Effects of Low-Temperature Heat Treatment on Mechanical and Thermophysical Properties of Cu-10Sn Alloys Fabricated by Laser Powder Bed Fusion.

This study investigated the impact of low-temperature heat treatments on the mechanical and thermophysical properties of Cu-10Sn alloys fabricated by a laser powder bed fusion (LPBF) additive manufacturing (AM) process. The microstructure, phase structure, and mechanical and thermal properties of the LPBF Cu-10Sn samples were comparatively investigated under both the as-fabricated (AF) condition and after low-temperature heat treatments at 140, 180, 220, 260, and 300 °C. The results showed that the low-temperature heat treatments did not significantly affect the phase and grain structures of the Cu-10Sn alloys. Both pre- and post-treatment samples displayed consistent grain sizes, with no obvious X-ray diffraction angle shift for the α phase, indicating that atom diffusion of the Sn element is beyond the detection resolution of X-ray diffractometers (XRD). However, the 180 °C heat-treated sample exhibited the highest hardness, while the AF samples had the lowest hardness, which was most likely due to the generation of precipitates according to thermodynamics modeling. Heat-treated samples also displayed higher thermal diffusivity values than their AF counterpart. The AF sample had the longest lifetime of ~0.19 nanoseconds (ns) in the positron annihilation lifetime spectroscopy (PALS) test, indicating the presence of the most atomic-level defects.

Higher specific capacitance and compressibility nanocellulose based supercapacitor hydrogel electrode assembled by efficient impregnation.

The rational and effective combination of different electrochemical substances to prepare high-performance supercapacitor electrodes has been widely studied by researchers. Currently, most work focuses on polymerizing conductive polymers onto the surface of nanocellulose and carbon materials, and then preparing them into supercapacitor electrodes. This method is effective, but the process is cumbersome. Therefore, we propose a simpler and more effective method. A hydrogel was prepared by using TEMPO oxidized cellulose nanofibers (TOCNF)/multi walled carbon nanotubes (MWCNT), and then immersed in aniline and FeCI3 solutions for 24 h to obtain a hydrogel electrode. At a current density of 0.5 mA cm-2, it exhibits an area specific capacitance of 1028 mF cm-2, with a maximum strain of 58 % and a compressive stress of 150 KPa. The assembled symmetrical supercapacitor exhibits a high specific capacitance of 303 mF cm-2 at a current density of 0.5 mA cm-2. The research results indicate that the proposed method is a new feasible approach for developing supercapacitors.

Visualized adsorption and enhanced photocatalytic removal of Cr6+ by carbon dots-incorporated fluorescent nanocellulose aerogels.

In this study, carbon dots (CDs) and titanate nanofibers (TNs) were mixed with TEMPO-oxidized nanocellulose (TOCNC) to prepare fluorescent nanocellulose aerogels (FNAs) by a Schiff base reaction. The resulting FNA can detect the adsorption of Cr6+ through the fluorescence quenching in CDs and promote the removal of Cr6+ through the synergistic effect of CDs in photocatalysis. The optimized FNA has a maximum adsorption capacity of 543.38 mg/g, higher than most reported Cr6+ adsorbents. This excellent performance is due to the porous structure of the aerogel, which gives it a high specific surface area of 20.53 m2/g and provides abundant adsorption sites. Simultaneously, CDs can enhance the amino-induced Cr6+ adsorption, improve the photocatalytic performance of TNs, and expose more adsorption sites through electrostatic adsorption of amino-induced reduction products (Cr3+). This study explores the preparation of visualized nanosorbents with enhanced photocatalytic removal of Cr6+ and provides a new direction for nanoscale photocatalysts.

Observation of a Superradiant Phase Transition with Emergent Cat States.

Superradiant phase transitions (SPTs) are important for understanding light-matter interactions at the quantum level, and play a central role in criticality-enhanced quantum sensing. So far, SPTs have been observed in driven-dissipative systems, but the emergent light fields did not show any nonclassical characteristic due to the presence of strong dissipation. Here we report an experimental demonstration of the SPT featuring the emergence of a highly nonclassical photonic field, realized with a resonator coupled to a superconducting qubit, implementing the quantum Rabi model. We fully characterize the light-matter state by Wigner matrix tomography. The measured matrix elements exhibit quantum interference intrinsic of a photonic mesoscopic superposition, and reveal light-matter entanglement.

Wound Dressing Double-Crosslinked Quick Self-Healing Hydrogel Based on Carboxymethyl Chitosan and Modified Nanocellulose.

