmental sustainability. Nevertheless, the inherent drawbacks of g‐C3N4 limit its progress. Metal‐free modification strategies, including nanostructure design, defect introduction, doping, and heterojunction construction, have been developed to improve the efficiency of g‐C3N4 photocatalytic H2O2 production. Compared to metal modification, metal‐free strategies avoid the use of precious metals and the leaching of heavy metal ions, which have the advantages of good stability and environmental friendliness. However, a comprehensive review of H2O2 production from g‐C3N4 modified by metal‐free strategies is still lacking. This review first recaps the mechanism of photocatalytic H2O2 production by g‐C3N4, including photoexcitation, carrier separation and redox reactions. Then, the perspective advances in metal‐free modified g‐C3N4 photocatalysts are presented, with the special focus on the kernel connection between different strategies and mechanism based on the pivotal stages of H2O2 production. Subsequently, recent applications of g‐C3N4‐based photocatalysts for in situ generated H2O2, mainly including water purification and organic synthesis, are briefly discussed. Finally, the prospects of g‐C3N4‐based photocatalysts are envisioned with the hope that it will have “something to do” in the field of H2O2 production.

Revisiting azimuthal angular asymmetries in diffractive di-jet production

We explore the impact of initial state soft gluon radiations on the azimuthal angle asymmetries in photo-production of hard di-jet via coherent diffraction in ultraperipheral heavy ion collisions, as well as in electron-proton (ep) and electron-nucleus (eA) collisions. The primary production mechanism is identified as the diffractive production of two hard jets, accompanied by a collinear gluon emission along the beam direction. In contrast, the diffractive exclusive di-jet production, where the initial state radiation is absent, is suppressed due to color transparency. Our analysis shows that azimuthal asymmetries, traditionally attributed to final state gluon emissions, are reduced by the presence of initial state radiations. The sensitivity of azimuthal asymmetries to both initial and final state radiations suggests that they could provide novel insights into the mechanisms of di-jet production in diffractive processes.

Investigation of decay mechanisms and associated aspects of exotic Nobeliumisotopes using the Skyrme energy density formalism

Abstract Persistent theoretical and experimental attempts have been made to investigate the
heavy ion induced reactions and their subsequent decay mechanisms in superheavy mass region.
In addition, the region of transfermium elements is itself of great interest because of the neutron
/ proton shell effects. Here, we aim to study the subsequent decay mechanisms of two isotopes of
Z = 102 nucleus, i.e. 248No and 250No.
The dynamical cluster-decay model (DCM) based on Quantum Mechanical Fragmen-
tation Theory (QMFT), is employed to conduct a comprehensive analysis of compound nucleus
(CN) and non-compound nucleus (nCN) mechanisms such as fusion-fission (ff), Quasi fission (QF)
and fast fission (FF), the role of centre of mass energy (Ec.m.) and angular momentum (ℓ) for
248No and 250No isotopes. The nuclear interaction potential is obtained using the Skyrme energy
density formalism (SEDF) in the domain of GSkI force parameters. The probability of compound nucleus formation
(PCN ) is determined using a function that depends on the centre of mass energy. The lifetimes for
the fusion-fission (ff) quasi fission (QF) channels are explored.
Here, CN and nCN decay mechanisms for two isotopes of Z = 102 nobelium are studied
over the wide range of centre-of-mass (Ec.m.) by including the quadrupole deformation (β2) and
optimum orientations (θopt.) of decaying fragments. The fragmentation potential, preformation
probability, neck length parameter and reaction cross-sections are explored. Further, the calcula-
tions are done for PCN in order to identify the decay modes of 248No and 250No isotopes. The
fusion-fission lifetimes and quasi fission lifetimes are compared with the dinuclear system (DNS)
approach. The most probable fragments such as 122Sn and 128T e are observed near to the magic shell closure Z = 50 and
N = 82. The ff and qf lifetime decreases with increase in the excitation energy.

Ex Situ Stabilization/Solidification Approaches of Marine Sediments Using Green Cement Admixtures

The routine dredging of waterways produces huge volumes of sediments. Handling contaminated dredged sediments poses significant and diverse challenges around the world. In recent years, novel and sustainable ex situ remediation technologies for contaminated sediments have been developed and applied. This review article focuses on cement-based binders in stabilizing contaminants through the stabilization/solidification (S/S) technique and the utilization of contaminated sediments as a resource. Through S/S techniques, heavy metals can be solidified and stabilized in dense and durable solid matrices, reducing their permeability and restricting their release into the environment. Industrial by-products like red mud (RM), soda residue (SR), pulverized fly ash (PFA), and alkaline granulated blast furnace slag (GGBS) can immobilize heavy metal ions such as lead, zinc, cadmium, copper, and chromium by precipitation. However, in a strong alkali environment, certain heavy metal ions might dissolve again. To address this, immobilization in low pH media can be achieved using materials like GGBS, metakaolin (MK), and incinerated sewage sludge ash (ISSA). Additionally, heavy metals can be also immobilized through the formation of silicate gels and ettringites during pozzolanic reactions by mechanisms such as adsorption, ion exchanges, and encapsulation. It is foreseeable that, in the future, the scientific community will increasingly turn towards multidisciplinary studies on novel materials, also after an evaluation of the effects on long-term heavy metal stabilization.

