Quantitative Descriptor Research Articles

A model for predicting grain-boundary energy of refractory high-entropy alloys based on local element concentration

Refractory high-entropy alloys (RHEAs) exhibit exceptional high-temperature mechanical properties, and their structural stability is primarily influenced by grain boundaries (GBs). However, it remains challenging to accurately quantify the grain boundary energy (GBE) in RHEAs. Herein, we introduce a quantitative descriptor for point-to-point prediction of GBEs in RHEAs based on local element concentration and valence-electron numbers. Our results demonstrate that the role of the constituent elements on GBEs is primarily determined by their valence-electron numbers in RHEAs. These findings are derived from the cohesive energy and atomic structure of the elements within the framework of the broken-bond model, as well as the differential contributions of s-electrons and d-electrons. The model establishes a structure-property relationship between local element concentration and GBEs, with the prediction consistent with experimental and theoretical results, which is crucial for evaluating the GB stability of RHEAs and facilitating the development of high-performance alloys.

Microstructural Hierarchy Descriptor Enabling Interpretative AI for Microelectronic Failure Analysis

Abstract This article proposes the MicroStructural Hierarchy Descriptor (µSHD) as a systematic and quantitative approach to spectra and image data in microelectronics failure analysis. It discusses concrete routes for employing µSHD directly as the quantitative descriptor for supervised and unsupervised machine learning. The authors propose that µSHD tools can be used to automate and improve characterization techniques and image processing and analysis protocols.

Unraveling the role of single-atom metal dopant over CeO2 catalyst in tuning catalytic performance of ethane oxidative dehydrogenation

Single-atom metal doped CeO2 (M1@CeO2) catalysts have exhibited better catalytic performance in methane and propane dehydrogenation, which may be applied to ethane dehydrogenation, revealing structure-activity relationship of M1@CeO2 catalysts is of great importance. In this work, DFT + U calculations together with kinetic Monte Carlo simulations were implemented to investigate the oxidative dehydrogenation stage (ODH) in ethane chemical looping-oxidative dehydrogenation (CL-ODH) over thirteen types of M1@CeO2 catalysts (M = Cr, Mn, Fe, Co, Ni, Ga, Mo, Ru, Rh, Pd, In, Ir and Pt). The results show that the doped single-atom metal and its adjacent O atoms act as active sites over four catalysts Rh, Pd, Ir and Pt doped CeO2, while only O atoms act as active sites over other nine catalysts M1@CeO2. Rh1@CeO2 was screened out to perform higher C2H4(g) selectivity of 98.8 % and C2H4(g) formation activity of 8.72×103 s−1 site−1 at 823.15 K with C2H6(g) partial pressure <0.2 bar, which is superior to the previously reported catalysts Pt, Pt3Sn, Pt3Ir, Ni3Mo, Co/g-C3N4 and Rh/ZrO2, and so on. A quantitative and quick descriptor, the binding strength of C2H5* intermediate is proposed to evaluate C2H4(g) formation activity. This study unravels the role of doped single-atom metal over CeO2 catalyst and help rationally design high-efficiency alkane dehydrogenation.

Origin of Spin‐State Precise Modulation for Enhanced Oxygen Evolution Activity: Effect of Secondary Coordination Sphere

AbstractThe process of oxygen evolution reaction (OER) is crucial for energy storage and conversion, and the spin electronic structure of catalyst significantly influences its catalytic activity. Precisely regulating the spin electronic structures of metal active centers with intermediate spin (IS) states is challenging but important. This study presents a general method for achieving spin‐state precise modulation by altering the secondary coordination sphere (SCS) in Fe‐substituted LaCo1‐xFexO3 perovskites, denoted as Co6‐y−[Co]−Fey (y = 0–6). The concentration‐dependent SCSs can precisely regulate the spin state of Co3+ from high‐spin (HS) to IS and low‐spin (LS) state by tuning the Co─O binding energy of primary coordination sphere (PCS) to ≈567 KJ mol−1. The binding energy demonstrates a strong negative correlation with the spin state of Co3+, serving as a quantitative descriptor for precise spin‐state modulation. Furthermore, a universal optimal doping concentration is proposed for generating IS‐state Co3+ with the best OER activity, ranging from 1/(m+1) to 2/(m+1) in M‐doped ACo1‐xMxOy system with the coordination number of m. As a proof‐of‐concept, the LaCo7/9Fe2/9O3 with IS Co3+ exhibits significantly enhanced OER activity, almost six times higher than the control samples (without IS Co3+). These findings provide new insights into spin‐state modulation for effective OER catalysts.

