We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.
Abstract Discovery of graphene and its astonishing properties have given birth to a new class of materials known as “2D materials”. Motivated by the success of graphene, alternative layered and non-layered 2D materials have become the focus of intense research due to their unique physical and chemical properties. Origin of these properties ascribed to the dimensionality effect and modulation in their band structure. This review highlights the recent progress of the state-of-the-art research on synthesis, characterization and isolation of single and few layer nanosheets and their assembly. Electronic, magnetic, optical and mechanical properties of 2D materials have also been reviewed for their emerging applications in the area of catalysis, electronic, optoelectronic and spintronic devices; sensors, high performance electrodes and nanocomposites. Finally this review concludes with a future prospective to guide this fast evolving class of 2D materials in next generation materials science.
Reverse osmosis (RO) is currently the most important desalination technology and it is experiencing significant growth. The objective of this paper is to review the historical and current development of RO membrane materials which are the key determinants of separation performance and water productivity, and hence to define performance targets for those who are developing new RO membrane materials. The chemistry, synthesis mechanism(s) and desalination performance of various RO membranes are discussed from the point of view of membrane materials science. The review starts with the first generation of asymmetric polymeric membranes and finishes with current proposals for nano-structured membrane materials. The paper provides an overview of RO performance in relation to membrane materials and methods of synthesis. To date polymeric membranes have dominated the RO desalination industry. From the late 1950s to the 1980s the research effort focussed on the search for optimum polymeric membrane materials. In subsequent decades the performance of RO membranes has been optimised via control of membrane formation reactions, and the use of poly-condensation catalysts and additives. The performance of state-of-the-art RO membranes has been highlighted. Nevertheless, the advances in membrane permselectivity in the past decade has been relatively slow, and membrane fouling remains a severe problem. The emergence of nano-technology in membrane materials science could offer an attractive alternative to polymeric materials. Hence nano-structured membranes are discussed in this review including zeolite membranes, thin film nano-composite membranes, carbon nano-tube membranes, and biomimetic membranes. It is proposed that these novel materials represent the most likely opportunities for enhanced RO desalination performance in the future, but that a number of challenges remain with regard to their practical implementation.
Molecular science entails the study of structures and properties of materials at the level of single molecules or small interacting complexes of molecules. Moving beyond single molecules and well‐defined complexes, aggregates (i.e., irregular clusters of many molecules) serve as a particularly useful form of materials that often display modified or wholly new properties compared to their molecular components. Some unique structures and phenomena such as polymorphic aggregates, aggregation‐induced symmetry breaking, and cluster excitons are only identified in aggregates, as a few examples of their exotic features. Here, by virtue of the flourishing research on aggregation‐induced emission, the concept of “aggregate science” is put forward to fill the gaps between molecules and aggregates. Structures and properties on the aggregate scale are also systematically summarized. The structure–property relationships established for aggregates are expected to contribute to new materials and technological development. Ultimately, aggregate science may become an interdisciplinary research field and serves as a general platform for academic research.
Membrane technology has gained great interest in industrial separation processing over the past few decades owing to its high energy efficiency, small capital investment, environmentally benign characteristics, and the continuous operation process. Among various types of membranes, mixed matrix membranes (MMMs) combining the merits of the polymer matrix and inorganic/organic fillers have been extensively investigated. With the rapid development of chemistry and materials science, recent studies have shifted toward the design and application of advanced porous materials as promising fillers to boost the separation performance of MMMs. Here, first a comprehensive overview is provided on the choices of advanced porous materials recently adopted in MMMs, including metal–organic frameworks, porous organic frameworks, and porous molecular compounds. Novel trends in MMMs induced by these advanced porous fillers are discussed in detail, followed by a summary of applying these MMMs for gas and liquid separations. Finally, a concise conclusion and current challenges toward the industrial implementation of MMMs are outlined, hoping to provide guidance for the design of high‐performance membranes to meet the urgent needs of clean energy and environmental sustainability.
The accuracy and efficiency of electronic-structure methods to understand, predict and design the properties of materials has driven a new paradigm in research. Simulations can greatly accelerate the identification, characterization and optimization of materials, with this acceleration driven by continuous progress in theory, algorithms and hardware, and by adaptation of concepts and tools from computer science. Nevertheless, the capability to identify and characterize materials relies on the predictive accuracy of the underlying physical descriptions, and on the ability to capture the complexity of realistic systems. We provide here an overview of electronic-structure methods, of their application to the prediction of materials properties, and of the different strategies employed towards the broader goals of materials design and discovery. Simulations can be used to accelerate the characterization and discovery of materials. Here we Review how electronic-structure methods such as density functional theory work, what properties they can be used to predict and how they can be used to design materials.
Nanocellulose is currently in the limelight of extensive research from fundamental science to technological applications owing to its renewable and carbon‐neutral nature, superior biocompatibility, tailorable surface chemistry, and unprecedented optical and mechanical properties. Herein, an up‐to‐date account of the recent advancements in nanocellulose‐derived functional materials and their emerging applications in areas of chiral photonics, soft actuators, energy storage, and biomedical science is provided. The fundamental design and synthesis strategies for nanocellulose‐based functional materials are discussed. Their unique properties, underlying mechanisms, and potential applications are highlighted. Finally, this review provides a brief conclusion and elucidates both the challenges and opportunities of the intriguing nanocellulose‐based technologies rooted in materials and chemistry science. This review is expected to provide new insights for nanocellulose‐based chiral photonics, soft robotics, advanced energy, and novel biomedical technologies, and promote the rapid development of these highly interdisciplinary fields, including nanotechnology, nanoscience, biology, physics, synthetic chemistry, materials science, and device engineering.
