In 1991, I published in this journal estimates of the percentage of new products and processes based on recent academic research—that is, academic research occurring within 15 years of the commercialization of whatever innovation is being considered— in the drug and medical product, information processing, chemical, electrical, instruments, metals, and Ž . oil industries in 1975–1985 Mansfield, 1991, 1992 . Because there has been considerable interest in such estimates , I have gathered similar data from a sample of 77 major firms for 1986–1994, the only significant difference in the sample design being that the machinery industry, which is reasonably active in this regard, has been substituted for oil. 3 Table 1 shows that the overall results for 1986– 1994 are very similar to those for 1975–1985, although particular industries sometimes vary substantially, as one might expect. The industry means in
Md. Atikur Rahman, Promit Debnath, Md. Tanvir Hossain
et al.
This study presents CdS and ZnS nanoparticles as multifunctional photocatalysts for simultaneous degradation of fluoroquinolone antibiotics (ciprofloxacin and levofloxacin) and Congo red dye with concurrent antimicrobial activity under visible-light irradiation. Nanoparticles synthesized via chemical precipitation exhibited cubic zinc-blende structures with crystallite sizes of 2.1 -2.6 nm (CdS) and 23.5-31.3 nm (ZnS), confirmed by XRD analysis. FTIR spectroscopy revealed metal-sulfur lattice vibrations at 632 cm-1 (Cd-S) and 650 cm-1 (Zn-S), while EDX confirmed stoichiometric composition (CdS: 75.01 wt% Cd, 24.99 wt% S). Williamson-Hall analysis indicated microstrain values of 1.98-7.77 × 10-3 for CdS and 4.42-5.89 × 10-2 for ZnS, suggesting moderate lattice distortion. CdS demonstrated superior photocatalytic performance attributed to its optimal bandgap and point of zero charge (PZC ≈ 6.0), achieving near-complete degradation of target pollutants through enhanced reactive oxygen species generation. Antimicrobial assays revealed CdS exhibited broad-spectrum activity against S.aureus (9.3±0.36 mm) and S.abony (8.3±0.42 mm), while ZnS showed limited activity only against S.abony (9.5±0.50 mm). Both materials remained inactive against L. monocytogenes, E. coli and Candida albicans (<6 mm). The superior multifunctional performance of CdS, combining efficient visible-light photocatalysis with selective antimicrobial activity, establishes it as a promising single-material solution for next-generation water treatment systems addressing pharmaceutical contamination and microbial threats in aquatic environments.
Traditional coal quality assessment methods rely exclusively on the laboratory testing of physical samples, which impedes detailed stratigraphic evaluation and limits the integration of intelligent precision mining technologies. To resolve this challenge, this study investigates geophysical logging as an innovative method for coal quality prediction. By integrating scanning electron microscopy (SEM), X-ray analysis, and optical microscopy with interdisciplinary methodologies spanning mathematics, mineralogy, and applied geophysics, this research analyzes the coal quality and mineral composition of the Shanxi Formation coal seams in northern Jiangsu, China. A predictive model linking geophysical logging responses to coal quality parameters was established to delineate relationships between subsurface geophysical data and material properties. The results demonstrate that the Shanxi Formation coals are gas coal (a medium-metamorphic bituminous subclass) characterized by low sulfur content, low ash yield, low fixed carbon, high volatile matter, and high calorific value. Mineralogical analysis identifies calcite, pyrite, and clay minerals as the dominant constituents. Pyrite occurs in diverse microscopic forms, including euhedral and semi-euhedral fine grains, fissure-filling aggregates, irregular blocky structures, framboidal clusters, and disseminated particles. Systematic relationships were observed between logging parameters and coal quality: moisture, ash content, and volatile matter exhibit an initial decrease, followed by an increase with rising apparent resistivity (LLD) and bulk density (DEN). Conversely, fixed carbon and calorific value display an inverse trend, peaking at intermediate LLD/DEN values before declining. Total sulfur increases with density up to a threshold before decreasing, while showing a concave upward relationship with resistivity. Negative correlations exist between moisture, fixed carbon, calorific value lateral resistivity (LLS), natural gamma (GR), short-spaced gamma-gamma (SSGG), and acoustic transit time (AC). In contrast, ash yield, volatile matter, and total sulfur correlate positively with these logging parameters. These trends are governed by coalification processes, lithotype composition, reservoir physical properties, and the types and mass fractions of minerals. Validation through independent two-sample <i>t</i>-tests confirms the feasibility of the neural network model for predicting coal quality parameters from geophysical logging data. The predictive model provides technical and theoretical support for advancing intelligent coal mining practices and optimizing efficiency in coal chemical industries, enabling real-time subsurface characterization to facilitate precision resource extraction.