Quantitative descriptor of lattice anharmonicity in crystal

&lt;sec&gt;Anharmonic effect is often one of the physical root causes of some special material properties, such as soft mode phase transition, negative thermal expansion, multiferroicity, and ultra-low thermal conductivity. However, the existing methods of quantifying the anharmonicity of material do not give a clear and accurate anharmonicity descriptor. The calculation of the anharmonic effect requires extremely time-consuming molecular dynamics simulation, the calculation process is complex and costly. Therefore, a quantitative descriptor is urgently needed, which can be used to implement quick calculation so as to understand, evaluate, design, and screen functional materials with strong anharmonicity.&lt;/sec&gt;&lt;sec&gt;In this paper, we propose a method to quantify the anharmonicity of materials by only phonon spectrum and static self-consistent calculation through calculating and analyzing the material composed of germanium and its surrounding elements. In this method, the lattice anharmonicity is decomposed into the anharmonic contribution of independent phonon vibration modes, and the quantitative anharmonicity descriptor &lt;inline-formula&gt;&lt;tex-math id="M3"&gt;\begin{document}$ {\sigma }_{\boldsymbol{q},j}^{A} $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231428_M3.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231428_M3.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt; of phonons is proposed. Combining it with the Bose-Einstein distribution, the quantitative descriptor &lt;inline-formula&gt;&lt;tex-math id="M4"&gt;\begin{document}$ {A}_{{\mathrm{p}}{\mathrm{h}}}\left(T\right) $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231428_M4.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231428_M4.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt; of temperature-dependent material anharmonicity is proposed. We calculate the bulk moduli and lattice thermal conductivities at 300 K of nine widely representative materials. There is a clear linear trend between them and our proposed quantitative descriptor &lt;inline-formula&gt;&lt;tex-math id="M5"&gt;\begin{document}$ {A}_{{\mathrm{p}}{\mathrm{h}}}\left(T\right) $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231428_M5.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231428_M5.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt;, which verifies the accuracy of our proposed descriptor. The results show that the descriptor has the following functions. i) It can systematically and quantitatively classify materials as the strength of anharmonicity; ii) it intuitively shows the distribution of the anharmonic effect of the material on the phonon spectrum, and realizes the separate analysis of the phonon anharmonicity that affects the specific properties of the material; iii) it is cost-effective in first-principles molecular dynamics calculations and lays a foundation for screening and designing materials based on anharmonicity.&lt;/sec&gt;&lt;sec&gt;This study provides an example for the high-throughput study of functional materials driven by anharmonic effect in the future, and opens up new possibilities for material design and application. In addition, for strongly anharmonic materials such as CsPbI&lt;sub&gt;3&lt;/sub&gt;, the equilibrium position of the atoms is not fixed at high temperatures, resulting in a decrease in the accuracy of quantifying anharmonicity using our proposed descriptor. In order to get rid of this limitation, our future research will focus on the distribution of atomic equilibrium positions in strongly anharmonic materials at high temperatures, so as to propose a more accurate theoretical method to quantify the anharmonicity in strongly anharmonic materials.&lt;/sec&gt;

