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Recent experiments demonstrate a “robust superconductivity phenomenon” in niobium-based alloys, where the superconducting state remains intact and the critical temperature (Tc) is largely unaffected by external pressure well above tens of gigapascal (GPa) into the megabar regime ( more than 100GPa). Motivated by these observations, we perform first-principles electron-phonon calculations for body-centered cubic Nb and NbTi crystals, as well as for special quasi-random structures of Nb0.5Ti0.5 and (NbTa)0.7(HfZrTi)0.3 high-entropy alloy (HEA). The calculations unravel the underlying mechanism of robust superconductivity, stemming from a compensation effect between varying electronic and phonon properties under pressure. The results also reveal how structural and chemical disorders modify the superconducting state. The first-principles Tc values agree quantitatively with the experiments throughout the entire pressure range under study. Our work thereby paves the way for exploring superconducting HEAs under pressure via advanced first principles simulations. 

Collaborative perception enables connected vehicles to share information, overcoming occlusions and extending the limited sensing range inherent in single-agent (non-collaborative) systems. Existing vision-only methods for 3D semantic occupancy prediction commonly rely on dense 3D voxels, which incur high communication costs, or 2D planar features, which require accurate depth estimation or additional supervision, limiting their applicability to collaborative scenarios. To address these challenges, we propose the first approach leveraging sparse 3D semantic Gaussian splatting for collaborative 3D semantic occupancy prediction. By sharing and fusing intermediate Gaussian primitives, our method provides three benefits: a neighborhood-based cross-agent fusion that removes duplicates and suppresses noisy or inconsistent Gaussians; a joint encoding of geometry and semantics in each primitive, which reduces reliance on depth supervision and allows simple rigid alignment; and sparse, object-centric messages that preserve structural information while reducing communication volume. Extensive experiments demonstrate that our approach outperforms single-agent perception and baseline collaborative methods by +8.42 and +3.28 points in mIoU, and +5.11 and +22.41 points in IoU, respectively. When further reducing the number of transmitted Gaussians, our method still achieves a +1.9 improvement in mIoU, using only 34.6% communication volume, highlighting robust performance under limited communication budgets. 

Ultrafast spectroscopy has advanced our understanding of chemical reaction mechanisms on molecular time scales, guiding the rational design of molecular systems and processes with spatial (atomic, nuclear) and temporal (electronic, vibrational) precisions. Kinetic analysis of ultrafast spectroscopic measurements yields valuable insights into the physical mechanisms that determine the behavior of a wide range of important chemical systems from chromophores and fluorescent proteins to nanosystems. One powerful and widely used method is global analysis, which uses a unified kinetic description of the entire spectrum. Importantly, interpretation of fit parameters to build a mechanistic understanding relies on an accurate estimate of the uncertainty. Software and numerical techniques using global analysis to fit data are well-developed; however, there is much less work on uncertainty analysis of the resulting kinetic parameters. Due to the nonlinear nature of modeling, traditional methods tend to underestimate the uncertainty. Building on previous work, we implement Markov chain Monte Carlo (MCMC) sampling to estimate the parameter uncertainty. We develop a procedure that can be readily included in the existing analysis software and demonstrate it on a series of generated and experimental femtosecond transient absorption data sets. Our results suggest that global analysis, using the simultaneously collected spectral data at many wavelengths, is crucial for accurate parameter estimation. The retrieved parameter uncertainty is well within 10% for a typical spectral data set with reasonable signal-to-noise ratios. 

We present a first-principles study based on density functional theory (DFT) on the electronic and structural properties of Ta2⁢NiSe5, a layered transition metal chalcogenide that has been considered as a possible candidate for an excitonic insulator. Our systematic DFT results however provide a nonexcitonic mechanism for the experimentally observed electronic and structural phase transitions in Ta2⁢NiSe5, in particular explaining why sulfur substitution of selenium reduces the distortion angle in the low-temperature phase and potassium dosing closes the gap in the electronic structure. Moreover, the calculations show that these two effects couple to each other. Further, our first-principles calculations predict several changes in both the crystal structure and electronic structure under the effects of uniform charge dosing and uniaxial strain, which could be tested experimentally. 

Fluorescent proteins (FPs) are noninvasive genetically encodable probes that have revolutionized bioimaging and health fields with vivid images and an ever-growing repertoire from jellyfish to sea anemones and corals. Inside the protein matrix, chromophore nonplanarity and flexibility have long been argued to govern the fluorescence efficiency of FPs, yet their fundamental roles and relative importance have been elusive which hinder the rational design of versatile FPs and biosensors. Herein, we tackle this central question by investigating two recently engineered FP-based turn-on chloride (Cl^–) sensors, ChlorON1 and 3, using an ultrafast electronic and vibrational spectroscopic toolset together with advanced multireference simulations for both structure and spectrum. We elucidate that fluorescence enhancement of the chloride-bound ChlorON3 stems from a substantially more twisted chromophore than ChlorON1 via comprehensive simulations starting from the available crystal structure of parent protein (mNeonGreen), also featuring an enhanced radiative pathway due to an adjacent leucine residue in the emissive population. This finding indicates that the commonly stated chromophore planarity is not, but conformational rigidity is, the decisive factor for high fluorescence efficiency. Such mechanistic insights into FPs are generalizable to chromoproteins and other photosensitive biomolecules, which can facilitate the targeted design of brighter and/or tunable biosensors. 

Photoconvertible fluorescent proteins (pcFPs) have enabled exquisite images of cellular structures due to their genetic encodability and red-shifted emission with high brightness, hence receiving increased traction in the field. However, the red form of Kaede-like pcFPs after photoconversion remains underexplored. We implemented ultrafast electronic and vibrational spectroscopies on the red Kaede chromophore in solution vs the protein pocket of the least-evolved ancestor (LEA, a Kaede-like green-to-red pcFP) to gain crucial insights into the photophysical processes of the chromophore. The measured fluorescence quantum yield (FQY) values were correlated with ultrafast dynamics to reveal that hydrogen-bonding interactions with the solvent can quench the excited-state Kaede in solution. A viscosity-dependent sub-ps decay indicates nonradiative relaxation involving swift chromophore conformational motions. Femtosecond transient absorption and stimulated Raman spectroscopy (FSRS) reveal an additional ∼1 ps decay of the photoconverted red form of LEA that is absent in green LEA before photoconversion. Transient structural dynamics from FSRS elucidate this decay to involve the phenolate and imidazolinone ring twists that are implicated during cis → trans isomerization and on → off photoswitching in phototransformable fluorescent proteins (FPs). Compared to green-emitting species, the FQY of red LEA (∼0.58) and many other red FPs are often reduced, limiting their applications in modern bioimaging techniques. By shining more light on the often overlooked photoconverted form of pcFPs with ultrafast spectroscopies, we envision such essential mechanistic insights to enable a bottom-up approach for rationally improving the brightness of red-emitting LEA and many other controllable bioprobes, including FPs.