Nuanced dilute doping strategy enables high-performance GeTe thermoelectrics.

In thermoelectrics, doping is essential to augment the figure of merit. Traditional strategy, predominantly heavy doping, aims to optimize carrier concentration and restrain lattice thermal conductivity. However, this tactic can severely hamper carrier transport due to pronounced point defect scattering, particularly in materials with inherently low carrier mean-free-path. Conversely, dilute doping, although minimally affecting carrier mobility, frequently fails to optimize other vital thermoelectric parameters. Herein, we present a more nuanced dilute doping strategy in GeTe, leveraging the multifaceted roles of small-size metal atoms. A mere 4% CuPbSbTe3 introduction into GeTe swiftly suppresses rhombohedral distortion and optimizes carrier concentration through the aid of Cu interstitials. Additionally, the formation of multiscale microstructures, including zero-dimensional Cu interstitials, one-dimensional dislocations, two-dimensional planar defects, and three-dimensional nanoscale amorphous GeO2 and Cu2GeTe3 precipitates, along with the ensuing lattice softening, contributes to an ultralow lattice thermal conductivity. Intriguingly, dilute CuPbSbTe3 doping incurs only a marginal decrease in carrier mobility. Subsequent trace Cd doping, employed to alleviate the bipolar effect and align the valence bands, yields an impressive figure-of-merit of 2.03 at 623 K in (Ge0.97Cd0.03Te)0.96(CuPbSbTe3)0.04. This leads to a high energy-conversion efficiency of 7.9% and a significant power density of 3.44 W cm-2 at a temperature difference of 500 K. These results underscore the invaluable insights gained into the constructive role of nuanced dilute doping in the concurrent tuning of carrier and phonon transport in GeTe and other thermoelectric materials.

High Pressure Drives Microstructure Modification and zT Enhancement in Bismuth Telluride-Based Alloys.

Manipulating and integrating the microstructures at different scales is crucial to tune the electrical and thermal properties of a given compound. High-pressure sintering can modify the multiscale microstructures and thus empower the cutting-edge thermoelectric performance. In this work, the high-pressure sintering technique followed by annealing is adopted to prepare Gd-doped p-type (Bi0.2Sb0.8)2(Te0.97Se0.03)3 alloys. First, the high energy of high-pressure sintering promotes the reduction of grain size, thus increasing the content of 2D grain boundaries. Next, high-pressure sintering induces strong interior strain, where 1D dense dislocations are generated near the strain field. More interestingly, the rare-earth element Gd with a high melting temperature is dissolved into the matrix via high-pressure sintering, thus promoting the formation of 0D extrinsic point defects. This concurrently improves the carrier concentration and density-of-state effective mass, resulting in an enhanced power factor. In addition, the integrated 0D point defects, 1D dislocations, and 2D grain boundaries by high-pressure sintering strengthen phonon scattering, thereby achieving a low lattice thermal conductivity of 0.5 Wm-1 K-1 at 348 K. Consequently, a maximum zT value of ∼1.1 at 348 K is achieved in the 0.4 at % Gd-doped (Bi0.2Sb0.8)2(Te0.97Se0.03)3 sample. This work demonstrates that high-pressure sintering enables microstructure modification to enhance the thermoelectric performance of Bi2Te3-based and other bulk materials.

Two-step phase manipulation by tailoring chemical bonds results in high-performance GeSe thermoelectrics.

In thermoelectrics, phase engineering serves a crucial function in determining the power factor by affecting the band degeneracy. However, for low-symmetry compounds, the mainstream one-step phase manipulation strategy, depending solely on the valley or orbital degeneracy, is inadequate to attain a high density-of-states effective mass and exceptional zT. Here, we employ a distinctive two-step phase manipulation strategy through stepwise tailoring chemical bonds in GeSe. Initially, we amplify the valley degeneracy via CdTe alloying, which elevates the crystal symmetry from a covalently bonded orthorhombic to a metavalently bonded rhombohedral phase by significantly suppressing the Peierls distortion. Subsequently, we incorporate Pb to trigger the convergence of multivalence bands and further enhance the density-of-states effective mass by moderately restraining the Peierls distortion. Additionally, the atypical metavalent bonding in rhombohedral GeSe enables a high Ge vacancy concentration and a small band effective mass, leading to increased carrier concentration and mobility. This weak chemical bond along with strong lattice anharmonicity also reduces lattice thermal conductivity. Consequently, this unique property ensemble contributes to an outstanding zT of 0.9 at 773 K for Ge0.80Pb0.20Se(CdTe)0.25. This work underscores the pivotal role of the two-step phase manipulation by stepwise tailoring of chemical bonds in improving the thermoelectric performance of p-bonded chalcogenides.