Emulsion liquid membrane (ELM) enhanced by nanoparticles and ionic liquid for extracting vanadium ions from wastewater.

Emulsion liquid membrane (ELM) stands out as an extraction process that has drawn much attention due to its promising prospects in industrial wastewater treatment technology. Nevertheless, the pivotal challenge is to reach high membrane stability to overcome the obstacle of applying ELM at the industrial scale. In this study, ELM was boosted by using nanoparticles (superparamagnetic iron oxide (Fe2O3)) in the stripping phase (W1) and ionic liquid (1-methyl-3-octyl-imidazolium-hexafluorophosphate [OMIM][PF6) in the oil phase (O) for recovering/extracting vanadium from synthetic wastewater to near completion and at the same time enhancing emulsion stability to be appropriate for industrial application. The vanadium recovery/extraction percentage has been raised significantly in 3min to 99.6% when adding 0.01% (w/w) Fe2O3 NPs (20 to 50nm in size) in the internal phase (W1) and 5% (v/v) [OMIM]PF6 ionic liquid in the oil phase (O). Also, the emulsion stability was considerably improved, and the leakage percentage was reduced to 16% after 3days. The results of this study could be used in the future to remove additional heavy metal ions from industrial effluents.

Multifunctional bacterial cellulose-bentonite@polyethylenimine composite membranes for enhanced water treatment: Sustainable dyes and metal ions adsorption and antibacterial properties

Developing multifunctional materials for water treatment remains a significant challenge. Bacterial cellulose (BC) holds immense potential as an adsorbent with high pollutant-binding capacity, hydrophilicity, and biosafety. In this study, N-acetylglucosamine was used as a carbon source to ferment BC, incorporating amide bonds in situ. Bentonite, renowned for its adsorption properties, was added to the culture medium, resulting in BC-bentonite composite membranes via a one-step fermentation process. Polyethyleneimine (PEI) was crosslinked with amide bonds on the membrane via glutaraldehyde through Schiff base reactions to enhance the performance of the composite membrane. The obtained membrane exhibited increased hydrophilicity, enhanced active adsorption sites, and enlarged specific surface area. It not only physically adsorbed contaminants through its unique structure but also effectively captured dye molecules (Congo red, Methylene blue, Malachite green) via electrostatic interactions. Additionally, it formed stable complexes with metal ions (Cd²⁺, Pb²⁺, Cu²⁺) through coordination and effectively adsorbed their mixtures. Moreover, the composite membrane demonstrated the broad-spectrum antibacterial activity, effectively inhibiting the growth of tested bacteria. This study introduces an innovative method for fabricating composite membranes as adsorbents for complex water pollutants, showing significant potential for long-term wastewater treatment of organic dyes, heavy metal ions, and pathogens.

The QCD phase diagram and Beam Energy Scan physics: A theory overview

We review recent theoretical developments relevant to heavy-ion experiments carried out within the Beam Energy Scan program at the Relativistic Heavy Ion Collider. Our main focus is on the description of the dynamics of systems created in heavy-ion collisions and establishing the necessary connection between the experimental observables and the QCD phase diagram.

Adsorption of heavy metal ions by carbon-based adsorbent using magnetic nitrogen-doped carbon and graphene oxide

