Origin of structural degradation in Li-rich layered oxide cathode.

Li- and Mn-rich (LMR) cathode materials that utilize both cation and anion redox can yield substantial increases in battery energy density1-3. However, although voltage decay issues cause continuous energy loss and impede commercialization, the prerequisite driving force for this phenomenon remains a mystery3-6 Here, with in situ nanoscale sensitive coherent X-ray diffraction imaging techniques, we reveal that nanostrain and lattice displacement accumulate continuously during operation of the cell. Evidence shows that this effect is the driving force for both structure degradation and oxygen loss, which trigger the well-known rapid voltage decay in LMR cathodes. By carrying out micro- to macro-length characterizations that span atomic structure, the primary particle, multiparticle and electrode levels, we demonstrate that the heterogeneous nature of LMR cathodes inevitably causes pernicious phase displacement/strain, which cannot be eliminated by conventional doping or coating methods. We therefore propose mesostructural design as a strategy to mitigate lattice displacement and inhomogeneous electrochemical/structural evolutions, thereby achieving stable voltage and capacity profiles. These findings highlight the significance of lattice strain/displacement in causing voltage decay and will inspire a wave of efforts to unlock the potential of the broad-scale commercialization of LMR cathode materials.

In situ Raman spectroscopy reveals the structure and dissociation of interfacial water.

Understanding the structure and dynamic process of water at the solid-liquid interface is an extremely important topic in surface science, energy science and catalysis1-3. As model catalysts, atomically flat single-crystal electrodes exhibit well-defined surface and electric field properties, and therefore may be used to elucidate the relationship between structure and electrocatalytic activity at the atomic level4,5. Hence, studying interfacial water behaviour on single-crystal surfaces provides a framework for understanding electrocatalysis6,7. However, interfacial water is notoriously difficult to probe owing to interference from bulk water and the complexity of interfacial environments8. Here, we use electrochemical, in situ Raman spectroscopic and computational techniques to investigate the interfacial water on atomically flat Pd single-crystal surfaces. Direct spectral evidence reveals that interfacial water consists of hydrogen-bonded and hydrated Na+ ion water. At hydrogen evolution reaction (HER) potentials, dynamic changes in the structure of interfacial water were observed from a random distribution to an ordered structure due to bias potential and Na+ ion cooperation. Structurally ordered interfacial water facilitated high-efficiency electron transfer across the interface, resulting in higher HER rates. The electrolytes and electrode surface effects on interfacial water were also probed and found to affect water structure. Therefore, through local cation tuning strategies, we anticipate that these results may be generalized to enable ordered interfacial water to improve electrocatalytic reaction rates.

BindingSiteDTI: differential-scale binding site modelling for drug-target interaction prediction.

MOTIVATION: Enhanced by contemporary computational advances, the prediction of drug-target interactions (DTIs) has become crucial in developing de novo and effective drugs. Existing deep learning approaches to DTI prediction are frequently beleaguered by a tendency to overfit specific molecular representations, which significantly impedes their predictive reliability and utility in novel drug discovery contexts. Furthermore, existing DTI networks often disregard the molecular size variance between macro molecules (targets) and micro molecules (drugs) by treating them at an equivalent scale that undermines the accurate elucidation of their interaction. RESULTS: We propose a novel DTI network with a differential-scale scheme to model the binding site for enhancing DTI prediction, which is named as BindingSiteDTI. It explicitly extracts multiscale substructures from targets with different scales of molecular size and fixed-scale substructures from drugs, facilitating the identification of structurally similar substructural tokens, and models the concealed relationships at the substructural level to construct interaction feature. Experiments conducted on popular benchmarks, including DUD-E, human, and BindingDB, shown that BindingSiteDTI contains significant improvements compared with recent DTI prediction methods. AVAILABILITY AND IMPLEMENTATION: The source code of BindingSiteDTI can be accessed at https://github.com/MagicPF/BindingSiteDTI.

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution.

The development of many quantum optical technologies depends on the availability of single quantum emitters with near-perfect coherence. Systematic improvement is limited by a lack of understanding of the microscopic energy flow at the single-emitter level and ultrafast timescales. Here we utilize a combination of fluorescence correlation spectroscopy and ultrafast spectroscopy to capture the sample-averaged dynamics of defects with single-particle sensitivity. We employ this approach to study heterogeneous emitters in two-dimensional hexagonal boron nitride. From milliseconds to nanoseconds, the translational, shelving, rotational and antibunching features are disentangled in time, which quantifies the normalized two-photon emission quantum yield. Leveraging the femtosecond resolution of this technique, we visualize electron-phonon coupling and discover the acceleration of polaronic formation on multi-electron excitation. Corroborated with theory, this translates to the photon fidelity characterization of cascaded emission efficiency and decoherence time. Our work provides a framework for ultrafast spectroscopy in heterogeneous emitters, opening new avenues of extreme-scale characterization for quantum applications.