The accurate determination of residual stresses has a crucial role in understanding the complex interactions between microstructure, mechanical state, mode(s) of failure, and structural integrity. Moreover, the residual stress management concept contributes to industrial applications, aiming to improve the product's service performance and life cycle. In this regard, the industry requests rapid, efficient, and modern methods to identify and control the residual stress state. This review article contains three main sections. The first section covers different residual stress determination methods and reports the advancements over the recent decade. The second section includes the role of residual stresses in the performance of a broad range of materials including metallic alloys, polymers, ceramics, composites, and biomaterials. This is presented by classifying different science areas dealing with residual stresses into two main groups, including “origins” and “effects” of residual stresses. The range of topics covered are “welding, machining, curing/cooling, and spray coating processes,” “medical and dental sciences,” and “fatigue and fracture mechanisms.” The third section summarizes various strategies to effectively control residual stresses through different manufacturing procedures. It is hoped that the data provided herein serves as a valuable up‐to‐date reference for engineers and scientists in the field of residual stress.
In metals additive manufacturing (AM), materials and components are concurrently made in a single process as layers of metal are fabricated on top of each other in the near-final topology required for the end-use product. Consequently, tens to hundreds of materials and part design degrees of freedom must be simultaneously controlled and understood; hence, metals AM is a highly interdisciplinary technology that requires synchronized consideration of physics, chemistry, materials science, physical metallurgy, computer science, electrical engineering, and mechanical engineering. The use of modern machine learning approaches to model these degrees of freedom can reduce the time and cost to elucidate the science of metals AM and to optimize the engineering of these complex, multidisciplinary processes. New machine learning techniques are not needed for most metals AM development; those used in other sects of materials science will also work for AM. Most prolifically, the density functional theory (DFT) community has used many of them since the early 2000s for evaluating numerous combinations of elements and crystal structures to discover new materials. This materials technologies-focused review introduces the basic mathematics and terminology of machine learning through the lens of metals AM, and then examines potential uses of machine learning to advance metals AM, highlighting the many parallels to previous efforts in materials science and manufacturing while also discussing new challenges and adaptations specific to metals AM.
Hydrogen embrittlement critically limits the reliability of high-strength steels, where α-Fe2O3 within passive films serves as the primary barrier against hydrogen ingress. Elemental doping is an effective approach to tune the hydrogen resistance of α-Fe2O3, yet the dopants selection criterion is absent. Here, the spin-polarized density functional theory (DFT) is employed to estimate the doping formation characteristics of 24 types of elements and elucidate how the doping elements influence the vacancies characteristics and hydrogen dissolution behaviors in α-Fe2O3. The 24 types of substitutional doping elements are classified according to their formation energies of dopants, oxygen vacancies, and iron vacancies in α-Fe2O3. The orange-group elements (Al, Cr, Y, Mn, and Ga) are selected as promising dopants to effectively resist the hydrogen and maintain the integrity of oxide film. The effects of strain on the hydrogen dissolution behaviors in doping α-Fe2O3 are also analyzed and the Y doped α-Fe2O3 shows the weakest strain sensitivity. At last, the linear regression models based on seven atomic descriptors are proposed, which could accurately predict the Edoping, EOv, EFev, and Ediss (R2 = 0.70–0.88), respectively. These descriptor-property relationships provide the guidance to design doped α-Fe2O3 passive films with desired hydrogen resistance.
Abstract The impact of Al/Ti electrodes on enhancing the performance and operational stability of n‐channel organic electrolyte‐gated transistors (OEGTs) is investigated. Utilizing Al/Ti electrodes as source and drain electrodes in diketopyrrolopyrrole (DPP)‐based polymeric semiconductor OEGTs leads to a significant decrease in the charge injection barrier for electrons, resulting in improvement of all electrical parameters including on‐current, mobility, on‐off ratio, and threshold voltages. Furthermore, through a comparative analysis of transistors utilizing polymer insulators and solid electrolytes as gate dielectrics, the effect of alterations in the electrodes on the contact resistance of each device is examined. In comparison to OEGTs with Au electrodes, OEGTs with Al/Ti electrodes demonstrate higher operational stability following multiple cycling tests. Finally, the OEGTs produced in this study demonstrate reliable short‐term memory characteristics, which are subsequently utilized for reservoir computing, achieving a high recognition accuracy of 94% for spoken digits.
Electric apparatus and materials. Electric circuits. Electric networks, Physics
Faiza I.A. Abdella, Mohamed Ajroud, Tahani D. Alanezi
et al.
In this study, water-dispersible CdTe quantum dots (QDs) capped with mercaptosuccinic acid (MSA) were synthesized via a green one-pot hydrothermal route and explored as efficient fluorescent probes for Pb2+ detection in aqueous media. The obtained QDs, with an average diameter of 3.4 nm, exhibited high colloidal stability, strong fluorescence, and a narrow emission profile. Remarkably, a selective fluorescence ''turn-off'' response was observed exclusively in the presence of Pb2+ ions, with no significant interference from other tested metal cations. Quantitative analysis using the Stern–Volmer model revealed a linear detection range of 0.2–4 µM (R² = 0.9948) and a low detection limit of 72 nM. Taken with the Benesi–Hildebrand analysis, results confirmed a static quenching mechanism arising from strong Pb2+-carboxylate binding, followed by electron transfer and formation of a non-emissive ground-state complex. Adsorption experiments demonstrated that Pb2+ uptake follows pseudo-first-order kinetics and fits the Langmuir isotherm model, indicating monolayer adsorption on homogeneous active sites. Recovery tests in spiked real tap water samples achieved 95–109 % recoveries with RSD < 5 %, underscoring the probe's reliability under realistic conditions. These results highlight CdTe-MSA QDs as cost-effective, selective, and sensitive chemosensors with strong potential for environmental monitoring of lead contamination.