Herein, a strategy is reported for the fabrication of NiCo2O4‐based mesoporous nanosheets (PNSs) with tunable cobalt valence states and oxygen vacancies. The optimized NiCo2.148O4 PNSs with an ...average Co valence state of 2.3 and uniform 4 nm nanopores present excellent catalytic performance with an ultralow overpotential of 190 mV at a current density of 10 mA cm−2 and long‐term stability (700 h) for the oxygen evolution reaction (OER) in alkaline media. Furthermore, Zn–air batteries built using the NiCo2.148O4 PNSs present a high power and energy density of 83 mW cm−2 and 910 Wh kg−1, respectively. Moreover, a portable battery box with NiCo2.148O4 PNSs as the air cathode presents long‐term stability for 120 h under low temperatures in the range of 0 to −35 °C. Density functional theory calculations reveal that the prominent electron exchange and transfer activity of the electrocatalyst is attributed to the surface lower‐coordinated Co‐sites in the porous region presenting a merging 3d–eg–t2g band, which overlaps with the Fermi level of the Zn–air battery system. This favors the adsorption of the *OH, and stabilized *O radicals are reached, toward competitively lower overpotential, demonstrating a generalized key for optimally boosting overall OER performance.
Optimized NiCo2.148O4 mesoporous nanosheets with an average Co valence state of 2.3 and uniform 4 nm mesopores demonstrate exceptional performance for Zn–air batteries under a wide temperature range from 80 to −35 °C, which arises from the high activities of electron exchange and transfer by the surface lower‐coordinated Co‐sites within the porous region.
Valence, the representation of a stimulus in terms of good or bad, plays a central role in models of affect, value-based learning theories, and value-based decision-making models. Previous work used ...Unconditioned Stimulus (US) to support a theoretical division between two different types of valence representations for a stimulus: the semantic representation of valence, i.e., stored accumulated knowledge about the value of the stimulus, and the affective representation of valence, i.e., the valence of the affective response to this stimulus. The current work extended past research by using a neutral Conditioned Stimulus (CS) in the context of reversal learning, a type of associative learning. The impact of expected uncertainty (the variability of rewards) and unexpected uncertainty (reversal) on the evolving temporal dynamics of the two types of valence representations of the CS was tested in two experiments. Results show that in an environment presenting the two types of uncertainty, the adaptation process (learning rate) of the choices and of the semantic valence representation is slower than the adaptation of the affective valence representation. In contrast, in environments with only unexpected uncertainty (i.e., fixed rewards), there is no difference in the temporal dynamics of the two types of valence representations. Implications for models of affect, value-based learning theories, and value-based decision-making models are discussed.
It is generally accepted that a word's emotional valence (i.e., whether a word is perceived as positive, negative, or neutral) influences how it is accessed and remembered. There is also evidence ...that the affective content of some words is represented in nonarbitrary sound-meaning associations (i.e., emotional sound symbolism). We investigated whether more extensive statistical relationships exist between the surface form properties of English words and ratings of their emotional valence, that is, form typicality. We found significant form typicality for both valence and extremity of valence (the absolute distance from the midpoint of the rating scale, regardless of polarity). Next, using behavioral megastudy data sets, we show that measures of emotional form typicality are significant predictors of lexical access during written and auditory lexical decision and reading aloud tasks in addition to recognition memory performance. These findings show nonarbitrary form-valence mappings in English are accessed automatically during language and verbal memory processing. We discuss how these findings might be incorporated into theoretical accounts that implement Bayesian statistical inference.
Public Significance StatementFor over a century, language researchers have generally assumed that the relationship between the sound of a word and its meaning is entirely arbitrary. Our study shows there are systematic associations between the emotional valence of English words and their sound features. We also show that these emotional sound-meaning associations influence language processing and memory.