Spectroscopy in Nanoscopic Cavities: Models and Recent Experiments.

The ability of nanophotonic cavities to confine and store light to nanoscale dimensions has important implications for enhancing molecular, excitonic, phononic, and plasmonic optical responses. Spectroscopic signatures of processes that are ordinarily exceedingly weak such as pure absorption and Raman scattering have been brought to the single-particle limit of detection, while new emergent polaritonic states of optical matter have been realized through coupling material and photonic cavity degrees of freedom across a wide range of experimentally accessible interaction strengths. In this review, we discuss both optical and electron beam spectroscopies of cavity-coupled material systems in weak, strong, and ultrastrong coupling regimes, providing a theoretical basis for understanding the physics inherent to each while highlighting recent experimental advances and exciting future directions.

Tagged actin mRNA dysregulation in IGF2BP1[Formula: see text] mice.

Gene expression is tightly regulated by RNA-binding proteins (RBPs) to facilitate cell survival, differentiation, and migration. Previous reports have shown the importance of the Insulin-like Growth Factor II mRNA-Binding Protein (IGF2BP1/IMP1/ZBP1) in regulating RNA fate, including localization, transport, and translation. Here, we generated and characterized a knockout mouse to study RBP regulation. We report that IGF2BP1 is essential for proper brain development and neonatal survival. Specifically, these mice display disorganization in the developing neocortex, and further investigation revealed a loss of cortical marginal cell density at E17.5. We also investigated migratory cell populations in the IGF2BP1[Formula: see text] mice, using BrdU labeling, and detected fewer mitotically active cells in the cortical plate. Since RNA localization is important for cellular migration and directionality, we investigated the regulation of ß-actin messenger RNA (mRNA), a well-characterized target with established roles in cell motility and development. To aid in our understanding of RBP and target mRNA regulation, we generated mice with endogenously labeled ß-actin mRNA (IGF2BP1[Formula: see text]; ß-actin-MS2[Formula: see text]). Using endogenously labeled ß-actin transcripts, we report IGF2BP1[Formula: see text] neurons have increased transcription rates and total ß-actin protein content. In addition, we found decreased transport and anchoring in knockout neurons. Overall, we present an important model for understanding RBP regulation of target mRNA.

Adaptive Signal Modulation Evolved by the Inherent Nonlinearity of Phase-Change Quantum-Dot String.

To simulate a topological neural network handling weak signals via stochastic resonance (SR), it is necessary to introduce an inherent nonlinearity into nanoscale devices. We use the self-assembly method to successfully fabricate a phase-change quantum-dot string (PCQDS) crossing Pd/Nb:AlNO/AlNO/Nb:AlNO/Pd multilayer. The inherent nonlinearity of phase change couples with electron tunneling so that PCQDS responds to a long signal sequence in a modulated output style, in which the pulse pattern evolves to that enveloped by two sets of periodic wave characterized by neural action potential. We establish an SR mode consisting of several two-state systems in which dissipative tunneling is coupled to environment. Size oscillations owing to NbO QDs adaptively adjust barriers and wells, such that tunneling can be periodically modulated by either asymmetric energy or local temperature. When the external periodic signals are applied, the system first follows the forcing frequency. Subsequently, certain PCQDs oscillate independently and consecutively to produce complicated frequency and amplitude modulations.

Electrical-Controllable Antiferromagnet-Based Tunnel Junction.

An electrical-controllable antiferromagnet tunnel junction is a key goal in spintronics, holding immense promise for ultradense and ultrastable antiferromagnetic memory with high processing speed for modern information technology. Here, we have advanced toward this goal by achieving an electrical-controllable antiferromagnet-based tunnel junction of Pt/Co/Pt/Co/IrMn/MgO/Pt. The exchange coupling between antiferromagnetic IrMn and Co/Pt perpendicular magnetic multilayers results in the formation of an interfacial exchange bias and exchange spring in IrMn. Encoding information states "0" and "1" is realized through the exchange spring in IrMn, which can be electrically written by spin-orbit torque switching with high cyclability and electrically read by antiferromagnetic tunneling anisotropic magnetoresistance. Combining spin-orbit torque switching of both exchange spring and exchange bias, a 16 Boolean logic operation is successfully demonstrated. With both memory and logic functionalities integrated into our electrically controllable antiferromagnetic-based tunnel junction, we chart the course toward high-performance antiferromagnetic logic-in-memory.

