Selection Rules Research Articles

Phonon-Mediated Exciton Relaxation in Two-Dimensional Semiconductors: Selection Rules and Relaxation Pathways.

Exciton-phonon coupling (ExPC) is crucial for energy relaxation in semiconductors, yet the first-principles calculation of such coupling remains challenging, especially for two-dimensional (2D) systems. Here, an accurate method for calculating ExPC is developed and applied in exciton relaxation problems in monolayer WSe2. Considering the interplay between the exciton wave functions and electron-phonon coupling (EPC) matrix elements, we find that ExPC shows selection rules distinct from the ones of EPC. By employing the Wannier exciton model, we generalize these selection rules, which state that the angular quantum numbers of the exciton must match the winding numbers of the EPC matrix elements for the ExPC to be allowed. To verify our theory and method, we calculate intervalley exciton relaxation pathways, which agree well with a recent experiment.

Electron Transport through Linear-, Broken-, and Cross-Conjugated Polycyclic Compounds.

Quantum interference (QI) effects offer unique opportunities to modulate charge transport through single molecules. In recent years, several transmission selection rules have been developed to determine constructive and destructive QIs in an intuitive and simple manner, although some of these rules fail for cross-conjugated systems. In this work, we evaluate the performance of distinct transmission rules on a broad series of anthracene and fluorene derivatives with distinctive structural features including linear-, broken-, and cross-conjugation, heteroatoms, and five-membered rings as such species affords a predictive challenge for the qualitative selection rules for QI effects. The electron transport properties and local transmission plots are first evaluated by combining DFT and the nonequilibrium Green function method allowing for an equal-footing comparison of the conductance of the different polycyclic compounds. Our findings are in line with experimental observations on the influence of the type of conjugation and the connectivity to the metallic electrodes on the transport properties. Thus, cross-conjugated systems exhibit reduced conductance values as compared to the linear-conjugated ones, although the transmission is enhanced in the meta-connected junctions. Remarkably, our study reveals that aromatic cores exhibit generally larger zero-bias conductance for a given connectivity, in contrast to the negative aromaticity-conductance relationship found in literature.

Woodward-Hoffmann or Hoffmann-Woodward? Cycloadditions and the Transformation of Roald Hoffmann from a "Calculator" to an "Explainer".

On May 1, 1965, Roald Hoffmann and R. B. Woodward published their second joint communication, Selection Rules for Concerted Cycloaddition Reactions, in the Journal of the American Chemical Society. Herein is presented a historical analysis of Woodward and Hoffmann's determination of the mechanism of cycloadditions. This analysis is based on thorough analyses with Roald Hoffmann of his 1964 and 1965 laboratory notebooks and his archived documents and on numerous in-person, video, and email interviews. This historical research pinpoints several seminal moments in chemistry and in the professional career of Hoffmann. For example, now documented is the fact that Woodward and Hoffmann had no anticipation that their collaboration would continue after the publication of their first 1965 communication on electrocyclizations. Also pinpointed is the moment in Hoffmann's professional and intellectual trajectories that he became a full-fledged, equal collaborator with Woodward and Hoffmann's transition from a "calculator" to an "explainer."

Ancient DNA sheds light on the funerary practices of late Neolithic collective burial in southern France.

The Aven de la Boucle (Corconne, Gard, southern France) is a karst shaft used as a collective burial between 3600 and 2800 cal BCE. The site encompasses the skeletal remains of approximately 75 individuals comprising a large majority of adult individuals, represented by scattered and commingled remains. To date, few studies have explored the potential of ancient DNA to tackle the documentation of Neolithic collective burials, and the funerary selection rules within such structures remain largely debated. In this study, we combine genomic analysis of 37 individuals with archaeo-anthropological data and Bayesian modelling of radiocarbon dates. Through this multidisciplinary approach, we aim to characterize the identity of the deceased and their relationships, as well as untangle the genetic diversity and funerary dynamics of this community. Genomic results identify 76% of male Neolithic individuals, suggesting a marked sex-biased selection. Available data emphasize the importance of biological relatedness and a male-mediated transmission of social status, as the affiliation to a specific male-lineage appears as a preponderant selection factor. The genomic results argue in favour of 'continuous' deposits between 3600 and 2800 BCE, carried out by the same community, despite cultural changes reflected by the ceramic material.

