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"Brenner, W"
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Journey beyond Sodor : the movie
Thomas travels to an unknown train yard outside Sodor and meets new friends.
Book
High-entropy high-hardness metal carbides discovered by entropy descriptors
High-entropy materials have attracted considerable interest due to the combination of useful properties and promising applications. Predicting their formation remains the major hindrance to the discovery of new systems. Here we propose a descriptor—entropy forming ability—for addressing synthesizability from first principles. The formalism, based on the energy distribution spectrum of randomized calculations, captures the accessibility of equally-sampled states near the ground state and quantifies configurational disorder capable of stabilizing high-entropy homogeneous phases. The methodology is applied to disordered refractory 5-metal carbides—promising candidates for high-hardness applications. The descriptor correctly predicts the ease with which compositions can be experimentally synthesized as rock-salt high-entropy homogeneous phases, validating the ansatz, and in some cases, going beyond intuition. Several of these materials exhibit hardness up to 50% higher than rule of mixtures estimations. The entropy descriptor method has the potential to accelerate the search for high-entropy systems by rationally combining first principles with experimental synthesis and characterization.
The overwhelming number of possible high-entropy materials represents a big challenge for predicting their existence. Here, the authors introduce an entropy-forming-ability descriptor capturing the synthesizability of these systems, and apply the model to the discovery of new refractory metal carbides.
Journal Article
Taos Society of Artists
\"\"A lavishly illustrated two-volume study of the Taos Society of Artists. Essays on the TSA and its founding plus scholarly biographical and art historical essays on twelve TSA artists with exemplary works of the artists studied\"-Provided by publisher\"-- Provided by publisher.
BOOK
Settling the matter of the role of vibrations in the stability of high-entropy carbides
High-entropy ceramics are attracting significant interest due to their exceptional chemical stability and physical properties. While configurational entropy descriptors have been successfully implemented to predict their formation and even to discover new materials, the contribution of vibrations to their stability has been contentious. This work unravels the issue by computationally integrating disorder parameterization, phonon modeling, and thermodynamic characterization. Three recently synthesized carbides are used as a testbed: (HfNbTaTiV)C, (HfNbTaTiW)C, and (HfNbTaTiZr)C. It is found that vibrational contributions should not be neglected when precursors or decomposition products have different nearest-neighbor environments from the high-entropy carbide.
The contribution of vibrations to the stability of high-entropy ceramics is still controversial. Here the authors computationally integrate disorder parameterization, phonon modelling, and thermodynamic characterization to investigate the role of vibrations to the stability of high-entropy carbides.
Journal Article
Cyber Threats The Emerging Fault Lines of the Nation State
As new technologies develop, terrorist groups are developing new methods of attack by using the Internet, and by using cyberspace as a battlefield, it has become increasingly difficult to discover the identity of attackers and bring them to justice. The seemingly limitless boundaries of cyberspace has allowed virtually anyone to launch an attack from a remote and anonymous location. But once these attacks occur, it raises several important questions; who should respond, and how?; how should nation-states effectively deal with a cyber-attack?; and will the United States and other nation-states be able to survive in a world where virtual boundaries are limitless? In Cyberthreats: The Emerging Fault Lines of the Nation State Susan Brenner gives a thorough explanation of how military and law enforcement personnel respond to these attacks and why bringing cyber-terrorist to justice can be difficult and sometimes impossible.
eBook
Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone
Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference standard, three CNNs were trained. Training sets balanced for infiltration status, lymph node location and additionally, masked images, were used for training. CNNs were evaluated using a separate test set and performance was compared to radiologists’ assessments and random forest classifiers. Heatmaps maps were used to identify the performance determining image regions. The CNNs performed with an Area-Under-the-Curve of 0.95 (status balanced) and 0.86 (location balanced, masked), compared to an AUC of 0.81 of experienced radiologists. Interestingly, CNNs used anatomical surroundings to increase their performance, “learning” the infiltration probabilities of anatomical locations. In conclusion, CNNs have the potential to build a well performing CT-based biomarker for lymph node metastases in PCa, with different types of class balancing strongly affecting CNN performance.