The rapid growth of aluminum and graphite industries has generated substantial stockpiles of red mud and graphite tailings, which pose environmental risks due to their high heavy metal content and potential for soil and water contamination. This study investigated the leaching behavior of heavy metals from these materials post-stabilization using cement and a sulfonated oil-based ion curing agent, thereby evaluating their suitability for safe reuse. Semi-dynamic leaching experiments were employed to measure heavy metal release, supplemented by kinetic modeling to discern key leaching mechanisms. The findings indicated that the heavy metal concentrations in leachates were consistently below regulatory standards, with leaching dynamics influenced by dual mechanisms: the diffusion of ions and surface chemical reactions. A diffusion coefficient-based analysis further suggested low leachability indices for all metals, confirming effective immobilization. These results suggest that cement and curing agent-stabilized red mud–graphite tailing composites reduce environmental risks and possess characteristics favorable for resource recovery, thus supporting their sustainable use in industrial applications.
Chandrasekhar Gokavarapu, Venkata Rao Kaviti, Srinivasa Rao Thirunagari
et al.
Chemical systems are traditionally described by lists of species, reactions, and externally imposed kinetic laws, a framework that lacks an intrinsic algebraic structure governing how transformations compose. We propose an axiomatic reformulation in which a chemical system is modelled as a ternary Gamma semiring (TGS), where chemical states form an additive semigroup, mediators encode catalytic or environmental context, and mediated transformations are represented by a ternary operation. We show that the TGS axioms admit direct physical interpretations: distributivity corresponds to ideal, non-interfering parallel reactions, while associativity characterizes thermodynamic path-independence. Classical systems including Michaelis-Menten kinetics, global equilibrium, and allosteric regulation are recovered as different algebraic regimes, and we develop operational tests that quantify departures from the axioms through experimentally measurable indices. The resulting framework unifies equilibrium, kinetics, regulation, and chemical computation within a single algebraic language, offering new principles for the analysis and design of responsive or self-regulating materials.
Masahiro Fukuda, Masato Senami, Yoshiaki Sugimoto
et al.
We propose a local regional chemical potential (RCP) analysis method based on an energy window scheme to quantitatively estimate the selectivity of atomic and molecular adsorption on surfaces, as well as the strength of chemical bonding forces between a probe tip and a surface in atomic force microscopy (AFM) measurements. In particular, focusing on the local picture of covalent bonding, we use a simple H$_2$ molecular model to demonstrate a clear relationship between chemical bonding forces and the local RCP. Moreover, density functional theory calculations on molecular systems and diamond C(001) surfaces reveal that the local RCP at the surfaces successfully visualizes electron-donating regions such as dangling bonds and double bonds. These results suggest that the local RCP can serve as an effective measure to analyze high-resolution non-contact or near-contact AFM images enhanced by chemical bonding forces.
Sumedha M. Amaraweera, C. Gunathilake, O. H. P. Gunawardene
et al.
Starch is one of the most common biodegradable polymers found in nature, and it is widely utilized in the food and beverage, bioplastic industry, paper industry, textile, and biofuel industries. Starch has received significant attention due to its environmental benignity, easy fabrication, relative abundance, non-toxicity, and biodegradability. However, native starch cannot be directly used due to its poor thermo-mechanical properties and higher water absorptivity. Therefore, native starch needs to be modified before its use. Major starch modification techniques include genetic, enzymatic, physical, and chemical. Among those, chemical modification techniques are widely employed in industries. This review presents comprehensive coverage of chemical starch modification techniques and genetic, enzymatic, and physical methods developed over the past few years. In addition, the current applications of chemically modified starch in the fields of packaging, adhesives, pharmaceuticals, agriculture, superabsorbent and wastewater treatment have also been discussed.