Rule-Ranking-Based Approximate Knowledge Interpolation With Directional Monotonicity.

Fuzzy rule interpolation (FRI) empowers fuzzy rule-based systems (FRBSs) with the ability to infer, even when presented with a sparse rule base where no direct rules are applicable to a given observation. The core principle lies in creating an intermediate fuzzy rule-either interpolated or extrapolated-derived from rules neighboring the observation. Conventionally, the selection of these rules hinges upon distance metrics. While this approach is easy to grasp and has been instrumental in the evolution of various FRI methods, it is burdened by the necessity of extensive distance calculations. This becomes particularly cumbersome when swift responses are imperative or when dealing with large datasets. This article introduces a groundbreaking rule-ranking-based FRI method, termed RT-FRI, which overcomes the constraints of the longstanding distance-centric FRI approach. Instead of relying on distances, RT-FRI harnesses ranking scores for rules and unmatched observation. These scores are produced by amalgamating the antecedent attributes using aggregation functions, thus streamlining the rule selection procedure. Recognizing the rigid monotonicity demands of aggregation functions, a variant-DMRT-FRI-has been introduced to ensure directional monotonicity. Experimental results indicate that RT-FRI emerges as a highly efficient technique, with DMRT-FRI exemplifying a notable balance of accuracy and efficiency.

Programmable generation of counterrotating bicircular light pulses in the multi-terahertz frequency range

The manipulation of solid states using intense infrared or terahertz light fields is a pivotal area in contemporary ultrafast photonics research. While conventional circular polarization has been well explored, the potential of counterrotating bicircular light remains widely underexplored, despite growing interest in theory. In the mid-infrared or multi-terahertz region, experimental challenges lie in difficulties in stabilizing the relative phase between two-color lights and the lack of available polarization elements. Here, we successfully generated phase-stable counterrotating bicircular light pulses in the 14–39 THz frequency range circumventing the above problems. Employing spectral broadening, polarization pulse shaping with a spatial light modulator, and intra-pulse difference frequency generation leveraging a distinctive angular-momentum selection rule within the nonlinear crystal, we achieved direct conversion from near-infrared pulses into the designed counterrotating bicircular multi-terahertz pulses. Use of the spatial light modulator enables programmable control over the shape, orientation, rotational symmetry, and helicity of the bicircular light field trajectory. This advancement provides a novel pathway for the programmable manipulation of light fields, and marks a significant step toward understanding and harnessing the impact of tailored light fields on matter, particularly in the context of topological semimetals.

Rules of acupoint selection in treatment of cancer-related insomnia with acupuncture and moxibustion based on data mining technology.

To analyze the rules of acupoint selection in treatment of cancer-related insomnia with acupuncture and moxibustion by data mining technology. The articles of cancer-related insomnia treated with acupuncture and moxibustion were searched from CNKI, Wanfang, VIP, SinoMed, PubMed, WOS, Cochrane, and Embase databases, from the inception of each database to January 5, 2024. The prescription database of acupuncture and moxibustion for cancer-related insomnia was established. The descriptive analysis was conducted on the use frequency, meridian tropism and distribution of acupoints. Using SPSS Modeler 18.0 Apriori algorithm, the association rules of acupoint prescriptions were analyzed. With Cytoscape3.9.1 software used, the complex network diagram was plotted, and the cluster analysis of high-frequency acupoints was performed by SPSS26.0 software. Forty-one articles were included, and 67 prescriptions were extracted with 89 acupoints involved, and the total use frequency was 447 times. The top 4 acupoints of the high use frequency were Baihui (GV20), Sanyinjiao (SP6), Shenmen (HT7) and Shenting (GV24). The included meridians were the governor vessel, the spleen meridian, the bladder meridian, the conception vessel, the heart meridian and the stomach meridian. The selected acupoints were mostly distributed on the head, the neck and and the upper and lower limbs. The special acupoints of the high use frequency included the five-Shu points, the crossing points and yuan-primordial points. Regarding acupoint combination, GV24, SP6, HT7, and GV20 were highly correlated. The three effective clusters were categorized among the top 12 acupoints of the high use frequency. In treatment of cancer-related insomnia with acupuncture and moxibustion, the principle focuses on supporting the healthy qi, eliminating pathogens, regulating yin and yang, promoting the circulation of the governor vessel for regulating the spirit, and tranquilizing the mind. The core acupoint prescription may includes GV24, SP6, HT7 and GV20；combined with Zusanli (ST36) and Yintang (GV4+) to enhance the therapeutic effect.

