Hasil untuk "Materials Science"

P. Kotetes

In recent years, the notion of “Quantum Materials” has emerged as a powerful unifying concept across diverse fields of science and engineering, from condensed-matter and coldatom physics to materials science and quantum computing. Beyond traditional quantum materials such as unconventional superconductors, heavy fermions, and multiferroics, the field has significantly expanded to encompass topological quantum matter, two-dimensional materials and their van der Waals heterostructures, Moiré materials, Floquet time crystals, as well as materials and devices for quantum computation with Majorana fermions. In this Roadmap collection we aim to capture a snapshot of the most recent developments in the field, and to identify outstanding challenges and emerging opportunities. The format of the Roadmap, whereby experts in each discipline share their viewpoint and articulate their vision for quantum materials, reflects the dynamic and multifaceted nature of this research area, and is meant to encourage exchanges and discussions across traditional disciplinary boundaries. It is our hope that this collective vision will contribute to sparking new fascinating questions and activities at the intersection of materials science, condensed matter physics, device engineering, and quantum information, and to shaping a clearer landscape of quantum materials science as a new frontier of interdisciplinary scientific inquiry. The 2020 Quantum Materials Roadmap – Table of

V. Georgakilas, M. Otyepka, A. Bourlinos et al.

Vinodkumar Etacheri, Rotem Marom, Ran Elazari et al.

Yanwu Zhu, S. Murali, Weiwei Cai et al.

R. Nair, P. Blake, A. Grigorenko et al.

There are few phenomena in condensed matter physics that are defined only by the fundamental constants and do not depend on material parameters. Examples are the resistivity quantum, h/e2 (h is Planck's constant and e the electron charge), that appears in a variety of transport experiments and the magnetic flux quantum, h/e, playing an important role in the physics of superconductivity. By and large, sophisticated facilities and special measurement conditions are required to observe any of these phenomena. We show that the opacity of suspended graphene is defined solely by the fine structure constant, a = e2/hc � 1/137 (where c is the speed of light), the parameter that describes coupling between light and relativistic electrons and that is traditionally associated with quantum electrodynamics rather than materials science. Despite being only one atom thick, graphene is found to absorb a significant (pa = 2.3%) fraction of incident white light, a consequence of graphene's unique electronic structure.

J. Yeh, S. Chen, Su-Jien Lin et al.

X. Michalet, F. Pinaud, L. Bentolila et al.

M. Daniel, D. Astruc

A. Belsky, M. Hellenbrandt, V. Karen et al.

I. Armentano, N. Bitinis, E. Fortunati et al.

Kesong Liu, Moyuan Cao, A. Fujishima et al.

Zuchong Yang, Daniele Zucchelli, Melissa Berteau‐Rainville et al.

Abstract Polymer semiconductors hold great potential as active materials in (opto)electronic, thermoelectric, and biomedical devices. Their charge transport performance has seen tremendous progress, with mobilities exceeding 1 cm2 V−1 s−1 for a variety of donor‐acceptor copolymers. Nevertheless, charge injection at the metal/polymer interface is still rather ineffective and poorly understood. In a field‐effect transistor, this process is manifested by the contact resistance (Rc) which, for polymers, is several orders of magnitude higher than for their inorganic counterparts. Therefore, an in‐depth investigation of the charge injection in metal/donor‐acceptor polymer systems is sought‐after. Here, the low‐temperature dependent Rc and charge transport of a model isoindigo donor‐acceptor copolymer‐based transistor are studied. The metal/polymer interface is tuned by functionalizing the electrodes with different thiolated self‐assembled monolayers (SAMs). Rc in devices with SAM‐functionalized electrodes is generally lower and exhibited a weak temperature dependence. Counterintuitively, electrodes functionalized with SAMs expected to lead to an apparently unfavorable energy level alignment displayed the lowest Rc. The Fermi level is found to be pinned at all the encompassed interfaces. An energy‐level alignment modeling is employed to understand this behavior. The findings reveal that simply looking at the energy levels alignment of metal/polymer interface does not necessarily lead to reduced Rc.

Peng He, Zhaohui Li, Zeyuan Wang et al.

Designing high-quality, standards-aligned instructional materials for K--12 science is time-consuming and expertise-intensive. This study examines what human experts notice when reviewing AI-generated evaluations of such materials, aiming to translate their insights into design principles for a future GenAI-based instructional material design agent. We intentionally selected 12 high-quality curriculum units across life, physical, and earth sciences from validated programs such as OpenSciEd and Multiple Literacies in Project-based Learning. Using the EQuIP rubric with 9 evaluation items, we prompted GPT-4o, Claude, and Gemini to produce numerical ratings and written rationales for each unit, generating 648 evaluation outputs. Two science education experts independently reviewed all outputs, marking agreement (1) or disagreement (0) for both scores and rationales, and offering qualitative reflections on AI reasoning. This process surfaces patterns in where LLM judgments align with or diverge from expert perspectives, revealing reasoning strengths, gaps, and contextual nuances. These insights will directly inform the development of a domain-specific GenAI agent to support the design of high-quality instructional materials in K--12 science education.

J. Lehn

Nargis Fatima Khatoon, Zubair Aslam, Mohd Shoab et al.

Abstract In this manuscript, we report successful synthesis and investigation of structural, morphological, electrical, and optical properties of doped and undoped Sb2Se3. A significant enhancement in electrical and optical properties of Zn-doped Sb2Se3 is observed. The temperature dependence of direct current (dc) conductivity has been investigated in thin films of Sb2ZnxSe3-x (where x = 0 and x = 0.25) in the temperature range of 290–490 K to determine the conduction mechanism and examine the effects of doping. It shows that, in the temperature range (343–490 K), conduction is primarily due to thermally activated tunneling of charge carriers through the band tails of localized states. In the lower temperature range 293–343 K, conduction occurs via variable range hopping in the localized states near the fermi level. The decrease in the optical bandgap value as a result of Zn doping in Sb2Se3 has been correlated with the variation in density of states, increased electron–phonon interaction and steepness parameter.