(Invited) Design of Lithium Battery Electrolytes Based on Electrode Potentials

Lithium (Li) metal is an ideal battery anode with low electrode potential (-3.045 V vs. SHE) and high theoretical capacity (3860 mAh g-1, 2060 mAh cm-3). However, its critical problem is a low Coulombic efficiency (CE), which is caused the thermodynamic instability of a Li/electrolyte interface because of the strong reducing ability of Li metal. Since Li electrode potential (E Li) is located far below the cathodic limit of the electrolyte's potential window, the electrolyte components are inevitably reduced and decomposed on the Li metal anode (Fig. 1). Some of the decomposition products function as solid electrolyte interphase (SEI) to suppress further electrolyte decomposition. Various electrolytes and additives have been proposed to form a stable SEI on Li metal, which leads to higher CEs. However, the correlation between CE and SEI is still unclear.Here we report E Li as a quantitative and thermodynamic descriptor of the CEs of Li metal anodes.1 We measured E Li in various electrolytes with reference to 1 mM ferrocene as an internal standard. The obtained E Li varied significantly (up to 0.6 V) depending on electrolyte formulations. We also evaluated the CEs of Li plating/stripping in various electrolytes without ferrocene. Based on these results, we found that the CEs are correlated with E Li (Fig. 2). The CE increased with increasing E Li, suggesting that the reductive decomposition of electrolytes was suppressed at high E Li (lower reducing ability of Li).Theoretically, E Li is directly determined by the chemical potential of Li+ (μ Li+) in the electrolyte. Hence, E Li, that is the reducing ability of Li, can be controlled by designing an electrolyte focusing on μ Li+. Raman Spectroscopy revealed that the formation of ion pairs is essential for increasing the μ Li+ and upshifting the E Li. This finding provides fundamental science that can tune the μ Li+ and E Li to increase the CE of Li metal anodes.1. Seongjae Ko, Tomohiro Obukata, Tatau Shimada, Norio Takenaka, Masanobu Nakayama, Atsuo Yamada, Yuki Yamada, Nat. Energy, 7, 1217-1224 (2022). Figure 1

Coupling a Main-Group Metal with a Transition Metal to Create Biatom Catalysts for Nitric Oxide Reduction

Developing efficient biatom catalysts for renewable energies is becoming increasingly worthwhile, yet it remains a great challenge. Herein, by means of large-scale first-principles calculations, we report a design principle of coupling main-group metal with transition metal (TM) to explore biatom catalysts for nitric oxide reduction reaction (NORR), namely, $\mathrm{Mg}/\mathrm{Al}/\mathrm{Ga}\ensuremath{-}\mathrm{TM}$ dimers anchored on nitrogen-doped graphene. We propose a comprehensive screening strategy to recognize promising candidates of such catalysts. Following this strategy, we screen $\mathrm{Mg}\ensuremath{-}\mathrm{Ni}@\mathrm{NC}$ and $\mathrm{Ga}\ensuremath{-}\mathrm{Cr}@\mathrm{NC}$ out of 24 candidates as promising biatom catalysts with high activity and selectivity for direct $\mathrm{NO}$-$\mathrm{to}$-${\mathrm{NH}}_{3}$ conversion. Such high catalytic activity is related to the synergetic interatomic interactions. Moreover, based on the interplay between main-group metal and TM centers, we propose a ``donation-backdonation-redonation'' mechanism to characterize $\mathrm{NO}$ activation. In addition, $\mathrm{\ensuremath{\Delta}}{\ensuremath{\epsilon}}_{s/p\ensuremath{\rightarrow}d}$ is identified as an efficient quantitative descriptor to prereduce the number of such catalyst candidates. Our work opens a strategy for rational design of biatom catalysts toward NORR.

Digital characterization of the surface texture of chinese classical garden rockery based on point cloud visualization: small-rock mountain retreat

The Rockery is often a key element of a Classical Chinese Garden. It’s exquisite detailed physical characteristics a major contributor to artistic value, aesthetic appeal, and the carrier of historical and cultural heritage values. Poets and scholars have often described the beauty of these places in classical gardens in qualitative terms but lacked the quantitative tools to provide replicable metric descriptions. The highly complex forms and surfaces, irregularity, and fragility of garden rockeries has challenged authors to accurately describe the characteristics of these qualities using traditional methods and tools. This article presents a new method of digital characterization approach based on laser scanning and point cloud visualization, which can quantitatively detect and represent the pattern of rockery surface textures. It offers a replicable accurate quantitative descriptor of the Classical Chinese rockery. The Small-Rock Mountain Retreat, a nationally protected rockery garden in China, has been used as a case study. It contains original historic elements and more recently restored areas. Two characteristics of rockery surfaces, including the well-proportioned density and space, and the proper contrast between solid and void, were analyzed by examining four attributes: (1) surface complexity; (2) contour curvature; (3) shape variation; and (4) the interweaving of lightness and darkness. The findings demonstrate that, despite some similarities between the restored portion of the rockery and the historical remnants, there are variances in the richness of the details and the balanced distribution of shape change. The digital characterization approach introduced in this article offers a new perspective for recording and in turn safeguarding Chinese garden rockeries and other irregular cultural heritage objects.