The use of hydrogels in wound dressings, which is pivotal for effective wound treatment, has been widely applied to diverse medical wound conditions. However, formulating natural hydrogels that combine robust strength and self-healing capabilities is a significant challenge. To overcome this, we successfully designed a natural nanocellulose self-healing hydrogel that can quickly self-heal and restore the complete hydrogel structure after injury to fill the injured area and protect the wound from external damage. Our study utilized modified natural polymer carboxymethyl chitosan (CMC), hydrazide-modified carboxymethyl cellulose nanofibers (HCNF), and cellulose nanocrystals modified by dialdehyde (DACNC) to fabricate the hydrogel. The amides containing more amino groups and HCNF in CMC can be used as cross-linking nodes, and the high aspect ratio and specific surface area of DACNC are favorable for the connection of many active hydrogels. The hydrogel is crosslinked by the dynamic imide bond and hydrazone bond between the amino group of CMC, the amide of HCNF, and the aldehyde of DACNC and has a double network structure. These connections can be readily reassembled when disrupted, enabling fast self-healing of hydrogels within five minutes. Moreover, HCNF and DACNC were incorporated as nano-reinforced fillers to bolster the hydrogel's strength while preserving its high liquid absorption capacity (381% equilibrium swelling rate).

Facile preparation of nanocellulose/multi-walled carbon nanotube/polyaniline composite aerogel electrodes with high area-specific capacitance for supercapacitors.

As a natural biological macromolecule, nanocellulose is a promising substrate for high-performance supercapacitor electrodes. However, it shows that a low area-specific capacitance can limit its use. To strengthen the area-specific capacitance of nanocellulose-based composite aerogel electrodes to obtain high-performance supercapacitors, we combined the addition of conductive materials and physical cross-linking. After physical cross-linking and polyaniline embedding in the original conductive framework, a nanocellulose-based composite aerogel with a conductive network and outstanding electrochemical performance was obtained. The good electrochemical performance of the composite aerogel film electrode can be attributed to the high specific surface area of 46.32 m2·g-1, mesoporous structure, and uniform growth of polyaniline. The electrode exhibited the highest area-specific capacitance of 2176.3 mF·cm-2 at a current density of 1 mA·cm-2. Even at a current density of 10 mA·cm-2, the capacitance was retained at 1071.67 mF·cm-2, thereby showing good rate performance. Furthermore, the as-prepared aerogel film electrode exhibited electrochemical stability with a capacitance retention of 64 % at a current density of 10 mA·cm-2 after 1050 cycles. The as-assembled all-solid-state supercapacitor showed the highest area-specific capacitance of 968.94 mF·cm-2 at a current density of 0.5 mA·cm-2 and considerable energy and power density of 86.1 µWh·cm-2 and 200 µW·cm-2, respectively. In this study, we demonstrated that the proper construction of conductive networks by conductive polymers could maximize electrochemical performance.

Probing the evolutionary mechanism of the hydrogen bond network of cellulose nanofibrils using three DESs.

Complex interactions between cellulose molecules and small molecules in Deep Eutectic Solvent (DES) systems can lead to dramatic changes in the structure of the hydrogen bond network in cellulose. However, the mechanism of interaction between cellulose and solvent molecules and the mechanism of evolution of hydrogen bond network are still unclear. In this study, cellulose nanofibrils (CNFs) were treated with DESs based on oxalic acid as hydrogen bond donors (HBD), and choline chloride, betaine, and N-methylmorpholine-N-oxide (NMMO) as hydrogen bond acceptors (HBA). The changes in the properties and microstructure of CNFs during treatment with the three types of solvents were investigated by Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The results showed that the crystal structures of CNFs were not changed during the process, but the hydrogen bond network evolved, increasing the crystallinity and crystallite size. Further analysis of the fitted peaks of FTIR and generalized two-dimensional correlation spectra (2DCOS) revealed that all three hydrogen bonds were disrupted to different degrees, the relative content changed, and evolved strictly in a certain order. These findings indicate that the evolution of hydrogen bond networks in nanocellulose has certain regularity.

Efficient visual adsorption of Pb2+ by nanocellulose/sodium alginate microspheres with fluorescence sensitivity.