Understanding green supply chain information integration on supply chain process ambidexterity: The mediator of dynamic ability and the moderator of leaders' networking ability.

Based on dynamic capability theory, this paper aims to explore the influence of green supply chain information integration (IT system integration and information sharing) on supply chain process ambidexterity (efficiency and flexibility) and expounds on the mediation mechanisms (supply chain dynamic capability) and the boundary condition (networking ability) between the two. Through the sample data test research model of 351 managers of manufacturing enterprises, it is found that information technology (IT) system integration can effectively promote the information sharing level of green supply chain enterprises. Supply chain dynamic capability partially mediates the influence of IT system integration and information sharing on supply chain process ambidexterity. Moreover, networking ability positively moderates the relationship between absorptive capacity, innovation capacity, and supply chain process ambidexterity, but does not play a significant role in the relationship between adaptive capacity and supply chain process ambidexterity.

Research on paths of opportunistic behavior avoidance and performance improvement in food supply chain from the perspective of social control.

It is essential to avoid opportunistic behaviors of food supply chain members to guarantee food safety and sustainable supply. This research adopted the perspective of supply chain membership governance to discuss the critical mechanisms of opportunistic behavior avoidance and performance improvement in the food supply chain. Two information-sharing mechanisms (information sharing with customers and information sharing with suppliers) were used as mediating variables to explore the mechanisms of how social control, information sharing, and opportunistic behavior worked on supply chain performance. Furthermore, an online questionnaire survey was conducted to collect 210 data samples from the food manufacturing industry in China, and the structural equation model method was applied to test the research hypotheses. According to the empirical research findings, social control can directly reduce opportunistic behaviors of supply chain members and reduce such behaviors indirectly via the mediating factor of information sharing; social control affects the supply chain performance via the mediating factors of information sharing and opportunistic behavior, instead of directly improving supply chain performance. Two information sharing mechanisms vary in their mechanism of influence. Information sharing with customers reduces opportunistic behaviors, but does not directly improve supply chain performance. Information sharing with suppliers enhances supply chain performance and reduces opportunistic behaviors. This research offers theoretical and practical suggestions for performance improvement and opportunistic behavior avoidance to promote food supply chain management.

Enabling High Quality Factor and Enhanced Thermoelectric Performance in BiBr3-Doped Sn0.93Mn0.1Te via Band Convergence and Band Sharpening.

Lead-free SnTe-based materials are expected to replace PbTe and have gained much attention from the thermoelectric community. In this work, a maximum ZT of ∼1.31 at 873 K is attained in SnTe via promoting a high quality factor resulting from Mn alloying and BiBr3 doping. The results show that Mn alloying in SnTe converges the L band and the ∑ band in valence bands to supply enhanced valley degeneracy and the density of states effective mass, giving rise to a high power factor of ∼21.67 µW cm-1 K-2 at 723 K in Sn0.93Mn0.1Te. In addition, the subsequent BiBr3 doping can sharpen the top of the valence band to coordinate the contradiction between the band effective mass and the carrier mobility, thus enhancing the carrier mobility while maintaining a relatively large density of states effective mass. Consequently, a maximum power factor of 23.85 µW cm-1 K-2 at 873 K is achieved in Sn0.93Mn0.1Te-0.8 atom % BiBr3. In addition to band sharpening, BiBr3 doping can also effectively suppress the bipolar effect at elevated temperatures and reduce the lattice thermal conductivity by strengthening the point defect phonon scattering. Benefitting from doping BiBr3 in Sn0.93Mn0.1Te optimizes the carrier mobility and suppresses the lattice thermal conductivity, resulting in a dramatically enhanced quality factor. Accordingly, an average ZT of ∼0.62 in the temperature range of 300-873 K is obtained in Sn0.93Mn0.1Te-0.8 atom % BiBr3, ∼250% increase compared with that in Sn1.03Te.

Specific oral and maxillofacial identifiers in panoramic radiographs used for human identification.