Cell firing between ON alpha retinal ganglion cells and coupled amacrine cells in the mouse retina.

Gap junctions are channels that allow for direct transmission of electrical signals between cells. However, the ability of one cell to be impacted or controlled by other cells through gap junctions remains unclear. In this study, heterocellular coupling between ON α retinal ganglion cells (α-RGCs) and displaced amacrine cells (ACs) in the mouse retina was used as a model. The impact of the extent of coupling of interconnected ACs on the synchronized firing between coupled ON α-RGC-AC pair was investigated using the dopamine 1 receptor (D1R) antagonist-SCH23390 and agonist-SKF38393. It was observed that the synchronized firing between the ON α-RGC-ACs pairs was increased by the D1R antagonist SCH23390, whereas it was eradicated by the agonist SKF38393. Subsequently, the signaling drive was investigated by infecting coupled ON α-RGC-AC pairs with the channelrhodopsin-2(ChR2) mutation L132C engineered to enhance light sensitivities. The results demonstrated that the spikes of ON α-RGCs (without ChR2) could be triggered by ACs (with ChR2) through the gap junction, and vice versa. Furthermore, it was observed that ON α-RGCs stimulated with 3-10 Hz currents by whole cell patch could elicit synchronous spikes in the coupled ACs, and vice versa. This provided direct evidence that the firing of one cell could be influenced by another cell through gap junctions. However, this phenomenon was not observed between OFF α-RGC pairs. The study implied that the synchronized firing between ON α-RGC-AC pairs could potentially be affected by the coupling of interconnected ACs. Additionally, one cell type could selectively control the firing of another cell type, thereby forcefully transmitting information. The key role of gap junctions in synchronizing firing and driving cells between α-RGCs and coupled ACs in the mouse retina was highlighted.NEW & NOTEWORTHY This study investigates the role of gap junctions in transmitting electrical signals between cells and their potential for cell control. Using ON α retinal ganglion cells (α-RGCs) and amacrine cells (ACs) in the mouse retina, the researchers find that the extent of coupling between ACs affects synchronized firing. Bidirectional signaling occurs between ACs and ON α-RGCs through gap junctions.

Analysis of the effects of M2 macrophage-derived PDE4C on the prognosis, metastasis and immunotherapy benefit of osteosarcoma.

Tumour-associated macrophages (TAMs), encompassing M1 and M2 subtypes, exert significant effects on osteosarcoma (OS) progression and immunosuppression. However, the impacts of TAM-derived biomarkers on the progression of OS remains limited. The GSE162454 profile was subjected to single-cell RNA (scRNA) sequencing analysis to identify crucial mediators between TAMs and OS cells. The clinical features, effects and mechanisms of these mediators on OS cells and tumour microenvironment were evaluated via biological function experiments and molecular biology experiments. Phosphodiesterase 4C (PDE4C) was identified as a pivotal mediator in the communication between M2 macrophages and OS cells. Elevated levels of PDE4C were detected in OS tissues, concomitant with M2 macrophage level, unfavourable prognosis and metastasis. The expression of PDE4C was observed to increase during the conversion process of THP-1 cells to M2 macrophages, which transferred the PDE4C mRNA to OS cells through exosome approach. PDE4C increased OS cell proliferation and mobility via upregulating the expression of collagens. Furthermore, a positive correlation was observed between elevated levels of PDE4C and increased TIDE score, decreased response rate following immune checkpoint therapy, reduced TMB and diminished PDL1 expression. Collectively, PDE4C derived from M2 macrophages has the potential to enhance the proliferation and mobility of OS cells by augmenting collagen expression. PDE4C may serve as a valuable biomarker for prognosticating patient outcomes and response rates following immunotherapy.

Rapid Mining of Fast Ion Conductors via Subgraph Isomorphism Matching.