Heterogeneous consecutive reaction kinetics of direct oxidation of H2 to H2O2: Effect and regulation of confined mass transfer

Porous catalysts in heterogeneous reactions have played an important role in the modern chemical industry, but it is still challenging to quantitatively describe mass transfer and surface reaction behaviors of reactants in nano-confined space. Direct synthesis of hydrogen peroxide (H2O2) is considered as an attractive alternative to anthraquinone oxidation process, while the confined mass transfer of H2O2 in porous catalysts limits the reactivity. In this work, taking the consecutive reaction of H2O2 synthesis as an example, a quantitative method in modeling the effects of confined mass transfer on the reactivity was studied. More specifically, calorimetry was developed to characterize the confined structures of porous carbon experimentally, the linear nonequilibrium thermodynamics and the statistical mechanics method were further combined. Then, the heterogeneous consecutive reaction kinetics and the Thiele modulus influenced by confined mass transfer were modeled. Consequently, regulation strategies were proposed with the help of theoretical models. The optimized catalyst with biological skeleton carbon support and 0.5 wt% palladium loading shows an excellent catalytic performance. Lastly, for the mesoscience in heterogeneous reaction, the resistance was explored as a quantitative descriptor to compromise in the competition between mass transfer and surface reaction. The mesoscale structures were considered as the dynamic spatiotemporal distribution of substance concentrations, and the resistance minimization multi-scale (RMMS) model was proposed.

Engineering Cu+/CeZrOx interfaces to promote CO2 hydrogenation to methanol

Cu-based catalysts are widely employed for CO2 hydrogenation to methanol, which is expected as a promising process to achieving carbon neutrality. However, most Cu-based catalysts still suffer from low methanol yield with a passable CO2 conversion and lack insight into its reaction mechanism for guiding the design of catalysts. In this work, Cu+/CeZrOx interfaces are engineered by employing a series of ceria-zirconia solid solution catalysts with various Ce/Zr ratios, forming a Cu+-Ov-Ce3+ structure where Cu+ atoms are bonded to the oxygen vacancies (Ov) of ceria. Compared to Cu/CeO2 and Cu/ZrO2, the optimized catalyst (i.e., Cu0.3Ce0.3Zr0.7) exhibits a much higher mass-specific methanol formation rate (192 gMeOH/kgcat/h) at 240 °C and 3 MPa. Through a series of in-situ and ex-situ characterization, it is revealed that oxygen vacancies in solid solutions can effectively assist the activation of CO2 and tune the electronic state of copper to promote the formation of Cu+/CeZrOx interfaces, which stabilizes the key *CO intermediate, inhibits its desorption and facilitates its further hydrogenation to methanol via the reverse water–gas-shift (RWGS) + CO-Hydro pathway. Therefore, the concentration of *CO or the apparent Cu+/(Cu++Cu0) ratio could be employed as a quantitative descriptor of the methanol formation rate. This work is expected to give a deep insight into the mechanism of metal/support interfaces in CO2 hydrogenation to methanol, offering an effective strategy to develop new catalysts with high performance.

Revealing the activity origin of oxygen-doped amorphous carbon material for SO2 catalytic oxidation: A descriptor considering dynamic electron transfer during O2 activation

Carbon-based catalytic oxidation widely exists in contamination control, energy conversion and chemical production, in which amorphous carbon containing heteroatom is commonly used carbocatalyst. Compared with crystalline carbon, small-sized aromatic carbon clusters in amorphous carbon exhibit edge and size effect for catalytic oxidation; however, the activity origin, especially accurate activity descriptor remains to be explored. Herein, using SO2 catalytic oxidation as the probe reaction, a combined computational and experimental investigation was conducted to reveal the activity origin of oxygen-doped amorphous carbon. By density functional theory calculations on various oxygen-doped carbon clusters, a site-specific descriptor considering dynamic electron transfer effect was proposed via combining Fukui function and Mulliken electronegativity, based on which the catalytic activity is found to be determined by both oxygen groups and edges. The configuration with cyclic ether embedded into K-region edge is predicted to own the highest activity with O2 activation and SO2 oxidation barrier as low as 35.4 and 89.3 kJ mol−1. SO2 catalytic oxidation dynamic experiments using model amorphous carbocatalysts further validate the favorable role of ether group and edges. This work demonstrates quantitative descriptor for O2 activation and catalytic oxidation on amorphous carbocatalyst, providing guidance for designing high-performance carbocatalyst considering size and edge effect.

