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The development and construction of thrust faults in mountain front areas are quite complicated, causing interpretation difficulties with electrical resistivity. To address these difficulties, an optimal stratification method involving magnetotellurics (MT) was applied, based on Fisher's clustering method for continuous data. The feasibility and effectiveness of this method are verified by applying it to the MT exploration data in Qiangtang Basin, Qinghai-Tibet Plateau, China. The results show that the optimal stratification method can improve the resolution of the resistivity model effectively in areas with complex structures. The MT inversion section after optimal stratification reflects the stratum interface, fault and structure style more directly and can be used for comparison with seismic data. The Fisher segmentation method can be applied to the interpretation of the MT data as a supplementary method, especially in the complicated structural belts, areas in which the geological structure and deformation information cannot be recognized effectively by conventional methods.

Inheritance classification is an interactive multi-attribute pattern recognition method. In the interpretation of geophysical data, combined with the advantages of multiple attributes of gravity, magnetic and electromagnetic in the identification of special lithologic bodies, complex reservoirs and other targets, the heritance classification method can be used to qualitatively predict the distribution of favorable target. Multiple data complementing each other and multi-attribute intelligent classification can effectively reduce the multiple solution of geological interpretation.

A real-space genetic algorithm for the optimization of defect structures embedded in bulk crystalline materials is developed. The purpose of this method is to enable automated prediction of stable structures for a range of embedded clusters, including radiation induced defect clusters, dopant clusters, and small precipitates. The method is applied to the prediction of small interstitial clusters in cubic SiC, BCC Fe, and BCC Fe–Cr random alloys for radiation damage applications. The performance of the method is analyzed and compared to alternative techniques such as basin hopping. The technique is able to reproduce small-size defects that had been previously identified as stable or metastable structures as well as predict new mid-size defects. The structure optimization program (StructOpt) developed in this study is available under open source licensing as part of the MAterials Simulation Toolkit (MAST) and can be obtained from https://pypi.python.org/pypi/MAST .

We process the standard 30 s, static GPS data and the 1 s, high-rate GPS (HRGPS) data provided by the Crustal Movement Observation Network of China with GAMIT/GLOBK software package, and obtain the co-seismic displacements of near field and far field, and the epoch-by-epoch time series of HRGPS during Lushan earthquake. GPS data from about 20 sites in Sichuan province, which located between 40 and 450 km from the epicenter, are analyzed so as to study the characteristics of the static displacements and the dynamic crustal deformations, with periods ranging from several minutes to over a month. The result shows that: the static displacements caused by Lushan earthquake are limited to several centimeters; the nearest station SCTQ at 43 km from the epicenter has the largest static displacement of about 2 cm, while the other stations generally have insignificant displacements of less than 5 mm. the stations in the east of Sichuan–Yunnan region shifts 5–10 mm toward the southwest, and the stations in the middle-west of Sichuan Basin moves indistinctively 1–2 mm toward the northwest; station SCTQ has the largest kinematic displacement of about 4 and 3 cm peak-to-peak on the north and east component, respectively, and is much greater than the static permanent displacement; for the stations located at a distance greater than 150 km from the epicenter, the kinematic motions are generally insignificant; exceptionally, station SCNC and station SCSN in central Sichuan Basin have significant kinematic motions although they are more than 200 km away from the epicenter.

Heulandite and clinoptilolite form the most abundant family of natural zeolite crystals. The topology of both of them is characterized by the framework type HEU. Despite many studies on these crystals, the mineral assignment to a zeolite as heulandite or clinoptilolite is still controversial and unresolved today. Based on a machine learning clustering analysis of crystallographic data of zeolite crystals, we show that zeolites belonging to the HEU framework type are divided into three groups of minerals instead of two. Two of the groups, HEU-h and HEU-c, contain crystals with names heulandite and clinoptilolite, respectively. The third newly proposed group HEU-m is composed of mixed zeolites named under both traditional names. The grouping is based on the EM algorithm and a set of descriptors built from data collected in the NIST/FIZ Inorganic Crystal Structure Database. Verification of the division of the HEU family into three groups is provided based on a battery of machine learning tests.