Comparative analysis of absorption resonances between carbynes and cyclo [n] carbons

Two approaches are presented here to analyze the absorption resonances between carbynes and cyclo [n] carbons, namely the analytical tight-binding model to calculate the optical selection rules of cumulenic atomic rings and chains and the ab initio time-dependent density functional theory for the optical investigation of polyynic carbon ring and chains. The optical absorption spectra of the carbon ring match that of the finite chain when their eigen energies align following the Nring=2Nchain+2 rule, which states that the number of atoms in an atomic ring Nring is twice the number of atoms on a finite chain Nchain with two additional atoms. Two representative atomic chains are chosen for our numerical calculations, specifically carbynes with N=7and8 carbon atoms as optical resonance spectra match to a recently synthesized carbon ring called cyclo[18]carbon. Despite the mismatch in resonance peaks, molecular orbital transitions of both carbynes N = 7 and 8 and cyclo[18]carbon reveal a wave function symmetry change from inversion to reflection and vice versa for allowed molecular orbital transitions, which results in electron density redistribution along the polyynic carbyne axis or the cyclo[18]carbon circumference. Our investigation of the correlation of optical absorption peaks between carbynes and cyclo [n] carbons is a step towards enhancing the reliability of allotrope identification in advanced molecular device spectroscopy. Moreover, this work could facilitate the non-invasive, rapid and crucial assessment of these sensitive 1D allotropes by providing accurate descriptions of their electronic and optical properties, particularly in controlled synthesis environments.

Impacts of electric gating and divacancies on optical absorption spectra of zigzag buckling silicene nanoribbons

In this study, by combining the tight-binding description with the gradient approximation, we investigated the impacts of electric gating and divacancies on the optical characteristics of zigzag buckling silicene nanoribbons. Our results show that the back-gate electric potential tends to shift the peak structure to higher frequencies in the free-defective structures, while the side-gate electric potentials intensify the intensity of the excitation channels obeying the selection rule ΔJ=even. In particular, applying the potentials in a suitable range can improve the optical absorption efficiency at a certain frequency with the back gate or widen the threshold absorption intensity from Jv=1 to Jc=1 with the side gates. Besides, the defective structures' absorption spectra exhibit richer features than the perfect one, with the appearance of new optical excitations due to the transitions between the local minimum or maximum in the low-energy bands around the Fermi level. Moreover, applying electric gating in defective structures can also tune the absorption spectra with additional features.

Spectral observation of symmetry-protected selection rules for dynamical high-dimensional parity in alignment magnetic resonance

Spectral observation of symmetry-protected selection rules for dynamical high-dimensional parity in alignment magnetic resonance

Infrared Reflection-Absorption Spectroscopy (IRRAS) applied to oxides: Ceria as a case study

Infrared Reflection-Absorption Spectroscopy (IRRAS), a pivotal tool in the study of the surface chemistry of metals, has recently also gained substantial impact for oxide surfaces, despite the inherent challenges originating from their dielectric properties. This review focuses on the application of IRRAS to ceria (CeO2), a metal oxide for which a significant amount of experimental data exists. We elaborate on the differences in optical properties between metals and metal oxides, which result in lower intensity of adsorbate vibrational bands by approximately two orders of magnitude and polarization-dependent shifts of vibrational frequencies. We examine how the surface selection rule, governing IR spectroscopy of adsorbates on metals, contrasts sharply with the behavior of dielectrics where both positive and negative vibrational bands can occur, and how IRRAS can capture vibrations with transition dipole moments oriented parallel to the surface—a capability not feasible on metallic surfaces. Finally, this paper explores the broader implications of these findings for enhancing our understanding of molecule interactions on oxide surfaces, and for using IR spectroscopy for operando studies under technologically relevant conditions.