Quantifying the apparent electron transfer number of electrolyte decomposition reactions in anode-free batteries

<h2>Summary</h2> Solid electrolyte interphase (SEI) is pivotal in dictating the stability of anodes in non-aqueous batteries. However, electrolyte decomposition mechanism as an indispensable piece of the puzzle to construct a stable SEI is with few quantitative understandings. Herein, as a quantitative descriptor, the apparent electron transfer number (ETN) is acquired by a facile yet precise methodology in working lithium metal batteries with lithium bis(fluorosulfonyl)imide (LiFSI)-dimethyl carbonate (DMC)-based localized high-concentration electrolyte. Through accurate measurements of the electrolyte evolution and concurrently accumulated inactive Li by electrolyte quantitative nuclear magnetic resonance (ely-qNMR) and titration-qNMR, respectively, the decomposition rates of different electrolyte components and ETNs that define the fate of electrolyte can all be acquired in a "one-stop" fashion. The recognition of ETNs (1.0 for DMC and 5.1 for LiFSI) provides pioneering insights into the electrolyte decomposition mechanism and affords new visions for electrolyte design to promote the continuous rise of non-aqueous rechargeable batteries.

Simple Evaluation of Singlet Fission Couplings for Interacting Dimer Systems

AbstractSinglet fission (SF) could potentially generate two triplet excitations from the absorption of a single photon, which can be applied to significantly enhance the energy conversion efficiency of solar cells. Efficiency of SF for molecular dimers depend on couplings between electronic configurations, however, available theoretical methods for quantitative evaluations of these couplings often require high computational cost and thus it is still difficult to explore geometrical dependence of SF performance for molecular dimers. Herein, we present a direct derivation of the couplings relevant to SF process on the basis of rigorously localized dimeric orbitals. We then systematically show that the SF rates can be correlated with a SF overlap factor that can be easily evaluated from monomeric molecular orbitals. Furthermore, we demonstrate the validity of the overlap factor as a quantitative descriptor of effective SF coupling based on comparative studies on slip‐stacked ethylene and tetracene dimers. With the validity confirmed, we applied the descriptor to investigate a large family of polycyclic aromatic hydrocarbons to reveal dimer geometries that could potentially exhibit highly efficient SF. Our results provide a theoretical tool that could significant increase the speed and reliability of the discovery process for efficient organic SF materials.

The Key Role of Competition between Orbital and Electrostatic Interactions in the Adsorption on Transition Metal Single‐Atom Catalysts Anchored by N‐doped Graphene

AbstractRational design of single‐atom catalyst (SAC) presents a promising route to precise heterogeneous catalysis, yet it requires us to understand the catalytic activity that often can be correlated with the adsorption energies. Here, we investigate the hydrogen adsorption on a series of 3d transition metal (TM) SACs anchored on the N4‐coordination site of N‐doped graphene (MN4/C), and find that the adsorption energies present a volcano curve that violates the d‐band theory. By decomposing the adsorption energies into two distinctive contributions, i. e., the orbital interaction ( ) and electrostatic interaction ( ), we find that it is the competition between the two that results in the volcano curve. We further identify that the trend of is dictated by the TM 4 s orbital that is governed by bonding with the substrate, while is regulated by the charge transfer from TM single‐atom to the N4/C substrate, which originates mainly from the bonding between the TM 3dxy orbital and the substrate. Furthermore, we establish the intrinsic dipole moment of active site as a quantitative descriptor for both and in the adsorption on MN4/C, and apply it to understanding the trends of adsorption energies on 4d and 5d TM‐based MN4/C SACs. Our findings provide deep insights into understanding the adsorption and thus the catalytic activity on TM‐based SACs.