The rapidly evolving field of inorganic solid-state electrolytes (ISSEs) has been driven in recent years by advances in data-mining techniques, which facilitates the high-throughput computational screening for candidate materials in the databases. The key to the mining process is the selection of critical features that underline the similarity of a material to an existing ISSE. Unfortunately, this selection is generally subjective and frequently under debate. Here we propose a subgraph isomorphism matching method that allows an objective evaluation of the similarity between two compounds according to the topology of the local atomic environment. The matching algorithm has been applied to discover four structure types that are highly analogous to the LiTi2(PO4)3 NASICON prototype. We demonstrate that the local atomic environments similar to LiTi2(PO4)3 endow these four structures with favorable Li diffusion tunnels and ionic conductivity on par with those of the prototype. By further taking into account the electronic structure and electrochemical stability window, 13 compounds are identified to be potential ISSEs. Our findings not only offer a promising approach toward rapid mining of fast ion conductors without limitation in the compositional range but also reveal insights into the design of ISSEs according to the topology of their framework structures.

Cation-Induced Interfacial Hydrophobic Microenvironment Promotes the C-C Coupling in Electrochemical CO2 Reduction.

The electrochemical carbon dioxide reduction reaction (CO2RR) toward C2 products is a promising way for the clean energy economy. Modulating the structure of the electric double layer (EDL), especially the interfacial water and cation type, is a useful strategy to promote C-C coupling, but atomic understanding lags far behind the experimental observations. Herein, we investigate the combined effect of interfacial water and alkali metal cations on the C-C coupling at the Cu(100) electrode/electrolyte interface using ab initio molecular dynamics (AIMD) simulations with a constrained MD and slow-growth approach. We observe a linear correlation between the water-adsorbate stabilization effect, which manifests as hydrogen bonds, and the corresponding alleviation in the C-C coupling free energy. The role of a larger cation, compared to a smaller cation (e.g., K+ vs Li+), lies in its ability to approach the interface through desolvation and coordinates with the *CO+*CO moiety, partially substituting the hydrogen-bonding stabilizing effect of interfacial water. Although this only results in a marginal reduction of the energy barrier for C-C coupling, it creates a local hydrophobic environment with a scarcity of hydrogen bonds owing to its great ionic radius, impeding the hydrogen of surrounding interfacial water to approach the oxygen of the adsorbed *CO. This skillfully circumvents the further hydrogenation of *CO toward the C1 pathway, serving as the predominant factor through which a larger cation facilitates C-C coupling. This study unveils a comprehensive atomic mechanism of the cation-water-adsorbate interactions that can facilitate the further optimization of the electrolyte and EDL for efficient C-C coupling in CO2RR.

Crystal Structure Assignment for Unknown Compounds from X-ray Diffraction Patterns with Deep Learning.

Determining the structures of previously unseen compounds from experimental characterizations is a crucial part of materials science. It requires a step of searching for the structure type that conforms to the lattice of the unknown compound, which enables the pattern matching process for characterization data, such as X-ray diffraction (XRD) patterns. However, this procedure typically places a high demand on domain expertise, thus creating an obstacle for computer-driven automation. Here, we address this challenge by leveraging a deep-learning model composed of a union of convolutional residual neural networks. The accuracy of the model is demonstrated on a dataset of over 60,000 different compounds for 100 structure types, and additional categories can be integrated without the need to retrain the existing networks. We also unravel the operation of the deep-learning black box and highlight the way in which the resemblance between the unknown compound and a structure type is quantified based on both local and global characteristics in XRD patterns. This computational tool opens new avenues for automating structure analysis on materials unearthed in high-throughput experimentation.

Immune checkpoint inhibitors in cancer: the increased risk of atherosclerotic cardiovascular disease events and progression of coronary artery calcium.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have contributed to a significant advancement in the treatment of cancer, leading to improved clinical outcomes in many individuals with advanced disease. Both preclinical and clinical investigations have shown that ICIs are associated with atherosclerosis and other cardiovascular events; however, the exact mechanism underlying this relationship has not been clarified. METHODS: Patients diagnosed with stages III or IV non-small cell lung cancer (NSCLC) at the Wuhan Union Hospital from March 1, 2020, to April 30, 2022, were included in this retrospective study. Coronary artery calcium (CAC) volume and score were assessed in a subset of patients during non-ECG-gated chest CT scans at baseline and 3, 6, and 12 months after treatment. Propensity score matching (PSM) was performed in a 1:1 ratio to balance the baseline characteristics between the two groups. RESULTS: Overall, 1458 patients (487 with ICI therapy and 971 without ICI therapy) were enrolled in this cardiovascular cohort study. After PSM, 446 patients were included in each group. During the entire period of follow-up (median follow-up 23.1 months), 24 atherosclerotic cardiovascular disease (ASCVD) events (4.9%) occurred in the ICI group, and 14 ASCVD events (1.4%) in the non-ICI group, before PSM; 24 ASCVD events (5.4%) occurred in the ICI group and 5 ASCVD events (1.1%) in the non-ICI group after PSM. The CAC imaging study group comprised 113 patients with ICI therapy and 133 patients without ICI therapy. After PSM, each group consisted of 75 patients. In the ICI group, the CAC volume/score increased from 93.4 mm3/96.9 (baseline) to 125.1 mm3/132.8 (at 12 months). In the non-ICI group, the CAC volume/score was increased from 70.1 mm3/68.8 (baseline) to 84.4 mm3/87.9 (at 12 months). After PSM, the CAC volume/score was increased from 85.1 mm3/76.4 (baseline) to 111.8 mm3/121.1 (12 months) in the ICI group and was increased from 74.9 mm3/76.8 (baseline) to 109.3 mm3/98.7 (12 months) in the non-ICI group. Both cardiovascular events and CAC progression were increased after the initiation of ICIs. CONCLUSIONS: Treatment with ICIs was associated with a higher rate of ASCVD events and a noticeable increase in CAC progression.