Informatics approaches play an increasingly important role in the design of new materials. In this work we apply unsupervised statistical learning for identifying four framework-type attractors of zeolite crystals in which several of the zeolite framework types are grouped together. Zeolites belonging to these super-classes manifest important topological, chemical and physical similarities. The zeolites form clusters located around four core framework types: LTA, FAU, MFI and the combination of EDI, HEU, LTL and LAU. Clustering is performed in a 9-dimensional space of attributes that reflect topological, chemical and physical properties for each individual zeolite crystalline structure. The implemented machine learning approach relies on hierarchical top-down clustering approach and the expectation maximization method. The model is trained and tested on ten partially independent data sets from the FIZ/NIST Inorganic Crystal Structure Database.

Zeolites are microporous crystalline materials with highly regular framework structures consisting of molecular-sized pores and channels. The characteristic framework type of a zeolite is conventionally defined by combining information on its coordination sequences, vertex symbols, tiling, and transitivity information. Here we present a novel knowledge-based approach for zeolite framework type classification. We show the predicting abilities of a machine learning model that uses a nine-dimensional feature vector including novel topological descriptors obtained by computational geometry techniques, together with selected physical and chemical properties of zeolite crystals. Trained on the crystallographic structures of known zeolites, this model predicts the framework types of zeolite crystals with very high accuracy.

The Cenozoic contractional deformation in the transitional belt between Kuche Depression and South Tianshan Uplift can be hardly deciphered by the typical “A-type” subduction model with the structural features like geological outcrop, seismic data, well-log, and CEMP (Continuous Electromagnetic Profile) data. This article advanced a “nonsubduction” contractional deformation model with “delaminate contraction and vertical stack”. The former, “delaminate contraction”, means that the basement and the cover, even multilevel cover, are of their own distinct contractional structural styles. The latter, “vertical stack”, means the strong deformation zones within various levels are stacked up vertically. No regional detachment fault developed. Detachment folds were developed in shallower cover, whereas fault system assembled with reverse fault, thrust, and inverse fault or normal fault developed in the lower cover and basement. The cover folds express structure pattern of a closed anticline combined with an opened syncline. The asymmetric anticline detached within salt rock of Eocene or coal strata of Jurassic and was cut off by a break thrust in the steep limb. A series of basement-involved thrust with high-angle dipping to South Tianshan Uplift dominate the contractional deformation in the basement. A miniscale imbricate wedge thrust system developed in the footwall of basement-involved thrust with high-angle dip and a faulted-anticline with basement-cored developed in the hang-wall. Most of the fault system in the lower level disappeared toward the salt rock of Eocene or coal strata of Jurassic. The high-angle basement-involved thrust tip in the core of detachment anticline is in the shallower level so that the salt rock of Eocene or coal strata of Jurassic might be an important transfer level. The high-angle basement-involved thrust could be an inverse fault utilizing the preexisting normal fault and leads to the local structure deformation, thus attributing to the dynamics of vertical shearing resulted from the uplift of Southern Tianshan mountains.

Application of knowledge discovery methods to crystal structure databases is an emerging research area of materials science that is playing an important role in facilitating data analysis. This study is aimed at combining computational geometry methods with machine learning algorithms for classification of inorganic solid materials of known structure. Zeolite crystals are used for the pilot study where a model based on the topology is developed for classification of the compound by mineral name and by zeolite framework type. The topological descriptors are derived from the Delaunay tessellation for 220 zeolites contained in the inorganic crystal structure database. This zeolite-structure-predictor (ZSP) is trained for classifying this set of selected zeolite crystals into 22 different types of minerals and into 13 framework types. The ZSP is based on the random forest algorithm and contains attributes of Delaunay simplex properties such as tetrahedrality index, frequency of simplex occurrence, and site occupation probability. The ZSP is able to obtain classification in this multitude of classes with more than 81% of correctly classified instances based on framework type. The model shows that the classification into framework types is superior, and that the classification into mineral names is not structurally unique.