Abstract
A novel system Li
3
Mg
2
(Nb
(1−
x
)
Mo
x
)O
6+
x
/2
(0 ≤
x
≤ 0.08) microwave dielectric ceramics were fabricated by the solid‐state method. The charge compensation of Mo
6+
ions ...substitution for Nb
5+
ions was performed by introducing oxygen ions. The X‐ray diffraction patterns and Rietveld refinements indicated Li
3
Mg
2
(Nb
(1−
x
)
Mo
x
)O
6+
x
/2
ceramics with single phase and orthorhombic structure. Micro‐structure and density confirmed that the grain of Li
3
Mg
2
(Nb
(1‐
x
)
Mo
x
)O
6+
x
/2
ceramics grew well. In addition, the permittivity of Li
3
Mg
2
(Nb
(1−
x
)
Mo
x
)O
6+
x
/2
ceramics with the same trend as density decreased slightly with increasing Mo
6+
ions content. However, the
Q*f
and
τ
f
were obviously improved with an appropriate amount of Mo
6+
ions. When
x
≤ 0.04, the
Q*f
was closely related to the bond valence of samples, while when
x
≥ 0.06, the
Q*f
was closely related to the density of samples. The variations of
τ
f
and oxygen octahedral distortion were the opposite. In conclusions, the Li
3
Mg
2
(Nb
0.98
Mo
0.02
)O
6.01
ceramic sintered at 1200°C for 6 hours exhibited outstanding properties:
ε
r
~ 15.18,
Q*f
~ 116 266 GHz,
τ
f
~ −15.71 ppm/
o
C.
The superposition of quantum states drives motion on the atomic and subatomic scales, with the energy spacing of the states dictating the speed of the motion. In the case of electrons residing in the ...outer (valence) shells of atoms and molecules which are separated by electronvolt energies, this means that valence electron motion occurs on a subfemtosecond to few-femtosecond timescale (1 fs = 10(-15) s). In the absence of complete measurements, the motion can be characterized in terms of a complex quantity, the density matrix. Here we report an attosecond pump-probe measurement of the density matrix of valence electrons in atomic krypton ions. We generate the ions with a controlled few-cycle laser field and then probe them through the spectrally resolved absorption of an attosecond extreme-ultraviolet pulse, which allows us to observe in real time the subfemtosecond motion of valence electrons over a multifemtosecond time span. We are able to completely characterize the quantum mechanical electron motion and determine its degree of coherence in the specimen of the ensemble. Although the present study uses a simple, prototypical open system, attosecond transient absorption spectroscopy should be applicable to molecules and solid-state materials to reveal the elementary electron motions that control physical, chemical and biological properties and processes.
A two‐step optimization strategy is used to improve the thermoelectric performance of SnTe via modulating the electronic structure and phonon transport. The electrical transport of self‐compensated ...SnTe (that is, Sn1.03Te) was first optimized by Ag doping, which resulted in an optimized carrier concentration. Subsequently, Mn doping in Sn1.03−xAgxTe resulted in highly converged valence bands, which improved the Seebeck coefficient. The energy gap between the light and heavy hole bands, i.e. ΔEv decreases to 0.10 eV in Sn0.83Ag0.03Mn0.17Te compared to the value of 0.35 eV in pristine SnTe. As a result, a high power factor of ca. 24.8 μW cm−1 K−2 at 816 K in Sn0.83Ag0.03Mn0.17Te was attained. The lattice thermal conductivity of Sn0.83Ag0.03Mn0.17Te reached to an ultralow value (ca. 0.3 W m−1 K−1) at 865 K, owing to the formation of Ag7Te4 nanoprecipitates in SnTe matrix. A high thermoelectric figure of merit (z T≈1.45 at 865 K) was obtained in Sn0.83Ag0.03Mn0.17Te.
The thermoelectric four: Highly converged valence bands and ultralow lattice thermal conductivity owing to nanoprecipitates lead to a high thermoelectric figure of merit (z T≈1.45 at 865 K) in Sn0.83Ag0.03Mn0.17Te, which is higher than that of Ag alone or Mn‐doped SnTe.