Marc Bohner, Fabrizio Bigolin, Isabelle Bohner
et al.
α-tricalcium phosphate (α-TCP) is the most widespread raw material for hydraulic calcium phosphate cements (CPCs). CPCs are widely used in bone repair due to their injectability, setting ability, and osteoconductivity. This study investigated the reactivity of α-TCP powders, focusing on the impact of minor phase impurities, β-calcium pyrophosphate and hydroxyapatite, and the synthesis temperature. The α-TCP powders were synthesized via a solid-state reaction of calcium carbonate and anhydrous dicalcium phosphate, with varying Ca/P molar ratios (1.4850–1.5075) and synthesis temperatures (1175°C–1350 °C). Powders produced with a Ca/P molar ratio below 1.50 and synthesized at a temperature above the melting point of β-CPP (1296 °C) had a broader size distribution and a two to fourfold lower hydraulic reactivity. Conversely, a higher Ca/P molar ratio improved reactivity. The study underscores the importance of precise control over synthesis parameters to enhance the performance of α-TCP-based CPCs, offering insights for optimizing material design in biomedical applications.
This study analyzes the consequences of first-order chemical reactions, radiation, and viscous dissipation on the unsteady magnetohydrodynamic natural convective flow of a viscous incompressible fluid over a vertically positioned semi-boundless oscillating plate with uniform mass diffusion and temperature. An implicit finite-difference technique is employed to solve a set of dimensionless, coupled, nonlinear partial differential equations. The numerical results for fluid velocity, concentration, and temperature at the plate under different dimensionless parameters are graphically displayed. Due to first-order homogeneous chemical reactions, it has been discovered that the velocity rises at the time of a generative reaction and drops during a destructive reaction. A decline in velocity is observed with an increase in the phase angle, radiation parameter, and chemical reaction parameter. Further, it has been revealed that plate oscillation, radiation, chemical reactions, and the magnetic field significantly influence the flow behavior.
Badreddine Ayadi, Kaouther Ghachem, Kamel Al-Khaled
et al.
The advances in nanotechnology led to the development of new kinds of engineered fluids called nanofluids. Nanofluids have several industrial and engineering applications, such as solar energy systems, heat conduction processes, nuclear systems, chemical processes, etc. The motivation of the present work is to analyze and explore the thermal and dynamic behaviors of a non-Newtonian fluid flow under time retardation effects. The flow is unsteady and caused by a bidirectional, periodically moving surface. In addition to the convective heat transfer and fluid flow, the radiation and chemical reactions have also been considered. The governing equations are established based on the modified Cattaneo–Christov heat flux formulation. It was found that the bidirectional velocities oscillate periodically, and that the magnitude of the oscillation increases with the retardation time. Higher temperatures occur when the porosity parameter is increased, and lower concentrations are encountered for higher values of the concentration relaxation parameter. The current results can be applied in thermal systems, heat transfer enhancement, chemical synthesis, solar systems, power generation, medical applications, the automotive industry, process industries, refrigeration, etc.
The article considers regional development trends in the context of economic activity and price processes, shows data on material well-being of families in Russian regions, and presents the ratings of the Russian regions by dynamics of wages and family welfare. The dynamics of sectoral production (agro-industrial complex, logging and wood processing, extractive industry, oil and oil products transshipment, chemical industry, motor transport, marine transportation, furniture production, construction materials, housing construction, machine building, shipbuilding, tourism, and education) in the Russian regions has been shown, and diffrentiation of regions by industries development revealed. The dynamics of consumer demand has been presented and main factors affcting consumer activity from the cost of living crisis and escapism manifested in diffrent forms revealed. A signifiant trend is also a decrease in concentrating attention. Main trends in online commerce development in Russia have been shown as it has been growing in 2022 even against the background of general decline in consumer demand. These trends include orientation of most players to sustainable development and ethics: increasing market share and capitalization, as well as reducing concentration of activities on profi. Global and local factors of consumer goods sales development in the Internet have been identifid.