In this study, carbon dots (CDs) were prepared by a one-pot hydrothermal method using tempo-oxidized cellulose nanocrystals (TOCNC) and polyethylenimine (PEI). The CDs were self-assembled with a microsphere adsorbent prepared using TOCNC and sodium alginate (SA). CDs-TOCNC/SA-an environmentally friendly, fluorescent-sensitive, and recyclable microsphere adsorbent-was obtained. FTIR analysis showed that PEI successfully modified the CDs. In addition, the fluorescence quenching of CDs was observed when the concentration of Pb2+ was 0.0001-100 mg/L, indicating that CDs can dynamically monitor Pb2+. CDs-TOCNC/SA can produce blue fluorescence under 365 nm UV light and selectively and efficiently adsorb Pb2+. When the concentration of Pb2+ was 0.0001-100 mg/L, fluorescence quenching of the adsorbent was observed, indicating that CDs-TOCNC/SA could visually adsorb Pb2+. The adsorption isotherm and kinetic parameters show that the adsorption process conforms to the Langmuir isotherm model at 298 K, and the maximum adsorption capacity of Pb2+ was 190.1 mg/g at pH = 5. Moreover, CDs-TOCNC/SA could still obtain 78.99 % Pb2+ after five sorption-desorption cycles. The adsorption mechanism may involve ion exchange, electrostatic attraction, intra-particle diffusion, and chemical complexation.

Dual-Modified Lignin-Assembled Multilayer Microsphere with Excellent Pb2+ Capture.

With the continuous research on lignin-based sorbents, there are still limitations in the research of spherical sorbents with a high adsorption capacity for Pb2+. In order to solve the problem of low adsorption effect, alkali lignin (AL) was modified and assembled to increase the adsorption active sites. In this work, we used dual-modified lignin (DML) as a raw material to assemble a singular lignin-based multilayer microsphere (LMM) with sodium alginate (SA) and dopamine. The prepared adsorbent had various active functional groups and spherical structures; the specific surface area was 2.14 m2/g and the average pore size was 8.32 nm. The adsorption process followed the Freundlich isotherm and the second-order kinetic model. Therefore, the LMM adsorbed Pb2+ ascribed by the electrostatic attraction and surface complexation; the adsorption capacity was 250 mg/g. The LMM showed a selective adsorption performance for Pb2+ and the adsorption capacity followed the order Pb2+ (187.4 mg/g) > Cu2+(168.0 mg/g) > Mn2+(166.5 mg/g). After three cycles, the removal efficiency of Pb2+ by the LMM was 69.34%, indicating the reproducibility of LMM.

SQNN: a spike-wave index quantification neural network with a pre-labeling algorithm for epileptiform activity identification and quantification in children.

Objective.Electrical status epilepticus during slow sleep (ESES) is a phenomenon identified by strong activation of epileptiform activity in the electroencephalogram (EEG) during sleep. For children disturbed by ESES, spike-wave index (SWI) is defined to quantify the epileptiform activity in the EEG during sleep. Accurate SWI quantification is important for clinical diagnosis and prognosis. To quantify SWI automatically, a deep learning method is proposed in this paper.Approach.Firstly, a pre-labeling algorithm (PreLA) composed of the adaptive wavelet enhanced decomposition and a slow-wave discrimination rule is designed to efficiently label the EEG signal. It enables the collection of large-scale EEG dataset with fine-grained labels. Then, an SWI quantification neural network (SQNN) is constructed to accurately classify each sample point as normal or abnormal and to identify the abnormal events. SWI can be calculated automatically based on the total duration of abnormalities and the length of the signal.Main results.Experiments on two datasets demonstrate that the PreLA is effective and robust for labeling the EEG data and the SQNN accurately and reliably quantifies SWI without using any thresholds. The average estimation error of SWI is 3.12%, indicating that our method is more accurate and robust than experts and previous related works. The processing speed of SQNN is 100 times faster than that of experts.Significance.Deep learning provides a novel approach to automatic SWI quantification and PreLA provides an easy way to label the EEG data with ESES syndromes. The results of the experiments indicate that the proposed method has a high potential for clinical diagnosis and prognosis of epilepsy in children.

SQNN: A Spike-wave index Quantification Neural Network with a pre-labeling algorithm for epileptiform activity identification and quantification in children.