Regularization methods for the inverse initial value problem for the time-fractional diffusion equation with robin boundary condition ★ ★ The project is supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX23_2549) and the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20190578).

In the article, we focus on the inverse initial value problem for the time-fractional diffusion equation with robin boundary condition on a cylindrical symmetric field. The ill-posedness of this problem is proved. We introduce the modified Landweber iteration method(MLIM), the Truncated singular value decomposition(TSVD) method for solving it and propose a new regularization method, named as the TSVD-modified Landweber iteration method(TMLIM). The error estimates between the exact solution and the regularized approximate solution are presented by using two regularization parameter selection rules. Finally, numerical examples are provided to demonstrate the effectiveness and feasibility of the regularization methods.

Nonlinear-Optical Analogies in Nuclear-Like Soliton Reactions: Selection Rules, Nonlinear Tunneling and Sub-Barrier Fusion–Fission

Abstract The main goal of our study is to reveal unexpected but intriguing analogies arising between optical solitons and nuclear physics, which still remain hidden from us. We consider the main cornerstones of the concept of nonlinear optics of nuclear reactions and the well-dressed repulsive-core solitons. On the base of this model, we reveal the most intriguing properties of the nonlinear tunneling of nucleus-like solitons and the soliton self-induced sub-barrier transparency effect. We describe novel interesting and stimulating analogies between the interaction of nucleus-like solitons on the repulsive barrier and nuclear sub-barrier reactions. The main finding of this study concerns the conservation of total number of nucleons (or the baryon number) in nuclear-like soliton reactions. We show that inelastic interactions among well-dressed repulsive-core solitons arise only when a “cloud” of “dressing” spectral side-bands appears in the frequency spectra of the solitons. This property of nucleus-like solitons is directly related to the nuclear density distribution described by the dimensionless small shape-squareness parameter. Thus the Fourier spectra of nucleus-like solitons are similar to the nuclear form factors. We show that the nuclear-like reactions between well-dressed solitons are realized by “exchange” between “particle-like” side bands in their spectra.

Large-scale multiconfiguration Dirac-Hartree-Fock calculations of atomic data, Landé gj -factors and hyperfine constants of the neutral Rn-211 isotope

We computed the atomic data of ns[K]J ( n = 7, 8, 9), np[K]J ( n = 7, 8, 9), nd[K]J ( n = 6, 7, 8, 9), and nf[K]J ( n = 5, 6, 7, 8) and 5g[K]J autoionized Rydberg spectra of the neutral radon-211 isotope. The computations are carried out by using the Multiconfiguration Dirac-Hartree-Fock method (MCDHF) together with the relativistic configuration (RCI) approach. The convergence of the obtained results is monitored by incorporating relativistic electron-electron correlation, the Breit-interaction effect, self-energy, and vacuum-polarization corrections. As a result, we acquired the energy levels, transition rates, oscillator strengths, Landé gJ -factors and magnetic dipole hyperfine constants. The transition parameters between the levels belonging to different series are computed for all allowed electric dipole transition selection rules. The present results are in very good agreement with other experimental and theoretical data available in the literature database. The present data could be useful in predicting spectral lines of radon via astrophysics and stellar spectroscopy.

Strain-tuned electronic and valley-related properties in Janus monolayers of SWSiX2 (X = N, P, As)

Abstract Exploring novel two-dimensional (2D) valleytronic materials has an essential impact on the design of spintronic and valleytronic devices. Our first principles calculation results reveal that the Janus SWSiX2 (X = N, P, As) monolayer has excellent dynamical and thermal stability. Owing to strong spin-orbit coupling (SOC), the SWSiX2 monolayer exhibits a valence band spin splitting of up to 0.49 eV, making it promising 2D semiconductor for valleytronic applications. The opposite Berry curvatures and optical selection rules lead to the coexistence of valley and spin Hall effects in the SWSiX2 monolayer. Moreover, the optical transition energies can be remarkably modulated by the in-plane strains. Large tensile (compressive) inplane strains can achieve spin flipping in the SWSiN2 monolayer, and induce both SWSiP2 and SWSiAs2 monolayers transit from semiconductor to metal. Our research provides new 2D semiconductor candidates for designing high-performance valleytronic devices.