Journal Article
Tuning friction and slip at solid-nanoparticle suspension interfaces by electric fields
We report an experimental Quartz Crystal Microbalance (QCM) study of tuning interfacial friction and slip lengths for aqueous suspensions of TiO
2
and Al
2
O
3
nanoparticles on planar platinum surfaces by external electric fields. Data were analyzed within theoretical frameworks that incorporate slippage at the QCM surface electrode or alternatively at the surface of adsorbed particles, yielding values for the slip lengths between 0 and 30 nm. Measurements were performed for negatively charged TiO
2
and positively charged Al
2
O
3
nanoparticles in both the absence and presence of external electric fields. Without the field the slip lengths inferred for the TiO
2
suspensions were higher than those for the Al
2
O
3
suspensions, a result that was consistent with contact angle measurements also performed on the samples. Attraction and retraction of particles perpendicular to the surface by means of an externally applied field resulted in increased and decreased interfacial friction levels and slip lengths. The variation was observed to be non-monotonic, with a profile attributed to the physical properties of interstitial water layers present between the nanoparticles and the platinum substrate.
Journal Article
Three decades of many-body potentials in materials research
A brief history of atomic simulation as it was used in chemistry, physics, and materials science is presented starting with seminal work by Eyring in the 1930s through to current work and future challenges. This article provides the background and perspective needed to understand the ways in which reactive many-body potentials developed over the last three decades and have impacted materials research. It also explains the way in which this substantial impact on the field has been facilitated by increases in computational resources and traces the development of reactive potentials, which have steadily increased in complexity and sophistication over time. Together with the other contributions in this issue of MRS Bulletin, this article will help guide and inspire the next generation of computational materials scientists and engineers as they build on current capabilities to expand atomic simulation into new and exciting areas of materials research.
Journal Article
Machine learned interatomic potentials for ternary carbides trained on the AFLOW database
Large-density functional theory (DFT) databases are a treasure trove of energies, forces, and stresses that can be used to train machine-learned interatomic potentials for atomistic modeling. Herein, we employ structural relaxations from the AFLOW database to train moment tensor potentials (MTPs) for four carbide systems: CHfTa, CHfZr, CMoW, and CTaTi. The resulting MTPs are used to relax ~6300 random symmetric structures, and are subsequently improved via active learning to generate robust potentials (RP) that can relax a wide variety of structures, and accurate potentials (AP) designed for the relaxation of low-energy systems. This protocol is shown to yield convex hulls that are indistinguishable from those predicted by AFLOW for the CHfTa, CHfZr, and CTaTi systems, and in the case of the CMoW system to predict thermodynamically stable structures that are not found within AFLOW, highlighting the potential of the employed protocol within crystal structure prediction. Relaxation of over three hundred (Mo
1−
x
W
x
)C stoichiometry crystals first with the RP then with the AP yields formation enthalpies that are in excellent agreement with those obtained via DFT.
Journal Article
Disordered enthalpy–entropy descriptor for high-entropy ceramics discovery
The need for improved functionalities in extreme environments is fuelling interest in high-entropy ceramics
1
–
3
. Except for the computational discovery of high-entropy carbides, performed with the entropy-forming-ability descriptor
4
, most innovation has been slowly driven by experimental means
1
–
3
. Hence, advancement in the field needs more theoretical contributions. Here we introduce disordered enthalpy–entropy descriptor (DEED), a descriptor that captures the balance between entropy gains and enthalpy costs, allowing the correct classification of functional synthesizability of multicomponent ceramics, regardless of chemistry and structure. To make our calculations possible, we have developed a convolutional algorithm that drastically reduces computational resources. Moreover, DEED guides the experimental discovery of new single-phase high-entropy carbonitrides and borides. This work, integrated into the AFLOW computational ecosystem, provides an array of potential new candidates, ripe for experimental discoveries.
DEED captures the balance between entropy gains and costs, allowing the correct classification of functional synthesizability of multicomponent ceramics, regardless of chemistry and structure, and provides an array of potential new candidates, ripe for experimental discoveries.
Journal Article