OBJECTIVE: Electrical status epilepticus during slow sleep (ESES) is a phenomenon identified by strong activation of epileptiform activity in the electroencephalogram (EEG) during sleep. For children disturbed by ESES, spike-wave index (SWI) is defined to quantify the epileptiform activity in the EEG during sleep. Accurate SWI quantification is important for clinical diagnosis and prognosis. To quantify SWI automatically, a deep learning method is proposed in this paper. APPROACH: Firstly, a pre-labeling algorithm (PreLA) composed of the adaptive wavelet enhanced decomposition and a slow-wave discrimination rule is designed to efficiently label the EEG signal. It enables the collection of large-scale EEG dataset with fine-grained labels. Then, an SWI Quantification Neural Network (SQNN) is constructed to accurately classify each sample point as normal or abnormal and to identify the abnormal events. SWI can be calculated automatically based on the total duration of abnormalities and the length of the signal. MAIN RESULTS: Experiments on two datasets demonstrate that the PreLA is effective and robust for labeling the EEG data and the SQNN accurately and reliably quantifies SWI without using any thresholds. The average estimation error of SWI is 3.12%, indicating that our method is more accurate and robust than experts and previous related works. The processing speed of SQNN is 100 times faster than that of experts. SIGNIFICANCE: Deep learning provides a novel approach to automatic SWI quantification and PreLA provides an easy way to label the EEG data with ESES syndromes. The results of the experiments indicate that the proposed method has a high potential for clinical diagnosis and prognosis of epilepsy in children.

Nanoarchitectonics for High Adsorption Capacity Carboxymethyl Cellulose Nanofibrils-Based Adsorbents for Efficient Cu2+ Removal.

In the present study, carboxymethyl cellulose nanofibrils (CMCNFs) with different carboxyl content (0.99-2.01 mmol/g) were prepared via controlling the ratio of monochloroacetic acid (MCA) and sodium hydroxide to Eucalyptus bleached pulp (EBP). CMCFs-PEI aerogels were obtained using the crosslinking reaction of polyethyleneimine (PEI) and CMCNFs with the aid of glutaraldehyde (GA). The effects of pH, contact time, temperature, and initial Cu2+ concentration on the Cu2+ removal performance of CMCNFs-PEI aerogels was highlighted. Experimental data showed that the maximum adsorption capacity of CMCNF30-PEI for Cu2+ was 380.03 ± 23 mg/g, and the adsorption results were consistent with Langmuir isotherm (R2 > 0.99). The theoretical maximum adsorption capacity was 616.48 mg/g. After being treated with 0.05 M EDTA solution, the aerogel retained an 85% removal performance after three adsorption-desorption cycles. X-ray photoelectron spectroscopy (XPS) results demonstrated that complexation was the main Cu2+ adsorption mechanism. The excellent Cu2+ adsorption capacity of CMCNFs-PEI aerogels provided another avenue for the utilization of cellulose nanofibrils in the wastewater treatment field.

Shortcuts to Adiabaticity for the Quantum Rabi Model: Efficient Generation of Giant Entangled Cat States via Parametric Amplification.

We propose a method for the fast generation of nonclassical ground states of the Rabi model in the ultrastrong and deep-strong coupling regimes via the shortcuts-to-adiabatic (STA) dynamics. The time-dependent quantum Rabi model is simulated by applying parametric amplification to the Jaynes-Cummings model. Using experimentally feasible parametric drive, this STA protocol can generate large-size Schrödinger cat states, through a process that is ∼10 times faster compared to adiabatic protocols. Such fast evolution increases the robustness of our protocol against dissipation. Our method enables one to freely design the parametric drive, so that the target state can be generated in the lab frame. A largely detuned light-matter coupling makes the protocol robust against imperfections of the operation times in experiments.

Effective pulse reverse-engineering for strong field-matter interaction.

In this Letter, we propose a scheme to control the evolution of a two-level quantum system in the strong-coupling regime, based on the idea of reverse engineering. A coherent control field is designed to drive the system along a user-predefined evolution trajectory without utilizing the rotating-wave approximation. As concrete examples, we show that complete population inversion, an equally weighted coherent superposition, and even oscillation-like dynamics can be achieved. Since there are no limitations on the coupling strength between the control field and matter, the scheme is attractive for applications such as accelerating desired system dynamics and fast quantum information processing.

Predictors and outcome surgery for posterior cortex epilepsies.

OBJECTIVE: The aim of this study is to identify the prognostic role of MRI and EEG in posterior cortex epilepsies (PCES) and to characterize their clinical features. PATIENT AND METHODS: We retrospectively studied 54 consecutive patients (18 females, 36 males) from April 2011 to November 2015, who had undergone PCES surgery. Electro-clinical, pathological and surgical data were evaluated. Of the patients, 18 (33.3%) patients underwent a cortical resection (corticectomy), 10 (18.5%) lobectomy, 6 (11.1%) multilobar resection, 20 (30.1%) disconnection. RESULTS: The postoperative follow-up duration was ≥1 year in all patients (12-44 months, mean = 25). Thirty-two patients (59.3%) became seizure free (ILAE 1) and 40 (74.1%) had a good (ILAE 1, 2, 3) outcome. The most common pathological finding was focal cortical dysplasia (in 34 patients). Univariate analysis showed that regional scalp interictal epilepsy discharges (IEDs) (P = 0.031), Regional EEG onset (P = 0.027), a MRI lesion (P = 0.001) and the number of seizures that were recorded by the epilepsy monitor unit (P = 0.016) were significantly associated with freedom from seizures. Multivariate analysis confirmed that MRI positive was statistically significant (HR = 4.284, CI = 1.198-15.315). CONCLUSIONS: Surgical treatment is effective for PCES, and MRI and EEG analyses are important in presurgical evaluation of PCES.