GWO+RuleFit: rule-based explainable machine-learning combined with heuristics to predict mid-treatment FDG PET response to chemoradiation for locally advanced non-small cell lung cancer.

Objective.Vital rules learned from fluorodeoxyglucose positron emission tomography (FDG-PET) radiomics of tumor subregional response can provide clinical decision support for precise treatment adaptation. We combined a rule-based machine learning (ML) model (RuleFit) with a heuristic algorithm (gray wolf optimizer, GWO) for mid-chemoradiation FDG-PET response prediction in patients with locally advanced non-small cell lung cancer.Approach.Tumors subregions were identified using K-means clustering. GWO+RuleFit consists of three main parts: (i) a random forest is constructed based on conventional features or radiomic features extracted from tumor regions or subregions in FDG-PET images, from which the initial rules are generated; (ii) GWO is used for iterative rule selection; (iii) the selected rules are fit to a linear model to make predictions about the target variable. Two target variables were considered: a binary response measure (ΔSUVmean ⩾ 20% decline) for classification and a continuous response measure (ΔSUVmean) for regression. GWO+RuleFit was benchmarked against common ML algorithms and RuleFit, with leave-one-out cross-validated performance evaluated by the area under the receiver operating characteristic curve (AUC) in classification and root-mean-square error (RMSE) in regression.Main results.GWO+RuleFit selected 15 rules from the radiomic feature dataset of 23 patients. For treatment response classification, GWO+RuleFit attained numerically better cross-validated performance than RuleFit across tumor regions and sets of features (AUC: 0.58-0.86 vs. 0.52-0.78,p= 0.170-0.925). GWO+Rulefit also had the best or second-best performance numerically compared to all other algorithms for all conditions. For treatment response regression prediction, GWO+RuleFit (RMSE: 0.162-0.192) performed better numerically for low-dimensional models (p= 0.097-0.614) and significantly better for high-dimensional models across all tumor regions except one (RMSE: 0.189-0.219,p< 0.004).Significance. The GWO+RuleFit selected rules were interpretable, highlighting distinct radiomic phenotypes that modulated treatment response. GWO+Rulefit achieved parsimonious models while maintaining utility for treatment response prediction, which can aid clinical decisions for patient risk stratification, treatment selection, and biologically driven adaptation. Clinical trial: NCT02773238.

Smoothed semicovariance estimation for portfolio selection

AbstractDownside risk measures, such as semivariance, are essential for evaluating investment risk. Focusing on semivariance allows investors to emphasize loss mitigation without considering upside volatility as risk. However, minimizing the semivariance of a portfolio is an analytically intractable and numerically challenging problem due to the endogeneity of the parameters in the semicovariance matrix. We introduce a methodology for consistent estimation of the portfolio semivariance based on a smooth approximation of the empirical semicovariance matrix. Differently from existing methods, the new estimator does not rely on biased surrogate semicovariance models and enables the treatment of large problems with many assets. The extent of smoothing is determined by a single tuning constant, which allows our method to span an entire set of optimal portfolios with limit cases represented by the minimum semivariance and the minimum variance portfolios. The methodology is implemented through an iteratively reweighted algorithm, which is computationally efficient for high-dimensional problems with many assets. Our numerical studies confirm the theoretical convergence of the smoothed semivariance estimator to the traditional sample semivariance. The resulting minimum smoothed semivariance portfolio performs well in- and out-of-sample compared to other popular selection rules.

