Categorization of incongruent TPMS by geometric features using manifold learning and clustering
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The CMS upgrade for the High-Luminosity LHC (HL-LHC) era will allow for an incredibly high rate of data collection, to be used in the next generation of precision measurements and searches for beyond the standard model physics. A key element of this upgrade is the full replacement of the silicon strip tracker to enable level-1 triggering on track level primitives, produced by pixel-strip (PS) and strip-strip (2S) modules, tiled together to form the new detector. Mechanically supporting and cooling these modules is not trivial, as material budget in the tracker volume is highly constrained, and as the modules accrue radiation damage they risk becoming entirely non-functional if the silicon sensors are not sufficiently cooled. To address this, each region of the tracker has a bespoke solution for housing and cooling their modules, mostly depending on carbon-fiber and carbon-foam structures, with dual phase CO2 cooling. For the most central part of the tracker, the Flat Barrel with PS modules (Flat TBPS) covers the pseudorapidity range out to $|\eta|=0.4$, and the mechanical structures are manufactured, assembled, and tested entirely by Fermilab and UC Davis. This presentation will describe the intense design and testing requirements for these components, and how they will ensure strong performance of the tracker through the HL-LHC era.
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Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.
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Maintaining uniform ionic transport at electrode|electrolyte interfaces, i.e., ionic conformality, remains challenging in polymer electrolyte (PE)-based solid-state batteries. Morphological conformality does not necessarily imply ionic conformality. In PEs, which typically consist of a mechanically supporting component and distinct ionically conductive components, the rearrangement or depletion of mobile ion-conductive domains at interfaces can disrupt ionic transport pathways. Such localized ionic depletion contributes to interfacial instability and capacity degradation in high-voltage lithium-metal batteries. Herein, an electrolyte design approach aimed at minimizing interfacial heterogeneities is demonstrated through compositional adjustments, characterized by spatially resolved structural and chemical X-ray techniques and NMR diffusometry to elucidate ion transport dynamics. This approach improves ionic conformality at electrode interfaces, enhancing cycling stability in Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC811) coin and pouch cells cycled at high voltages. These results contribute to understanding interfacial behaviors in multiphase PEs and inform strategies for improving stability across solid-state battery interfaces.
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Reflection and refraction are ubiquitous phenomena with extensive applications, yet minimizing energy loss and information distortion during these processes remains a significant challenge. This study examines the behavior of structurally stable solitons, known as directrons, in nematic liquid crystals interacting with an interface where the director field orientation changes, despite identical physical properties, external potentials, and boundary anchoring in the two regions. During reflection and refraction, the directrons maintain nearly constant structure and velocity, ensuring energy conservation and information integrity. Microscopic analyses of the director field and macroscopic evaluations of effective potential are employed to elucidate the dependence of reflection and refraction probabilities on the directron’s incident angle and the orientation difference across the interface. The findings provide valuable insights into the dynamics of solitary waves in structured liquid crystal systems, offering significant implications for the development of tunable photonic devices, reconfigurable optical systems, and nanoscale material engineering.
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Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.
Abstract Symmetry-protected topological phases 1–4 cannot be described by any local order parameter and are beyond the conventional symmetry-breaking model 5 . They are characterized by topological boundary modes that remain stable under symmetry respecting perturbations 1–4,6–8 . In clean, gapped systems without disorder, the stability of these edge modes is restricted to the zero-temperature manifold; at finite temperatures, interactions with mobile thermal excitations lead to their decay 9–11 . Here we report the observation of a distinct type of topological edge mode 12–14 , which is protected by emergent symmetries and persists across the entire spectrum, in an array of 100 programmable superconducting qubits. Through digital quantum simulation of a one-dimensional disorder-free stabilizer Hamiltonian, we observe robust long-lived topological edge modes over up to 30 cycles for a wide range of initial states. We show that the interaction between these edge modes and bulk excitations can be suppressed by dimerizing the stabilizer strength, leading to an emergent U(1) × U(1) symmetry in the prethermal regime of the system. Furthermore, we exploit these topological edge modes as logical qubits and prepare a logical Bell state, which exhibits persistent coherence, despite the system being disorder-free and at finite temperature. Our results establish a viable digital simulation approach 15–18 to experimentally study topological matter at finite temperature and demonstrate a potential route to construct long-lived, robust boundary qubits in disorder-free systems.
Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.
Two-dimensional (2D) van der Waals (vdW) magnetic semiconductors are a new class of quantum materials for studying the emergent physics of excitons and spins in the 2D limit. Twist engineering provides a powerful tool to manipulate the fundamental properties of 2D vdW materials. Here, in this work, we show that twist engineering of the anisotropic ferromagnetic monolayer semiconductor CrSBr leads to bilayer magnetic semiconductors with continuously tunable magnetic moment, dielectric anisotropy, exciton energy, and linear dichroism. We furthermore provide a model for exciton energy in the media with tunable anisotropy. These results advance fundamental studies of 2D vdW materials and open doors to applications to nano-optics, twistronics, and spintronics.
Recent angle-resolved photoelectron spectroscopy (ARPES) measurements of the hole effective mass in CsPbBr$_3$ revealed an enhancement of $\sim$50 % compared to the bare mass computed from first principles for CsPbBr$_3$ at $T = 0 K$. This large enhancement was interpreted as evidence of polaron formation. Employing accurate finite-temperature first-principles calculations, we show that the calculated hole effective mass of CsPbBr$_3$ at $T = 300 K$ can explain experimental results without invoking polarons. Thermal fluctuations are particularly strong in halide perovskites compared to conventional semiconductors such as Si and GaAs, and cannot be ignored when comparing with experiment. We not only resolve the debate on polaron formation in halide perovskites, but also demonstrate the general importance of including thermal fluctuations in first-principles calculations for strongly anharmonic materials.
Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.
Rare event searches such as neutrinoless double beta decay and Weakly Interacting Massive Particle detection require ultra-low background detectors. Radon contamination is a significant challenge for these experiments, which employ highly sensitive radon assay techniques to identify and select low-emission materials. This work presents the development of ultra-sensitive electrostatic chamber (ESC) instruments designed to measure radon emanation in a recirculating gas loop, for future lower background experiments. Unlike traditional methods that separate emanation and detection steps, this system allows continuous radon transport and detection. This is made possible with a custom-built recirculation pump. A Python-based analysis framework, PyDAn, was developed to process and fit time-dependent radon decay data. Radon emanation rates are given for various materials measured with this instrument. A radon source of known activity provides an absolute calibration, enabling statistically-limited minimal detectable activities of 20 µBq. These devices are powerful tools for screening materials in the development of low-background particle physics experiments.