(1) Background: Properties and descriptors are two forms of molecular in silico representations. Properties can be further divided into functional, e.g., catalyst or drug activity, and material, e.g., X-ray crystal data. Millions of real measured fun...
The research presented in this paper aims at creating a bilingual (sr-en), easily searchable, hypertext, born-digital, corpus-based terminological database of raw material terminology for dictionary production. The approach is based on linking dictio...
The development of material science in the manufacturing industry has resulted in a huge amount of material data, which are often from different sources and vary in data format and semantics. The integration and fusion of material data can offer a un...
The performance of lithium-ion batteries is strongly determined by material properties, which are provided in technical data sheets but often in inconsistent formats and terminology. Automated extraction of these parameters could enable downstream ap...
The selection of the most suitable material is one of the key decisions to be made during the design stage of a manufacturing process. Traditional approaches, such as Ashby maps based on material properties, are widely used in industry. However, in t...
The aim of nuclear safeguards is to ensure that special nuclear material is used for peaceful purposes. Historically, nuclear material accounting (NMA) has provided the quantitative basis for monitoring for nuclear material loss or diversion, and pro...
As the use of data models and data science techniques in industrial processes grows exponentially, the question arises: to what extent can these techniques impact the future of manufacturing processes? This article examines the potential future impac...
Cast iron is a very common and useful metal alloy, characterized by its high carbon content (>4%) in the allotropic state of graphite. The correct shape and distribution of graphite are essential for ensuring that the material has the right proper...
Human life occurs within a complex bio-psycho-social milieu, a heterogeneous system that is integrated by multiple bidirectional interrelations existing between the abstract-intangible ideas and physical-chemical support of environment. The mind is t...
Physics-Informed neural networks (PINNs) have demonstrated remarkable performance in solving partial differential equations (PDEs) by incorporating the governing PDEs into the network’s loss function during optimization. PINNs have been success...
This study conducted a big data mining and lexical co-occurrence network analysis on design texts sourced from architectural media over the past decade, systematically evaluating the application trends of materials in architectural design. This appro...
A new data-driven continuum model based on an artificial neural network is developed in this study for a new three-dimensional lattice-structured material design. The model has the capability to capture and predict the nonlinear elastic behaviour of...
Multi-material jetting (CerAM MMJ, previously T3DP) enables the additive manufacturing of ceramics, metals, glass and hardmetals, demonstrating comparatively high solid contents of the processed materials. The material is applied drop by drop onto a...
Dynamic material stock–flow analysis is widely used to assess long-lived built-environment systems, but data scarcity makes its application challenging because stock, inflow, and outflow evidence often do not form a coherent accounting structur...
The Curie temperature (Tc) of LaMnO3-based perovskites is one of the most important properties associated with their magnetic and spintronic applications. The search for new perovskites with even higher Tc is a challenging problem in material design....
The rapid expansion of artificial intelligence has intensified the demand for high-performance data centers, leading to unprecedented pressures on energy, water, and material resources. This critical review examines the emerging challenges associated...
Road hazardous material transportation plays a critical role in road traffic management. Due to the dangerous nature of the cargo, hazardous material transportation trucks (HMTTs) have different route selection and driving characteristics compared to...
Museum cultural relics represent a special material cultural heritage, and modern interpretations of them are needed in current society. Based on the catalogue data of cultural relics published by the State Administration of Cultural Heritage, this p...
Material research and development driven by data analysis necessitates a substantial volume of data. However, conventional material data sharing platforms encounter challenges in sharing and integrating data across multiple platforms. This article pr...
Biphasic soft materials are challenging to model by nature. Ongoing efforts are targeting their effective modeling and simulation. This work uses experimental atomic force nanoindentation of thick hydrogels to identify the indentation forces are a fu...
Machine learning (ML) in materials science refers to computational methods that learn statistical, structural, or physics-informed relationships from experimental, computational, and literature-derived materials data. These methods are used to predic...
With the rapid development of machine learning techniques, data-mining for processes in chemistry, materials, and engineering has been widely reported in recent years. In this discussion, we summarize some typical applications for process optimizatio...
In the current data age, the fundamental research related to optical applications has been rapidly developed. Countless new-born materials equipped with distinct optical properties have been widely explored, exhibiting tremendous values in practical...
In recent years, high-entropy materials (HEMs) have garnered significant attention due to their unique multi-principal element compositions, which endow them with remarkable properties distinct from traditional materials. The order and disorder in HE...
The construction industry is heavily influenced by the volatility of material prices, which can significantly impact project costs and budgeting accuracy. Traditional econometric methods have been challenged by their inability to capture the frequent...