Fast linear model trees by PILOT

Linear model trees are regression trees that incorporate linear models in the leaf nodes. This preserves the intuitive interpretation of decision trees and at the same time enables them to better capture linear relationships, which is hard for standard decision trees. But most existing methods for fitting linear model trees are time consuming and therefore not scalable to large data sets. In addition, they are more prone to overfitting and extrapolation issues than standard regression trees. In this paper we introduce PILOT, a new algorithm for linear model trees that is fast, regularized, stable and interpretable. PILOT trains in a greedy fashion like classic regression trees, but incorporates an L2 boosting approach and a model selection rule for fitting linear models in the nodes. The abbreviation PILOT stands for PIecewise Linear Organic Tree, where ‘organic’ refers to the fact that no pruning is carried out. PILOT has the same low time and space complexity as CART without its pruning. An empirical study indicates that PILOT tends to outperform standard decision trees and other linear model trees on a variety of data sets. Moreover, we prove its consistency in an additive model setting under weak assumptions. When the data is generated by a linear model, the convergence rate is polynomial.

Selection of Single-Analyte Delta Check Rules with Logistic Regression for Detection of Intravenous Fluid Contamination in a Clinical Chemistry Laboratory.

The conventional single-analyte delta check, utilized for identifying intravenous fluid contamination and other preanalytical errors, is known to flag many specimens reflecting true patient status changes. This study aimed to derive delta check rules that more accurately identify contamination. Results for calcium, creatinine, glucose, sodium, and potassium were retrieved from 326 103 basic or comprehensive metabolic panels tested between February 2021 and January 2022. In total, 7934 specimens showed substantial result changes, of which 1489 were labeled as either contaminated or non-contaminated based on chart review. These labeled specimens were used to derive logistic regression models and to select the most predictive single-analyte delta checks for 4 common contaminants. Their collective performance was evaluated using a test data set from October 2023 comprising 14 717 specimens. The most predictive single-analyte delta checks included a calcium change by ≤-24% for both saline and Plasma-Lyte A contamination, a potassium increase by ≥3.0 mmol/L for potassium contamination, and a glucose increase by ≥400 mg/dL (22.2 mmol/L) for dextrose contamination. In the training data sets, multi-analyte logistic regression models performed better than single-analyte delta checks. In the test data set, logistic regression models and single-analyte delta checks demonstrated collective alert rates of 0.58% (95% CI, 0.46%-0.71%) and 0.60% (95% CI, 0.49%-0.74%), respectively, along with collective positive predictive values of 79% (95% CI, 70%-89%) and 77% (95% CI, 68%-87%). Single-analyte delta checks selected by logistic regression demonstrated a low false alert rate.

Topological phonons and thermal conductivity of two-dimensional Dirac semimetal PtN4C2

PtN4C2 is a recently predicted two-dimensional (2D) Dirac semimetal exhibiting significant topological quantum spin and valley Hall effects. Herein, we explore its topological phonon states and thermal transport properties from first-principles calculations. In terms of symmetry arguments, we predict the existence of multiple topologically protected phononic Dirac points in the frequency range of 0–20 THz, which are evidenced by the relevant irreducible representations and calculated nontrivial edge states on the (100) surface. In addition, anharmonic phonon renormalization is found to play a significant role in determining the phonon spectrum, especially for the out-of-plane flexural acoustic (ZA) branch. Moreover, we explicitly consider three-phonon scattering, four-phonon scattering, and phonon renormalization to predict the lattice thermal conductivity κl of PtN4C2, by solving the Boltzmann transport equation. With the incorporation of four-phonon scattering, we predict that the intrinsic κl is 68 W/mK at room temperature, which is reduced by about 45% as compared to the value obtained by only including three-phonon scattering. This reduction is found to arise mainly from the ZA phonons, whose contribution to κl is significantly suppressed by four-phonon scattering, due to the restriction of the mirror symmetry-induced selection rules on three-phonon processes. We also unveil that the presence of Dirac points steepens the surrounding phonon dispersion and thus greatly increases the phonon group velocities, thereby making a considerable contribution to κl. This work establishes a thorough understanding of intrinsic topological phonons and thermal transport in PtN4C2 and highlights the importance of phonon renormalization and higher-order anharmonicity in determining the phonon transport properties of 2D materials.