ABSTRACT The adsorption of weighty metal particles from contaminated water sources has garnered significant attention due to its critical role in environmental remediation and ensuring safe drinking water. Heavy metal ions can be removed from water using conventional adsorbents such as activated zeolites; however, these materials have low absorption and slow kinetics. To solve these issues, carbon-based adsorbents that exhibit easy synthesis, high porosity, design ability, and stability have been proposed. In this review, a carbon-based adsorbent, named M-NC, and graphene oxide were created for the particular evacuation of weighty metal particles. To increase the potential for Heavy Metals (HM) immobilization, sulfide-modified biochar was created via a process called synchronous carbon layer epitome. A hypothetical physicochemical and thermodynamic examination of the adsorption of weighty metals Zn2+, Cd2+, Ni2+, Ag2+, Pb2+ and Cu2+ on carbon-based adsorbents was done with factual material science fundaments. The biochar with large surface areas is utilized to eliminate weighty metal particles, quite possibly the most significant heavy metal pollutants, from aqueous solutions. The limit of the adsorbent for eliminating weighty metal ions was concentrated on utilizing Langmuir adsorption isotherm under ultrasound-helped conditions. The Mesoporous Silica Nanoparticles (MNCs) can be applied to the Langmuir model and pseudo-second-order kinetics. It is possible to use the Langmuir and second-order kinetic equations to accurately explain the adsorption method. Thermodynamic limitations were also envisioned because sorption is exothermic when it happens spontaneously. A homogeneous measurable physical science adsorption typically was utilized to describe and analyze the experimental heavy metal removal isotherms at 30°C and pH5 utilizing adsorbents produced by pyrolysis of biomasses (broccoli stalks). The experimental results were investigated in terms of Langmuir and pseudo-2nd-order kinetic equations, Freundlich and isotherm models. The outcome of pH, initial heavy metal ion concentration, contact time, and adsorbent dosage regarding the adsorption capacity and removal efficiency of Pb2+ and Cd2+ on the hydrogel was examined. This study contributes to the advancement of information in the ground of environmentally friendly heavy metal removal techniques, specifically focusing on the usage of biomass-based adsorbents. These findings have the potential to address the need for effective solutions in water purification and environmental cleanup efforts.

Advances in field-effect tube biosensors constructed on silicon nanowires, graphene and carbon nanotubes for heavy metal ion detection

Advances in field-effect tube biosensors constructed on silicon nanowires, graphene and carbon nanotubes for heavy metal ion detection

Green modified electrode for sensitive simultaneous heavy metal ions electrodetection

The detection of heavy metals (HM) is of particular importance in terms of human health and environmental protection. Electrochemical sensors are usually limited by the interference of various cations that coexist in real samples. These shortcomings are usually solved by incorporating various particles into the electrode material, which represents another source of pollution, thus being unsustainable. In this study, it was demonstrated that the new investigated natural clay (nc), used without processing, and immobilized with chitosan (Chi) matrix on the surface of a GCE in order to obtain nc-Chi/GCE modified electrode can detect, separately and simultaneously, four heavy metals (i.e. Zn2+, Cd2+, Pb2+ and Cu2+). The electrochemical behavior of the new eco-friendly modified electrode and its capacity to detect heavy metals has been investigated by electrochemical impedance spectroscopy (EIS) and square wave anodic stripping voltammetry (SWASV). The obtained electroanalytical performances (i.e., a detection limit of 43.1 nM for Zn2+, 19.1 nM for Cd2+, 4.3 nM for Pb2+ and 57.3 nM for Cu2+) corroborated with the reproducibility and stability of the modified electrode successfully recommends it as a suited device for heavy metals ions detection. The nc-Chi/GCE modified electrode was validated by measurements performed in real samples of tap water.

Deep learning-based voxel sampling for particle therapy treatment planning

Objective. Scanned particle therapy often requires complex treatment plans, robust optimization, as well as treatment adaptation. Plan optimization is especially complicated for heavy ions due to the variable relative biological effectiveness. We present a novel deep-learning model to select a subset of voxels in the planning process thus reducing the planning problem size for improved computational efficiency. Approach. Using only a subset of the voxels in target and organs at risk (OARs) we produced high-quality treatment plans, but heuristic selection strategies require manual input. We designed a deep-learning model based on P-Net to obtain an optimal voxel sampling without relying on patient-specific user input. A cohort of 70 head and neck patients that received carbon ion therapy was used for model training (50), validation (10) and testing (10). For training, a total of 12 500 carbon ion plans were optimized, using a highly efficient artificial intelligence (AI) infrastructure implemented into a research treatment planning platform. A custom loss function increased sampling density in underdosed regions, while aiming to reduce the total number of voxels. Main results. On the test dataset, the number of voxels in the optimization could be reduced by 84.8% (median) at <1% median loss in plan quality. When the model was trained to reduce sampling in the target only while keeping all voxels in OARs, a median reduction up to 71.6% was achieved, with 0.5% loss in the plan quality. The optimization time was reduced by a factor of 7.5 for the total AI selection model and a factor of 3.7 for the model with only target selection. Significance. The novel deep-learning voxel sampling technique achieves a significant reduction in computational time with a negligible loss in the plan quality. The reduction in optimization time can be especially useful for future real-time adaptation strategies.