A Hybrid Expert System for Individualized Quantification of Electrical Status Epilepticus During Sleep Using Biogeography-Based Optimization

Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with complex clinical manifestations. It is accompanied by specific electroencephalography (EEG) patterns of continuous spike and slow-waves. Quantifying such EEG patterns is critical to the diagnosis of ESES. While most of the existing automatic ESES quantification systems ignore the morphological variations of the signal as well as the individual variability among subjects. To address these issues, this paper presents a hybrid expert system that dedicates to mimicking the decision-making process of clinicians in ESES quantification by taking the morphological variations, individual variability, and medical knowledge into consideration. The proposed hybrid system not only offers a general scheme that could propel a semi-auto morphology analysis-based expert decision model to a fully automated ESES quantification with biogeography-based optimization (BBO), but also proposes a more precise individualized quantification system to involve the personalized characteristics by adopting an individualized parameters-selection framework. The feasibility and reliability of the proposed method are evaluated on a clinical dataset collected from twenty subjects at Children's Hospital of Fudan University, Shanghai, China. The estimation error for the individualized quantitative descriptor ESES is 0-4.32% and the average estimation error is 0.95% for all subjects. Experimental results show the presented system outperforms existing works and the individualized system significantly improves the performance of ESES quantification. The favorable results indicate that the proposed hybrid expert system for automatic ESES quantification is promising to support the diagnosis of ESES.

Prediction of prostate cancer grade using fractal analysis of perfusion MRI: retrospective proof-of-principle study

ObjectivesMultiparametric MRI has high diagnostic accuracy for detecting prostate cancer, but non-invasive prediction of tumor grade remains challenging. Characterizing tumor perfusion by exploiting the fractal nature of vascular anatomy might elucidate the aggressive potential of a tumor. This study introduces the concept of fractal analysis for characterizing prostate cancer perfusion and reports about its usefulness for non-invasive prediction of tumor grade.MethodsWe retrospectively analyzed the openly available PROSTATEx dataset with 112 cancer foci in 99 patients. In all patients, histological grading groups specified by the International Society of Urological Pathology (ISUP) were obtained from in-bore MRI-guided biopsy. Fractal analysis of dynamic contrast-enhanced perfusion MRI sequences was performed, yielding fractal dimension (FD) as quantitative descriptor. Two-class and multiclass diagnostic accuracy was analyzed using area under the curve (AUC) receiver operating characteristic analysis, and optimal FD cutoffs were established. Additionally, we compared fractal analysis to conventional apparent diffusion coefficient (ADC) measurements.ResultsFractal analysis of perfusion allowed accurate differentiation of non-significant (group 1) and clinically significant (groups 2–5) cancer with a sensitivity of 91% (confidence interval [CI]: 83–96%) and a specificity of 86% (CI: 73–94%). FD correlated linearly with ISUP groups (r2 = 0.874, p < 0.001). Significant groupwise differences were obtained between low, intermediate, and high ISUP group 1–4 (p ≤ 0.001) but not group 5 tumors. Fractal analysis of perfusion was significantly more reliable than ADC in predicting non-significant and clinically significant cancer (AUCFD = 0.97 versus AUCADC = 0.77, p < 0.001).ConclusionFractal analysis of perfusion MRI accurately predicts prostate cancer grading in low-, intermediate-, and high-, but not highest-grade, tumors.Key Points• In 112 prostate carcinomas, fractal analysis of MR perfusion imaging accurately differentiated low-, intermediate-, and high-grade cancer (ISUP grade groups 1–4).• Fractal analysis detected clinically significant prostate cancer with a sensitivity of 91% (83–96%) and a specificity of 86% (73–94%).• Fractal dimension of perfusion at the tumor margin may provide an imaging biomarker to predict prostate cancer grading.

Quantifying Solvophobic Effects in Organic Solvents Using a Hydrocarbon Molecular Balance

We evaluate the use of the cohesive energy density (ced) as a quantitative descriptor for solvophobic effects in organic solvents by measuring ΔGZ/E of the rigid Z- and E-2,2'-diethynyl-9,9'-bifluorenylidene. In line with previously employed balances, solvent-dependent changes in ΔGZ/E are predominantly induced by solvophobic effects, leading to a strong correlation with the solvent's ced. We re-emphasize the role of ceds as quantitative descriptors of solvophobic effects of organic solvents. Our experimental findings are well supported by B3LYP-D3/def2TZVP computations.

Sarc-Graph: Automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytes.