An Electrochemically Initiated Self-Limiting Hydrogel Electrolyte for Dendrite-Free Zinc Anode.

The zinc dendrite growth generally relies upon a "positive-feedback" mode, where the fast-grown tips receive higher current densities and ion fluxes. In this study, a self-limiting polyacrylamide (PAM) hydrogel that presents negative feedback to dendrite growth is developed. The monomers are purposefully polymerized at the dendrite tips, then the hydrogel reduces the local current density and ion flux by limiting zinc ion diffusion with abundant functional groups. As a consequence, the accumulation at the dendrite tips is restricted, and the (002) facets-oriented deposition is achieved. Moreover, the refined porous structure of the gel enhances Coulombic Efficiency by reducing water activity. Due to the synergistic effects, the zinc anodes perform an ultralong lifetime of 5100 h at 0.5 mA cm-2 and 1500 h at 5 mA cm-2, which are among the best records for PAM-based gel electrolytes. Further, the hydrogel significantly prolongs the lifespan of zinc-ion batteries and capacitors by dozens of times. The developed in situ hydrogel presents a feasible and cost-effective way to commercialize zinc anodes and provides inspiration for future research on dendrite suppression using the negative-feedback mechanism.

Photoreceptor-Mimetic Microflowers for Restoring Light Responses in Degenerative Retina through a 2D Nanopetal/Cell Biointerface.

Retinitis pigmentosa is the main cause of inherited human blindness and is associated with dysfunctional photoreceptors (PRs). Compared with traditional methods, optoelectronic stimulation can better preserve the structural integrity and genetic content of the retina. However, enhancing the spatiotemporal accuracy of stimulation is challenging. Quantum dot-doped ZnIn2S4 microflowers (MF) are utilized to construct a biomimetic photoelectric interface with a 0D/3D heterostructure, aiming to restore the light response in PR-degenerative mice. The MF bio interface has dimensions similar to those of natural PRs and can be distributed within the curved spatial region of the retina, mimicking cellular dispersion. The soft 2D nano petals of the MF provide a large specific surface area for photoelectric activation and simulate the flexibility interfacing between cells. This bio interface can selectively restore the light responses of seven types of retina ganglion cells that encode brightness. The distribution of responsive cells forms a pattern similar to that of normal mice, which may reflect the generation of the initial "neural code" in the degenerative retina. Patch-clamp recordings indicate that the bio interface can induce spiking and postsynaptic currents at the single-neuron level. The results will shed light on the development of a potential bionic subretinal prosthetic toolkit for visual function restoration.

Substitutional Cd Dopant as Photohole Transfer Mediator Boosting Photoelectrochemical Solar Energy Conversion of 2D Cd-ZnIn2 S4 Photoanode.

Fast recombination dynamics of photocarriers competing with sluggish surface photohole oxidation kinetics severely restricts the photoelectrochemical (PEC) conversion efficiency of photoanode. Here, a defect engineering strategy is developed to regulate photohole transfer and interfacial injection dynamics of 2D ZnIn2 S4 (ZIS). Via selectively introducing substitutional Cd dopant at Zn sites of the ZIS basal plane, energy band structure and surface electrochemical activity are successfully modulated in the Cd-doped ZIS (Cd-ZIS) nanosheet array photoanode. Comprehensive characterizations manifest that a shallow acceptor level induced by Cd doping and superior electrochemical activity make surface Cd dopants simultaneously act as capture centers and active sites to mediate photohole dynamics at the reaction interface. In depth photocarrier dynamics analysis demonstrates that highly efficient photohole capture of Cd dopants brings about effective space separation of photocarriers and acceleration of surface reaction kinetics. Therefore, the optimum 2D Cd-ZIS achieves excellent PEC solar energy conversion efficiency with a photocurrent density of 5.1 mA cm-2 at 1.23 VRHE and a record of applied bias photon-to-current efficiency (ABPE) of 3.0%. This work sheds light on a microstructure design strategy to effectively regulate photohole dynamics for the next-generation semiconducting PEC photoanodes.