Research of single-event burnout in vertical Ga2O3 FinFET by low carrier lifetime control

This paper presents the 2D simulations of single-event burnout (SEB) in vertical enhancement-mode gallium oxide (Ga2O3) fin-shaped channels field-effect transistor (FinFET) by low carrier lifetime control (LCLC) method. The correctness of the structure parameters and simulated physical models are verified by the basic electrical characteristics in experiments. The SEB simulations show that the most sensitive region to heavy ion is the narrow channel region. The SEB failure is due to the diffusion of a large number of electron–hole pairs induced by heavy ion into a strong electric field region, resulting in a large transient current density to cause the thermal failure. Afterwards, the influences of the narrow channel region width on basic characteristics and SEB performance are discussed. Then, the SEB hardening mechanism of LCLC is studied that the electric field peak in the top of the structure can be effectively reduced, and the transient current caused by second avalanche is restrained. In addition, the basic characteristics with LCLC are proved to be hardly influenced in Ga2O3 FinFET. Finally, the carrier lifetime value and local control region are studied that the SEB hardening performance can be significantly improved by a large enough control area with a low carrier lifetime.

Insight on photocatalytic synchronous oxidation and reduction for pollutant removal: Chemical energy conversion between macromolecular organic pollutants and heavy metal

Collaborative treatment of pollutants is a promising approach for wastewater treatment. In this work, a covalent organic framework material (COFs) with an imine structure was synthesised by the Schiff base reaction, and photochemical tests showed good photochemical effects. It was used to explore the photocatalytic treatment of co-existing pollutants (heavy metal ions and antibiotics) and the performance of treating co-existing wastewater was investigated. The degradation performance of levofloxacin (LVX) and Cr(VI) was improved in the coexisting pollutants system, with the LVX degradation being 4.2 times more effective than that of the LVX solitary system. Moreover, this phenomenon was also observed in LVX/Ag(I), LVX/Fe(III), sulfadiazine/Cr(VI), norfloxacin/Cr(VI) and tetracycline/Cr(VI) systems. The analysis of active species suggesting that the synergistic promotion of photocatalytic oxidation-reduction systems was not only promoting from the improvement of simple charge separation, but it was also found that high-valent metal species can act directly in the oxidative decomposition of antibiotics. The interaction of pollutants and intermediates were rationally exploited and confirmed by control experiments and theoretical calculation. This conclusion helps us to re-examine the underlying mechanisms of photocatalytic synchronous oxidation and reduction reactions, simultaneously beneficial for the development of mixed pollutant control processes.

Disclosing the influence mechanism of facet-dependent pyrite photo-activation and photo-dissolution processes on the reduction of Cr(VI)

The photo-activation and photo-dissolution processes of pyrite (FeS2) can affect the environmental behavior of the co-existing hexavalent chromium (Cr(VI)). But the photochemical performance of FeS2 is intimately dependent on its exposed facets. Herein, FeS2 nanosheets (FeS2 NS) and FeS2 nanocubes (FeS2 NC) with the dominant exposed facets of (001) and (210)/(100) respectively are prepared. The more Fe3+, Fe2+, and SO42- are released in the FeS2 NS system than the other system due to its more excellent generation ability of photogenerated electrons and reactive oxygen species. The higher surface energy on (001) facet leads to the faster dissolution rate of FeS2 NS. Due to the optimal production ability of photogenerated electrons and Fe2+ of (001) facet, the much higher Cr(VI) elimination efficiency in the FeS2 NS system is observed than that in the FeS2 NC (72.8%) system within 120 min. This work could help to unveil the influence of FeS2 on the fate of Cr(VI) in surface environment, and offer a theoretical support to clarify the influence of heavy metal ions on the iron sulfide minerals.

Heavy metal removal performance of capacitive deionization technology studied by machine learning

Capacitive deionization (CDI) technology is utilized for efficient treatment of industrial wastewater, characterized by low energy consumption and environmental protection. In order to comprehend the correlation between key experimental parameters and the electrosorption capacity (EC) of heavy metals in CDI technology, this paper employs a genetic algorithm (GA) to optimize a backpropagation artificial neural network (BPANN) for predicting the EC of CDI technology for heavy metal ions, with the characteristics of electrode materials converted into numerical characteristics for further analysis. Compared to the BPANN, the optimized GABPANN model demonstrates superior predictive accuracy. It achieves automatic adjustment of the hidden layer structure, neuron count, and transfer functions. Furthermore, the grey relational analysis indicates that the electrode material and the initial pH value of the solution are pivotal in determining the EC of heavy metal ions. This underscores the efficacy of machine learning (ML) algorithms in forecasting the nonlinear dynamics of CDI systems and elucidates the influence of individual parameters on the efficacy of heavy metal removal.