Uncapped linear Cn clusters have been studied with hybrid density functional theory focusing on the geometry, HOMO−LUMO gap, and the longitudinal optical (LO) vibrational mode. The latter two correlate well with the bond length alternation (BLA) of the optimized geometry. Due to end effects, the BLA is not constant along the chains. The degree of BLA changes continuously with increasing n: starting with essentially nonalternating structures (cumulenic), then turning into strongly alternating (acetylenic) structures. This transition has not yet been described or characterized and occurs at relatively large values of n. The implications for the widely observed characteristic LO vibrational bands of linear carbon clusters are discussed.

Building ladder polymers provides an alternative way to design intrinsically low band gap conjugated polymers. Using conventional conjugated polymers, polyacetylene, polydiacetylene and polytriacetylene as sidepieces, we propose a series of novel types of ladder polymers with conjugated acetylenic blocks (−C⋮C−)m serving as crosspieces. Periodic boundary conditions density functional calculations are performed to investigate the effect of the acetylenic cross-couplings between the two sidepieces. We predict the band gap of the acetylenic coupled (AC) ladder polymers can be reduced to less than 0.3 eV without doping, significantly reduced compared with the parent sidepiece polymers at the same theoretical level. The effect of varying the length and spacing of the crosspieces along the sidepieces is investigated in order to maximize the effect of the gap reduction. Unusual electronic and optical properties are expected from these series of ladder conjugated polymers.

We investigate the molecular beam epitaxy (MBE) growth of GaAs1-xBix film using density functional theory with spin-orbit coupling to understand the growth of this film, especially the mechanisms of Bi incorporation. We study the stable adsorption structures and kinetics of the incident molecules (As₂ molecule, Ga atom, Bi atom, and Bi₂ molecule) on the (2 x 1)-Gasub||Bi surface and a proposed q(1 x 1)-Gasub||AsAs surface has a quasi-(1 x 1) As layer above the Ga-terminated GaAs substrate and a randomly oriented As dimer layer on top. We obtain the desorption and diffusion barriers of the adsorbed molecules and also the reaction barriers of three key processes related to Bi evolution, namely, Bi incorporation, As/Bi exchange, and Bi clustering. The results help explain the experimentally observed dependence of Bi incorporation on the As/Ga ratio and growth temperature. Furthermore, we find that As₂ exchange with Bi of the (2 x 1)-Gasub||Bi surface is a key step controlling the kinetics of the Bi incorporation. Finally, we explore two possible methods to enhance the Bi incorporation, namely, replacing the MBE growth mode from codeposition of all fluxes with a sequential deposition of fluxes and applying asymmetric in-plane strain to the substrate.

The two bond length alternation related backbone carbon–carbon stretching Raman active normal modes of polyacetylene are notoriously difficulty to predict theoretically. We apply our new linear/exponential scaled quantum mechanical force field scheme to tackle this problem by exponentially adjusting the decay of the coupling force constants between backbone stretchings based on their distance which extends over many neighbors. With transferable scaling parameters optimized by least squares fitting to the experimental vibrational frequencies of short oligoenes, the scaled frequencies of trans-polyacetylene and its isotopic analogs agree very well with experiments. The linear/exponential scaling scheme is also applicable to the cis-polyacetylene case.

The smallest possible inner tube diameter in a double walled carbon nanotube is the zero diameter inner tube, in other words, an infinite linear carbon chain. In this work, we present a first principles study of the vibrational properties of the infinite carbon chain, employing a novel linear/exponential scaling scheme based on the intrinsic behavior of the long range force constant couplings in quasi one-dimensional chains. The longitudinal optical Raman active frequency is predicted at 1870-1877 cm -1 , in contrast to the widely accepted values in the 2000-2200 cm -1 range. Our results provide further evidence for the assignment of the characteristic Raman peaks near 1850 cm -1 of the recently discovered long linear carbon chains encapsulated inside multi-walled or double walled carbon nanotubes.

The bond length alternation (BLA) and energy band gap of polyyne are investigated by various first-principles theories, including Hartree-Fock, MP2, hybrid, and nonhybrid density functional theories. Both solid-state calculations utilizing periodic boundary conditions on polymers and molecular quantum mechanical calculations on extra-long oligomers were performed with consistent results. By validation on similar linear conjugated polymers, polyacetylene and polydiacetylene, the combination of hybrid-DFT schemes, B3LYP//BHandHLYP or B3LYP//KMLYP, is shown to give the best predictions for both geometry and band gap of polyyne based on available experimental data. We conclude that the best estimate of the BLA of polyyne is about 0.13 A and that of the band gap is about 2.2 eV.