Homa Hosseinzadeh-Bandbafha, Hamed Kazemi Shariat Panahi, Mona Dehhaghi
et al.
Sustainable socio-economic development largely depends on the sustainability of the energy supply from economic, environmental, and public health perspectives. Fossil fuel combustion only meets the first element of this equation and is hence rendered unsustainable. Biofuels are advantageous from a public health perspective, but their environmental and economic sustainability might be questioned considering the conflicts surrounding their feedstocks, including land use change and fuel vs. food conflict. Therefore, it is imperative to put more effort into addressing the downsides of biofuel production using advanced technologies, such as nanotechnology. In light of that, this review strives to scrutinize the latest developments in the application of nanotechnology in producing biodiesel, a promising alternative to fossil diesel with proven environmental and health benefits. The main focus is placed on nanotechnology applications in the feedstock production stage. First, the latest findings concerning the application of nanomaterials as nanofertilizers and nanopesticides to improve the performance of oil crops are presented and critically discussed. Then, the most promising results reported recently on applying nanotechnology to boost biomass and oil production by microalgae and facilitating microalgae harvesting are reviewed and mechanistically explained. Finally, the promises held by nanomaterials to enhance animal fat production in livestock, poultry, and aquaculture systems are elaborated. Despite the favorable features of using nanotechnology in biodiesel feedstock production, the presence of nanoparticles in living systems is also associated with important health and environmental challenges, which are critically covered and discussed in this work.
Fuel, Energy industries. Energy policy. Fuel trade
Shesha Gopal Marehalli Srinivas, Matteo Polettini, Massimiliano Esposito
et al.
Stochastic chemical processes are described by the chemical master equation satisfying the law of mass-action. We first ask whether the dual master equation, which has the same steady state as the chemical master equation, but with inverted reaction currents, satisfies the law of mass-action, namely, still describes a chemical process. We prove that the answer depends on the topological property of the underlying chemical reaction network known as deficiency. The answer is yes only for deficiency-zero networks. It is no for all other networks, implying that their steady-state currents cannot be inverted by controlling the kinetic constants of the reactions. Hence, the network deficiency imposes a form of non-invertibility to the chemical dynamics. We then ask whether catalytic chemical networks are deficiency-zero. We prove that the answer is no when they are driven out of equilibrium due to the exchange of some species with the environment.
Tsuyoshi Mizohata, Tetsuya J. Kobayashi, Louis-S. Bouchard
et al.
We investigate the dynamics of chemical reaction networks (CRNs) with the goal of deriving an upper bound on their reaction rates. This task is challenging due to the nonlinear nature and discrete structure inherent in CRNs. To address this, we employ an information geometric approach, using the natural gradient, to develop a nonlinear system that yields an upper bound for CRN dynamics. We validate our approach through numerical simulations, demonstrating faster convergence in a specific class of CRNs. This class is characterized by the number of chemicals, the maximum value of stoichiometric coefficients of the chemical reactions, and the number of reactions. We also compare our method to a conventional approach, showing that the latter cannot provide an upper bound on reaction rates of CRNs. While our study focuses on CRNs, the ubiquity of hypergraphs in fields from natural sciences to engineering suggests that our method may find broader applications, including in information science.
Laura Sisson, Aryan Amit Barsainyan, Mrityunjay Sharma
et al.
The application of deep learning techniques on aroma-chemicals has resulted in models more accurate than human experts at predicting olfactory qualities. However, public research in this domain has been limited to predicting the qualities of single molecules, whereas in industry applications, perfumers and food scientists are often concerned with blends of many molecules. In this paper, we apply both existing and novel approaches to a dataset we gathered consisting of labeled pairs of molecules. We present graph neural network models capable of accurately predicting the odor qualities arising from blends of aroma-chemicals, with an analysis of how variations in architecture can lead to significant differences in predictive power.