Minh-Hao Van, Prateek Verma, Chen Zhao et al.

Foundation models (FMs) are catalyzing a transformative shift in materials science (MatSci) by enabling scalable, general-purpose, and multimodal AI systems for scientific discovery. Unlike traditional machine learning models, which are typically narrow in scope and require task-specific engineering, FMs offer cross-domain generalization and exhibit emergent capabilities. Their versatility is especially well-suited to materials science, where research challenges span diverse data types and scales. This survey provides a comprehensive overview of foundation models, agentic systems, datasets, and computational tools supporting this growing field. We introduce a task-driven taxonomy encompassing six broad application areas: data extraction, interpretation and Q\&A; atomistic simulation; property prediction; materials structure, design and discovery; process planning, discovery, and optimization; and multiscale modeling. We discuss recent advances in both unimodal and multimodal FMs, as well as emerging large language model (LLM) agents. Furthermore, we review standardized datasets, open-source tools, and autonomous experimental platforms that collectively fuel the development and integration of FMs into research workflows. We assess the early successes of foundation models and identify persistent limitations, including challenges in generalizability, interpretability, data imbalance, safety concerns, and limited multimodal fusion. Finally, we articulate future research directions centered on scalable pretraining, continual learning, data governance, and trustworthiness.

Amitayush Jha Thakur, Maximilian Thees, Franck Fortuna et al.

We report the measurement, using angle-resolved photoemission spectroscopy, of the metallic electronic structure of the hole-doped thermoelectric oxide CuRh$_{0.9}$Mg$_{0.1}$O$_2$. The material is found to have a ``pudding mold'' type band structure, with a nearly flat band edge located near the Fermi level, which is thought to be the origin of the thermoelectric behavior of this material. The experimental data match the density functional theory of the undoped parent compound, simply corrected by a rigid shift of the bands. Transport calculations based on the observed band structure yield a Seebeck coefficient of $\sim 200 \,μ$V/K for the undoped parent material, consistent with experimental measurements. Our results show that CuRhO$_2$ is a textbook example of how pure band-structural effects can result in a large thermoelectric figure of merit, demonstrating that flat band edges in oxides are a realistic route for the efficient conversion of thermal energy.

Grace Wolf-Chase, Charles Kerton, Kathryn Devine et al.

We review participatory science programs that have contributed to the understanding of star formation. The Milky Way Project (MWP), one of the earliest participatory science projects launched on the Zooniverse platform, produced the largest catalog of ``bubbles'' associated with feedback from hot young stars to date, and enabled the identification of a new class of compact star-forming regions (SFRs) known as ``yellowballs'' (YBs). The analysis of YBs through their infrared colors and catalog cross-matching led to discovering that YBs are compact photodissociation regions generated by intermediate- and high-mass young stellar objects embedded in clumps that range in mass from 10 - 10,000 solar masses and luminosity from 10 - 1,000,000 solar luminosities. The MIRION catalog, assembled from 6176 YBs identified by citizen scientists, increases the number of candidate intermediate-mass SFRs by nearly two orders of magnitude. Ongoing work utilizing data from the Spitzer, Herschel and WISE missions involves analyzing infrared color trends to predict physical properties and ages of YB environments. Methods include applying summary statistics to histograms and color-color plots as well as SED fitting. Students in introductory astronomy classes contribute toward continued efforts refining photometric measurements of YBs while learning fundamental concepts in astronomy through a classroom-based participatory science experience, the PERYSCOPE project. We also describe an initiative that engaged seminaries, family groups, and interfaith communities in a wide variety of science projects on the Zooniverse platform. This initiative produced important guidance on attracting audiences that are underserved, underrepresented, or apprehensive about science.

Paphada Limpachanangkul, Licheng Liu, Prathana Nimmmanterdwong et al.

An artificial neural network (ANN) was applied to construct the relationship between the CO2 photocatalyst variables. A total of 147 data points from 38 research publications related to photocatalytic CO2 reduction via bismuth-based photocatalysts were used to develop, validate and test the developed model. The most important variable for the yield of the obtained product is irradiation time. The longer irradiation time the higher obtained product yield. Whereas the type of main product and band gap energy had the strongest effect on product yield in the positive and negative directions, respectively, in the Pearson correlation analysis. The ANN model was successfully tested to predict other literature datasets. The ANN model can then be used to estimate the yield of the obtained product, which reflects the CO2 photocatalytic reduction efficiency.

Futing Shu, Hongchao Huang, Shichu Xiao et al.

Diabetic wounds, characterized by prolonged inflammation and impaired vascularization, are a serious complication of diabetes. This study aimed to design a gelatin methacrylate (GelMA) hydrogel for the sustained release of netrin-1 and evaluate its potential as a scaffold to promote diabetic wound healing. The results showed that netrin-1 was highly expressed during the inflammation and proliferation phases of normal wounds, whereas it synchronously exhibited aberrantly low expression in diabetic wounds. Neutralization of netrin-1 inhibited normal wound healing, and the topical application of netrin-1 accelerated diabetic wound healing. Mechanistic studies demonstrated that netrin-1 regulated macrophage heterogeneity via the A2bR/STAT/PPARγ signaling pathway and promoted the function of endothelial cells, thus accelerating diabetic wound healing. These data suggest that netrin-1 is a potential therapeutic target for diabetic wounds.