Various molecular and solid state quantum chemical methods are compared for their performance in predicting the bandgaps of conjugated polymers. Extrapolations based on oligomers provide an alternative way to calculate bandgaps. A combination of semi-empirical geometry optimization followed by a hybrid functional density functional theory (DFT) calculation for the energy levels of molecular oligomers provides a reliable and computationally efficient method for predicting bandgaps of a group of diverse conjugated polymers.

Technological applications of novel metastable materials are frequently inhibited by abundant defects residing in these materials. Using first-principles methods we investigate the point defect thermodynamics and phase segregation in the technologically-important metastable alloy GaAsBi. Our calculations predict defect energy levels in good agreement with abundant previous experiments and clarify the defect structures giving rise to these levels. We find that vacancies in some charge states become metastable or unstable with respect to antisite formation, and this instability is a general characteristic of zincblende semiconductors with small ionicity. The dominant point defects degrading electronical and optical performances are predicted to be As$_G$$_a$, Bi$_G$$_a$, Bi$_G$$_a$+Bi$_A$$_s$, As$_G$$_a$+Bi$_A$$_s$, V$_G$$_a$ and V$_G$$_a$+Bi$_A$$_s$, of which the first-four and second-two defects are minority-electron and minority-hole traps, respectively. V$_G$$_a$ is also found to play a critical role in controlling the metastable Bi supersaturation through mediating Bi diffusion and clustering. To reduce the influences of these deleterious defects, we suggest shifting the growth away from As-rich condition and/or using hydrogen passivation to reduce the minority-carrier traps. We expect this work to aid in the applications of GaAsBi to novel electronic and optoelectronic devices, and shine a light on controlling the deleterious defects in other metastable materials.

The molecular structure of the tungsten-benzylidyne complex trans-W(≡CPh)(dppe)(2)Cl (1; dppe = 1,2-bis(diphenylphosphino)ethane) in the singlet (d(xy))(2) ground state and luminescent triplet (d(xy))(1)(π*(WCPh))(1) excited state (1*) has been studied using X-ray transient absorption spectroscopy, X-ray crystallography, and density functional theory (DFT) calculations. Molecular-orbital considerations suggest that the W-C and W-P bond lengths should increase in the excited state because of the reduction of the formal W-C bond order and decrease in W→P π-backbonding, respectively, between 1 and 1*. This latter conclusion is supported by comparisons among the W-P bond lengths obtained from the X-ray crystal structures of 1, (d(xy))(1)-configured 1(+), and (d(xy))(2) [W(CPh)(dppe)(2)(NCMe)](+) (2(+)). X-ray transient absorption spectroscopic measurements of the excited-state structure of 1* reveal that the W-C bond length is the same (within experimental error) as that determined by X-ray crystallography for the ground state 1, while the average W-P/W-Cl distance increases by 0.04 Å in the excited state. The small excited-state elongation of the W-C bond relative to the M-E distortions found for M(≡E)L(n) (E = O, N) compounds with analogous (d(xy))(1)(π*(ME))(1) excited states is due to the π conjugation within the WCPh unit, which lessens the local W-C π-antibonding character of the π*(WCPh) lowest unoccupied molecular orbital (LUMO). These conclusions are supported by DFT calculations on 1 and 1*. The similar core bond distances of 1, 1(+), and 1* indicates that the inner-sphere reorganization energy associated with ground- and excited-state electron-transfer reactions is small.

Knowledge of the framework topology of zeolites is essential for multiple applications. Framework type determination relying on the combined information of coordination sequences and vertex symbols is appropriate for crystals with no defects. In this work we present an alternative machine learning model to classify zeolite crystals according to their framework types. The model is based on an eighteen-dimensional feature vector generated from the crystallographic data of zeolite crystals that contains topological, physical-chemical and statistical descriptors. Trained with sufficient known data, this model predicts the framework types of unknown zeolite crystals within 1-2 % error and shows to be better suited when dealing with real zeolite crystals, all of which always have geometrical defects even when the structure is resolved by crystallography.