Radiographically assisted dental identification is an important means for individual identification. Specific identifiers help to quickly filter some of the possible corresponding AM and PM images at the beginning. The study seeks specific oral and maxillofacial identifiers in panoramic radiographs. A total of 920 panoramic radiographs from 460 live patients were used. The most recent radiograph served as the surrogate post-mortem (PM) record of an unidentified person, and the earliest radiograph served as the ante-mortem (AM) record of the same person. We evaluated the following four groups of identifiers of the images: (1) dental morphology, tooth number, and position; (2) dental treatment and pathology; (3) morphological identifiers of the jaw; and (4) pathological identifiers of the jaw. The ratio of each identifier being identified simultaneously in the AM and PM databases was determined. Specific identifiers were defined as those that appeared at low frequency (ratio: 0%-0.250%). A total of 18 specific oral and maxillofacial identifiers were determined. The specific identifiers were a retained deciduous tooth (0.011%), S-shaped deflection of a tooth root (0.012%), distal deflection of tooth root (0.017%), inverted impaction (0.018%), malposition (0.038%), supernumerary teeth (0.061%), mesial deflection of tooth root (0.092%), microdontia (0.136%), buccal/lingual impaction (0.188%), cementoma (0.002%), hypercementosis (0.002%), continuous crown (0.004%), pulp calcification (0.023%), attrition (0.030%), residual root (0.106%), root resorption (0.137%), implant (0.156%), and osteomyelitis (0.002%). Identifiers of the teeth and jaw can be used for human identification, and dental identifiers are more specific than identifiers of jaw.

(GeTe)1-x(AgSnSe2)x: Strong Atomic Disorder-Induced High Thermoelectric Performance near the Ioffe-Regel Limit.

In thermoelectrics, the material's performance stems from a delicate tradeoff between atomic order and disorder. Generally, dopants and thus atomic disorder are indispensable for optimizing the carrier concentration and scatter short-wavelength heat-carrying phonons. However, the strong disorder has been perceived as detrimental to the semiconductor's electrical conductivity owing to the deteriorated carrier mobility. Here, we report the sustainable role of strong atomic disorder in suppressing the detrimental phase transition and enhancing the thermoelectric performance in GeTe. We found that AgSnSe2 and Sb co-alloying eliminates the unfavorable phase transition due to the high configurational entropy and achieve the cubic Ge1-x-ySbyTe1-x(AgSnSe2)x solid solutions with cationic and anionic site disorder. Though AgSnSe2 substitution drives the carrier mean free path toward the Ioffe-Regel limit and minimizes the carrier mobility, the increased carrier concentration could render a decent electrical conductivity, affording enough phase room for further performance optimization. Given the lowermost carrier mean free path, further Sb alloying on Ge sites was implemented to progressively optimize the carrier concentration and enhance the density-of-state effective mass, thereby substantially enhancing the Seebeck coefficient. In addition, the high density of nanoscale strain clusters induced by strong atomic disorders significantly restrains the lattice thermal conductivity. As a result, a state-of-the-art zT ≈ 1.54 at 773 K was attained in cubic Ge0.58Sb0.22Te0.8(AgSnSe2)0.2. These results demonstrate that the strong atomic disorder at the high entropy scale is a previously underheeded but promising approach in thermoelectric material research, especially for the numerous low carrier mobility materials.

Automatic human identification from panoramic dental radiographs using the convolutional neural network.

Human identification is an important task in mass disaster and criminal investigations. Although several automatic dental identification systems have been proposed, accurate and fast identification from panoramic dental radiographs (PDRs) remains a challenging issue. In this study, an automatic human identification system (DENT-net) was developed using the customized convolutional neural network (CNN). The DENT-net was trained on 15,369 PDRs from 6300 individuals. The PDRs were preprocessed by affine transformation and histogram equalization. The DENT-net took 128 × 128 × 7 square patches as input, including the whole PDR and six details extracted from the PDR. Using the DENT-net, the feature extraction took around 10 milliseconds per image and the running time for retrieval was 33.03 milliseconds in a 2000-individual database, promising an application on larger databases. The visualization of CNN showed that the teeth, maxilla, and mandible all contributed to human identification. The DENT-net achieved Rank-1 accuracy of 85.16% and Rank-5 accuracy of 97.74% for human identification. The present results demonstrated that human identification can be achieved from PDRs by CNN with high accuracy and speed. The present system can be used without any special equipment or knowledge to generate the candidate images. While the final decision should be made by human specialists in practice. It is expected to aid human identification in mass disaster and criminal investigation.