Abstract
Designing novel single‐atom catalysts (SACs) supports to modulate the electronic structure is crucial to optimize the catalytic activity, but rather challenging. Herein, a general strategy ...is proposed to utilize the metalloid properties of supports to trap and stabilize single‐atoms with low‐valence states. A series of single‐atoms supported on the surface of tungsten carbide (M‐WC
x
, M=Ru, Ir, Pd) are rationally developed through a facile pyrolysis method. Benefiting from the metalloid properties of WC
x
, the single‐atoms exhibit weak coordination with surface W and C atoms, resulting in the formation of low‐valence active centers similar to metals. The unique metal‐metal interaction effectively stabilizes the low‐valence single atoms on the WC
x
surface and improves the electronic orbital energy level distribution of the active sites. As expected, the representative Ru‐WC
x
exhibits superior mass activities of 7.84 and 62.52 A mg
Ru
−1
for the hydrogen oxidation and evolution reactions (HOR/HER), respectively. In‐depth mechanistic analysis demonstrates that an ideal dual‐sites cooperative mechanism achieves a suitable adsorption balance of H
ad
and OH
ad
, resulting in an energetically favorable Volmer step. This work offers new guidance for the precise construction of highly active SACs.
A new π‐stacked compound, 1,8‐bis(2′,5′‐dimethoxy‐4′‐methyl‐1,1′‐biphenyl‐4‐yl)naphthalene (1) has been synthesized and characterized as a precursor molecule of monocationic mixed‐valence system ...(MVS). Cyclic and differential pulse voltammograms reveal that the ΔE°ox value between two sequential oxidation potentials is 163 mV. The three‐dimensional geometries of 1, 1•+, and 12+ were obtained via using density functional theory (DFT) calculations with a range‐separated hybrid functional and dispersion corrections (LC‐wPBE‐D3). Two dimethoxytoluene redox centers were aligned in parallel with van der Waals interplanar distances (3.50–3.70 Å). The electronic coupling in this MVS was evaluated by two different approaches: (1) Mulliken–Hush analysis of intervalence charge transfer (IVCT) band obtained from the spectroelectrochemical method, and (2) partial charge distribution analysis of quinonoidal distortion of D•+/D centers obtained from theoretical DFT calculations. The H12 were 2055 and 1903 cm−1 by (1) and (2), respectively. This work suggests that the pure through‐space electronic coupling can be large when two aromatic redox centers are properly aligned.
A new π‐stacked mixed‐valence system (MVS, 1•+) exhibiting strong IVCT absorption band in the NIR region. MVS 1•+ possesses two dimethoxytoluyl (D) units, which are separated by 3.5–3.7 Å. The experimentally determined electronic coupling matrix element was revealed to be 2055 cm−1, which is consistent with that evaluated by the geometrical analysis performed by DFT calculation (1903 cm−1).
Shape‐shifting molecules were probed in the gas phase, which conclusively unveiled the valence tautomerism phenomena for an archetypal barbaralone as described by José L. Alonso et al. in their ...Communication (e202117045). The two valence tautomers of this bistable molecular system were isolated in a supersonic jet for the first time and characterized by high‐resolution rotational spectroscopy coupled with laser ablation techniques. This observation opens the door towards the characterization of new fluxional systems under isolation conditions.
Previous works on image emotion analysis mainly focused on predicting the dominant emotion category or the average dimension values of an image for affective image classification and regression. ...However, this is often insufficient in various real-world applications, as the emotions that are evoked in viewers by an image are highly subjective and different. In this paper, we propose to predict the continuous probability distribution of image emotions which are represented in dimensional valence-arousal space. We carried out large-scale statistical analysis on the constructed Image-Emotion-Social-Net dataset, on which we observed that the emotion distribution can be well-modeled by a Gaussian mixture model. This model is estimated by an expectation-maximization algorithm with specified initializations. Then, we extract commonly used emotion features at different levels for each image. Finally, we formalize the emotion distribution prediction task as a shared sparse regression (SSR) problem and extend it to multitask settings, named multitask shared sparse regression (MTSSR), to explore the latent information between different prediction tasks. SSR and MTSSR are optimized by iteratively reweighted least squares. Experiments are conducted on the Image-Emotion-Social-Net dataset with comparisons to three alternative baselines. The quantitative results demonstrate the superiority of the proposed method.
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