Pan-cancer analysis reveals CCL5/CSF2 as potential predictive biomarkers for immune checkpoint inhibitors.

BACKGROUND: Currently, there are no optimal biomarkers available for distinguishing patients who will respond to immune checkpoint inhibitors (ICIs) therapies. Consequently, the exploration of novel biomarkers that can predict responsiveness to ICIs is crucial in the field of immunotherapy. METHODS: We estimated the proportions of 22 immune cell components in 10 cancer types (6,128 tumors) using the CIBERSORT algorithm, and further classified patients based on their tumor immune cell proportions in a pan-cancer setting using k-means clustering. Differentially expressed immune genes between the patient subgroups were identified, and potential predictive biomarkers for ICIs were explored. Finally, the predictive value of the identified biomarkers was verified in patients with urothelial carcinoma (UC) and esophageal squamous cell carcinoma (ESCC) who received ICIs. RESULTS: Our study identified two subgroups of patients with distinct immune infiltrating phenotypes and differing clinical outcomes. The patient subgroup with improved outcomes displayed tumors enriched with genes related to immune response regulation and pathway activation. Furthermore, CCL5 and CSF2 were identified as immune-related hub-genes and were found to be prognostic in a pan-cancer setting. Importantly, UC and ESCC patients with high expression of CCL5 and low expression of CSF2 responded better to ICIs. CONCLUSION: We demonstrated CCL5 and CSF2 as potential novel biomarkers for predicting the response to ICIs in patients with UC and ESCC. The predictive value of these biomarkers in other cancer types warrants further evaluation in future studies.

Tensor Network Message Passing.

When studying interacting systems, computing their statistical properties is a fundamental problem in various fields such as physics, applied mathematics, and machine learning. However, this task can be quite challenging due to the exponential growth of the state space as the system size increases. Many standard methods have significant weaknesses. For instance, message-passing algorithms can be inaccurate and even fail to converge due to short loops, while tensor network methods can have exponential computational complexity in large graphs due to long loops. In this Letter, we propose a new method called "tensor network message passing." This approach allows us to compute local observables like marginal probabilities and correlations by combining the strengths of tensor networks in contracting small subgraphs with many short loops and the strengths of message-passing methods in globally sparse graphs, thus addressing the crucial weaknesses of both approaches. Our algorithm is exact for systems that are globally treelike and locally dense-connected when the dense local graphs have a limited tree width. We have conducted numerical experiments on synthetic and real-world graphs to compute magnetizations of Ising models and spin glasses, and have demonstrated the superiority of our approach over standard belief propagation and the recently proposed loopy message-passing algorithm. In addition, we discuss the potential applications of our method in inference problems in networks, combinatorial optimization problems, and decoding problems in quantum error correction.

Electrical Detection of Acoustic Antiferromagnetic Resonance in Compensated Synthetic Antiferromagnets.

Compensated synthetic antiferromagnets (SAFs) stand out as promising candidates to explore various spintronic applications, benefitting from high precession frequency and negligible stray field. High-frequency antiferromagnetic resonance in SAFs, especially the optic mode (OM), is highly desired to attain fast operation speed in antiferromagnetic spintronic devices. SAFs exhibit ferromagnetic configurations above saturation field; however in that case, the intensity of OM is theoretically zero and hard to be detected in well-established microwave resonance experiments. To expose the hidden OM, the exchange symmetry between magnetic layers must be broken, inevitably introducing remanent magnetization. Here, we experimentally demonstrate a feasible method to break the symmetry via surface acoustic waves with the maintenance of compensated SAF structure. By introducing an out-of-plane strain gradient inside the Ir-mediated SAFs, we successfully reveal the hidden OM. Remarkably, the OM intensity can be effectively modulated by controlling strain gradients in SAFs with different thicknesses, confirmed by finite-element simulations. Our findings provide a feasible scheme for detecting the concealed OM, which would trigger future discoveries in magnon-phonon coupling and hybrid quasiparticle systems.