A better fundamental understanding of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) has the potential to advance applications ranging from drug discovery to cardiac repair. Automated quantitative analysis of beating hiPSC-CMs is an important and fast developing component of the hiPSC-CM research pipeline. Here we introduce "Sarc-Graph," a computational framework to segment, track, and analyze sarcomeres in fluorescently tagged hiPSC-CMs. Our framework includes functions to segment z-discs and sarcomeres, track z-discs and sarcomeres in beating cells, and perform automated spatiotemporal analysis and data visualization. In addition to reporting good performance for sarcomere segmentation and tracking with little to no parameter tuning and a short runtime, we introduce two novel analysis approaches. First, we construct spatial graphs where z-discs correspond to nodes and sarcomeres correspond to edges. This makes measuring the network distance between each sarcomere (i.e., the number of connecting sarcomeres separating each sarcomere pair) straightforward. Second, we treat tracked and segmented components as fiducial markers and use them to compute the approximate deformation gradient of the entire tracked population. This represents a new quantitative descriptor of hiPSC-CM function. We showcase and validate our approach with both synthetic and experimental movies of beating hiPSC-CMs. By publishing Sarc-Graph, we aim to make automated quantitative analysis of hiPSC-CM behavior more accessible to the broader research community.

TaxonWorks: Character state matrices and identification tools

TaxonWorks is an integrated web-based application for practicing taxonomists and biodiversity specialists. It is focused on promoting collaboration between researchers and developers. TaxonWorks has a modular structure that enables various components of the application to target specific needs and requirements of different groups of users. Specific areas of interest may include nomenclature-related tasks (Yoder and Dmitriev 2021) designed to help assemble and validate scientific name checklists of a target group of organisms; and collection management tasks, including interfaces to create, filter, and edit collecting events, collection objects, and loans. This presentation focuses on matrix-related tools integrated into TaxonWorks. A matrix, which could either be used for phylogenetic analysis or to build an identification key, is structured as a table where columns represent numerous characters that could be used to describe a set of entities, taxa or specimens (presented as rows of the table). Each cell of the table may contain observations for specific character/entity combinations. TaxonWorks does not generate a table for each a particular matrix—all observations are stored as graphs. This structure allows building of a matrix of an unlimited size as well as reuse of individual observations in multiple matrices. For matrix columns, TaxonWorks supports a variety of different kinds of characters or descriptors: qualitative, presence/absence, quantitative, sample, gene, free text, and media. Each character may have specific properties, for example a qualitative descriptor may have numerous characters states, and a quantitative descriptor may have a measurement unit defined. For an entity in a matrix row, TaxonWorks supports either collection objects (specimens) or taxa as Operational Taxonomic Units (OTU). OTUs could either be linked to nomenclature or be stand alone entities (e.g., representing undescribed species). The matrix, once built, could serve several purposes. A matrix based on qualitative and quantitative characters could be used to build an interactive key (Fig. 1), construct standardized natural language descriptions for each entity, and determine a diagnosis (a minimal set of characters that separate one entity from all others). It could also be exported and used for phylogenetic analysis or to build an interactive key in an external application. TaxonWorks supports export files in several formats, including Nexus, TNT, NeXML. Application Programming Interfaces (API) are also available. A matrix based on media descriptors could be used as a pictorial identification tool (Fig. 2).

Long-Range Forces in Rock-Salt-Type Tellurides and How they Mirror the Underlying Chemical Bonding.

Chemical bonding in main-group IV chalcogenides is an intensely discussed topic, easily understandable because of their remarkable physical properties that predestine these solid-state materials for their widespread use in, for instance, thermoelectrics and phase-change memory applications. The atomistic origin of their unusual property portfolio remains somewhat unclear, however, even though different and sometimes conflicting chemical-bonding concepts have been introduced in the recent years. Here, it is proposed that projecting phononic force-constant tensors for pairs of atoms along differing directions and ranges provide a suitable and quantitative descriptor of the bonding nature for these materials. In combination with orbital-based quantitative measures of covalency such as crystal orbital Hamilton populations (COHP), it is concluded that the well-established many-center and even n-center bonding is an appropriate picture of the underlying quantum-chemical bonding mechanism, supporting the recent proposal of hyperbonded phase-change materials.