Arbitrary quantum state engineering in three-state systems via Counterdiabatic driving.

A scheme for arbitrary quantum state engineering (QSE) in three-state systems is proposed. Firstly, starting from a set of complete orthogonal time-dependent basis with undetermined coefficients, a time-dependent Hamiltonian is derived via Counterdiabatic driving for the purpose of guiding the system to attain an arbitrary target state at a predefined time. Then, on request of the assumed target states, two single-mode driving protocols and a multi-mode driving protocol are proposed as examples to discuss the validity of the QSE scheme. The result of comparison between single-mode driving and multi-mode driving shows that multi-mode driving seems to have a wider rang of application prospect because it can drive the system to an arbitrary target state from an arbitrary initial state also at a predefined time even without the use of microwave fields for the transition between the two ground states. Moreover, for the purpose of discussion in the scheme's feasibility in practice, a polynomial ansatz as the simplest exampleis used to fix the pulses. The result shows that the pulses designed to implement the protocols are not hard to be realized in practice. At the end, QSE in higher-dimensional systems is also discussed in brief as a generalization example of the scheme.

Fast generation of W states of superconducting qubits with multiple Schrödinger dynamics.

In this paper, we present a protocol to generate a W state of three superconducting qubits (SQs) by using multiple Schrödinger dynamics. The three SQs are respective embedded in three different coplanar waveguide resonators (CPWRs), which are coupled to a superconducting coupler (SCC) qubit at the center of the setups. With the multiple Schrödinger dynamics, we build a shortcuts to adiabaticity (STA), which greatly accelerates the evolution of the system. The Rabi frequencies of the laser pulses being designed can be expressed by the superpositions of Gaussian functions via the curves fitting, so that they can be realized easily in experiments. What is more, numerical simulation result shows that the protocol is robust against control parameters variations and decoherence mechanisms, such as the dissipations from the CPWRs and the energy relaxation. In addition, the influences of the dephasing are also resisted on account of the accelerating for the dynamics. Thus, the performance of the protocol is much better than that with the conventional adiabatic passage techniques when the dephasing is taken into account. We hope the protocol could be implemented easily in experiments with current technology.

Improving the stimulated Raman adiabatic passage via dissipative quantum dynamics.

We propose a method to improve the stimulated Raman adiabatic passage (STIRAP) via dissipative quantum dynamics, taking into account the dephasing effects. Fast and robust population transfer can be obtained with the scheme by the designed pulses and detuning, even though the initial state of the system is imperfect. With a concrete three-level system as an example, the influences of the imperfect initial state, variations in the control parameters, and various dissipation effects are discussed in detail. The numerical simulation shows that the scheme is insensitive to moderate fluctuations of experimental parameters and the relatively large dissipation effects of the excited state. Furthermore, the dominant dissipative factors, namely, the dephasing effects of the ground states and the imperfect initial state are no longer undesirable, in fact, they are the important resources to the scheme. Therefore, the scheme could provide more choices for the realization of the complete population transfer in the strong dissipative fields where the standard stimulated Raman adiabatic passage or shortcut schemes are invalid.

Reverse engineering of a Hamiltonian by designing the evolution operators.

We propose an effective and flexible scheme for reverse engineering of a Hamiltonian by designing the evolution operators to eliminate the terms of Hamiltonian which are hard to be realized in practice. Different from transitionless quantum driving (TQD), the present scheme is focus on only one or parts of moving states in a D-dimension (D ≥ 3) system. The numerical simulation shows that the present scheme not only contains the results of TQD, but also has more free parameters, which make this scheme more flexible. An example is given by using this scheme to realize the population transfer for a Rydberg atom. The influences of various decoherence processes are discussed by numerical simulation and the result shows that the scheme is fast and robust against the decoherence and operational imperfection. Therefore, this scheme may be used to construct a Hamiltonian which can be realized in experiments.