The energetics of even and odd linear C(n) carbon chain clusters are investigated by hybrid density functional theory (DFT) calculations. These molecular species are especially interesting due to their recent observation inside carbon nanotubes by polarized resonant Raman spectroscopy and high-resolution transmission electron microscopy (HRTEM) by different research groups. Neutral, anionic and dianionic carbon chains were studied with sizes up to n=75, although most presented calculations are limited to nor= 24. Aggregation into longer chains is favored for neutral and anionic chains of any size. The barrier to aggregation of 2C(n)--C(2n) is of the order of 40-20 kcal mol(-1), which gradually decreases with increasing chain size, n. These barriers can be overcome during the high temperature synthesis or annealing conditions, but not when cooled down for the HRTEM and Raman experiments. Therefore, in addition to the already observed long chains also shorter chains should be observable under appropriate conditions inside carbon nanotubes.

The properties of an infinite carbon chain (polyyne), an allotropic form of elemental carbon, are of importance in materials science as well as astronomy. The Raman active longitudinal optical (LO) frequencies are calculated with first-principles methods for oligoynes and polyyne and compared with experiments. Since traditional force constant scaling schemes fail in this case, we introduced a linear/exponential scaling scheme based on the exponential behavior of the carbon−carbon bond stretching force constant couplings in quasi-one-dimensional conjugated chains. The LO Raman active frequency is predicted at 1870−1877 cm-1. Our results provides further evidence for the assignment of the characteristic Raman peaks near 1850 cm-1 of the recently discovered long linear carbon chains encapsulated inside multiwalled or double-walled carbon nanotubes.

The physical properties of a linear carbon chain encapsulated within single-walled carbon nanotubes are investigated with density-functional theory using periodic boundary conditions. The dominant feature of an isolated carbon chain is the Peierls dimerization and the opening of a Peierls gap. The two weakly interacting subsystems (infinite carbon chain and nanotube) establish a common Fermi level, resulting in charge transfer (CT) which leads to a metallic combined system with a high density of states at the Fermi level. The rigid band model provides useful insights. Unusual physics arises from the effects of CT and chain-tube orbital hybridization which both tend to suppress the Peierls dimerization. Implications for the observed Raman spectrum of the chain-nanotube system are discussed.

The physical properties of several kinds of single walled carbon nanotubes containing a single carbon chain in their interior are investigated with density functional theory, using the Vienna ab initio Simulation Package (VASP). The optimized geometry and the electronic band structure are both examined, and compared to the results of the isolated subsystems: the isolated carbon chain and the isolated nanotube. We find bondlength alternation in the optimized geometry of the isolated chain, as well as a gap in the band structure, clear signs of Peierls distortion. In the combined systems, hybridization and charge transfer are found between the tube and the chain, resulting in a partial or complete breakdown of the Peierls distortion of the carbon chain. The combined systems are always predicted to be metallic, even if both subsystems are semiconductors, and even if the chain still exhibits some bond length alternation.

In this work a structural characterization of zeolite crystals is performed by identifying the framework type to which each zeolite belongs. The framework type is assigned for 1433 zeolitedatabase entries in the FIZ/NIST Inorganic CrystalStructureDatabase (ICSD) populating 95 framework types. These entries correspond to both natural and synthetic zeolites. Each ICSD entry is based on published work containing crystallographic information of the zeolite crystalline structure and some physical and chemical data. Today, the Structure Commission of the International Zeolite Association recognizes crystalline materials as belonging to the “zeolite” family only if they possess one of the approved framework types by the organization. Such information is of fundamental importance for identifying zeolites, for reference, for zeolite standards, for supporting the discovery of new zeolites, and for crystalline substance selection based on application. Unfortunately, framework-type information is not contained in the ICSD records. The long term goal of this work is filling such gap. Although the ICSD contains an extensive collection of zeolites, inclusion of zeolites belonging to the 191 accepted framework types could substantially expand such collection. The structural determination was achieved via several structuralanalysis methods based on numerical-computer implementations.

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