Programmable quantum simulators based on Rydberg atom arrays provide a versatile platform for data-driven quantum simulation of strongly correlated systems, combinatorial optimization problems, and artificial quantum materials. In this review, we pre...
In order to accurately extract and match carbon emission factors from the Chinese textual building materials list and construct a precise carbon emission factor database, it is crucial to accurately classify the textual building materials. In this st...
Scientific communication, collaboration and progress are enhanced through the exchange of data, materials and ideas. Recent advances in technology, commercial proprietary discovery and current local and global events (e.g., emerging human, animal and...
There is a high need for a big data repository for material compositions and their derived analytics of metal strength, in the material science community. Currently, many researchers maintain their own excel sheets, prepared manually by their team by...
Biodegradable zinc alloys have shown great potential in the biomedical field, but are limited by their poor mechanical properties. Alloying is essential for improving mechanical properties, yet designing multicomponent zinc alloys remains challenging...
In order to realize the intelligent management of a power materials warehouse, the Internet of Things based on wireless sensor networks (WSNs) is a promising effective solution. Considering the limited battery capacity of sensor nodes, the optimizati...
Photocatalytic anti-corrosion materials are an emerging intelligent protective material that has been widely used in marine and offshore engineering in recent years. However, its failure mechanism under multi-factor coupling is complex, and it is dif...
In the ongoing academic discussion regarding what happens to our data after we die, how our data are utilised for commercial profit-making purposes, and what kinds of death-related practices our posthumous data figure in, the notion of digital afterl...
To obtain the mechanical behavior response of the material under loading, a data-driven construction method of material mechanical behavior model is proposed, which is universal for predicting the mechanical behavior of any material under different l...
In automotive body-in-white production, presshardened 22MnB5 steel is the most widely used ultra-high-strength steel grade. Welding is the most important faying technique for this steel type, as other faying technologies often cannot deliver the same...
The aim of this research is to investigate potential uses of the CHIME and LSTM missions for urban climate research. Therefore, this paper initially introduces two methodologies to obtain synthetic images for these future ESA missions starting from e...
The objective of this paper was to examine the potential for the automated release of research data within the context of material science consortium projects, with adherence to the stipulated rules and contractual agreements, while also considering...
For the European Union in the field of raw material policy, it is primarily important to ensure reliable, seamless, and unrestricted access to raw materials in all EU countries. An important aspect in assessing the European Union’s raw material...
Advancements in deep learning have revolutionized materials discovery by enabling predictive modeling of complex material properties. However, single-modal approaches often fail to capture the intricate interplay of compositional, structural, and mor...
Aligning the European Union goals for climate neutrality by 2050 and the ambition for carbon equivalent emissions reduction to almost half by 2030 demands the exploration of alternative decarbonisation pathways. Energy consumption across all sectors...
Imaging scatterometry is a method for determining the reflection distribution based on bidirectional reflectance distribution function (BRDF) measurements. However, it has a well-known limitation that results obtained by imaging scatterometry for sma...
The need to accelerate the innovation and application of the supply chain has been suggested by the State Council of China. To solve the problem of data isolation caused by privacy protection in the power material supply chain, a data traceability an...
As the application of machine learning technology in predicting and optimizing material performance continues to grow, handling the electromagnetic data of magnetic materials, especially in removing unavoidable data noise and accurately extracting re...
The wedge-loaded asymmetric double cantilever beam (WADCB) test is an experimental method to determine the mixed-mode I/II fracture toughness of composite materials by inserting a wedge into the specimen along a potential delamination path. Whilst th...
In this work, we provide an innovative route for analysing urban expansion and population growth and their link to the consumption of construction materials by combining satellite data with material consumption analysis within the Hanoi Province (Vie...
Polarization provides useful quantitative information about scattering surfaces. In hyperspectral remote sensing of natural surfaces composed of granular materials, there are relatively few studies of polarization. Most earlier remote sensing studies...
Flexible wearable electronics have shown strong potential for medical and health monitoring; however, conventional materials often fail to simultaneously satisfy the requirements of signal stability, wear comfort, and environmental adaptability under...
This study presents a comprehensive simulation-driven approach to identify and mitigate bottlenecks in the supply flows of an automotive manufacturing system. The supply process relies on a Kanban-based assembly line replenishment, supported by multi...
When characterizing the viscoelastic properties of polymers, shear rheological measurements are commonly the method of choice. These properties are known to affect extrusion and nozzle-based processes such as fiber melt spinning, cast film extrusion...
Material-resolving computed tomography is a powerful and well-proven tool for various clinical applications. For industrial scan setups and materials, several problems, such as K-edge absence and beam hardening, prevent the direct transfer of these m...
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