Matter Sciences

52 items

Machine Learning Science and Technology Sep 25, 2026
The authors introduce Projected Hessian Learning (PHL), which supervises second-order curvature in machine-learning interatomic potentials (MLIPs) through stochastic Hutchinson-trace-based Hessian-vector product (HVP) projections instead of explicit Hessian construction; on a ωB97XD/6-31G(d) dataset of reactants, products, transition states, IRC and normal-mode-sampled geometries they compare four schemes (E-F, E-F-HVP with one-column or Hutchinson probes, and E-F-H), finding that with probe vectors resampled each minibatch both HVP methods are statistically indistinguishable from full-Hessian training in energy, force and Hessian accuracy while giving more than 24x speedup per epoch, and that under the more realistic fixed-vector regime with one HVP per molecule Hutchinson projections con
The authors introduce Projected Hessian Learning (PHL), which supervises second-order curvature in machine-learning interatomic potentials (MLIPs) through stochastic Hutchinson-trace-based Hessian-vector product (HVP) projections instead of explicit Hessian construction; on a ωB97XD/6-31G(d) dataset of reactants, products, transition states, IRC and normal-mode-sampled geometries they compare four schemes (E-F, E-F-HVP with one-column or Hutchinson probes, and E-F-H), finding that with probe vectors resampled each minibatch both HVP methods are statistically indistinguishable from full-Hessian training in energy, force and Hessian accuracy while giving more than 24x speedup per epoch, and that under the more realistic fixed-vector regime with one HVP per molecule Hutchinson projections con
Replacing full-Hessian supervision with random projected Hessian-vector products matches second-order accuracy while speeding each epoch by more than 24x
The authors introduce Projected Hessian Learning (PHL), which supervises second-order curvature in machine-learning interatomic potentials (MLIPs) through stochastic Hutchinson-trace-based Hessian-vector product (HVP) projections instead of explicit Hessian construction; on a ωB97XD/6-31G(d) dataset of reactants, products, transition states, IRC and normal-mode-sampled geometries they compare four schemes (E-F, E-F-HVP with one-column or Hutchinson probes, and E-F-H), finding that with probe vectors resampled each minibatch both HVP methods are statistically indistinguishable from full-Hessian training in energy, force and Hessian accuracy while giving more than 24x speedup per epoch, and that under the more realistic fixed-vector regime with one HVP per molecule Hutchinson projections con
The authors introduce Projected Hessian Learning (PHL), which supervises second-order curvature in machine-learning interatomic potentials (MLIPs) through stochastic Hutchinson-trace-based Hessian-vector product (HVP) projections instead of explicit Hessian construction; on a ωB97XD/6-31G(d) dataset of reactants, products, transition states, IRC and normal-mode-sampled geometries they compare four schemes (E-F, E-F-HVP with one-column or Hutchinson probes, and E-F-H), finding that with probe vectors resampled each minibatch both HVP methods are statistically indistinguishable from full-Hessian training in energy, force and Hessian accuracy while giving more than 24x speedup per epoch, and that under the more realistic fixed-vector regime with one HVP per molecule Hutchinson projections con
Nature News Sep 25, 2026
An analysis of roughly 1.3 million chemical reactions in patents from 1976 to 2016 found that solvents classed as hazardous rose from about 60% of patented reactions in 1976 to above 70% by 2016, that when regulations restrict a toxic solvent chemists are more likely to switch to another hazardous liquid than to a greener alternative, and that use of trifluoroacetic acid (TFA) rose substantially; the analysis drew on an existing USPTO-derived reaction database and used Rxn-INSIGHT, an AI system developed by Dobbelaere that digests chemical databases and answers queries about which reagents, catalysts and solvents to use.
An analysis of roughly 1.3 million chemical reactions in patents from 1976 to 2016 found that solvents classed as hazardous rose from about 60% of patented reactions in 1976 to above 70% by 2016, that when regulations restrict a toxic solvent chemists are more likely to switch to another hazardous liquid than to a greener alternative, and that use of trifluoroacetic acid (TFA) rose substantially; the analysis drew on an existing USPTO-derived reaction database and used Rxn-INSIGHT, an AI system developed by Dobbelaere that digests chemical databases and answers queries about which reagents, catalysts and solvents to use.
Four decades of patented reactions: hazardous solvents rose from about 60% to over 70%, and restrictions mostly pushed chemists to another hazardous liquid
An analysis of roughly 1.3 million chemical reactions in patents from 1976 to 2016 found that solvents classed as hazardous rose from about 60% of patented reactions in 1976 to above 70% by 2016, that when regulations restrict a toxic solvent chemists are more likely to switch to another hazardous liquid than to a greener alternative, and that use of trifluoroacetic acid (TFA) rose substantially; the analysis drew on an existing USPTO-derived reaction database and used Rxn-INSIGHT, an AI system developed by Dobbelaere that digests chemical databases and answers queries about which reagents, catalysts and solvents to use.
An analysis of roughly 1.3 million chemical reactions in patents from 1976 to 2016 found that solvents classed as hazardous rose from about 60% of patented reactions in 1976 to above 70% by 2016, that when regulations restrict a toxic solvent chemists are more likely to switch to another hazardous liquid than to a greener alternative, and that use of trifluoroacetic acid (TFA) rose substantially; the analysis drew on an existing USPTO-derived reaction database and used Rxn-INSIGHT, an AI system developed by Dobbelaere that digests chemical databases and answers queries about which reagents, catalysts and solvents to use.
Communications Physics Sep 24, 2026
The authors introduce a general framework based on Lie-algebraic properties that maps a pool of Pauli operators to a binary matrix ΓA over F2, proves that pool completeness and minimality can be decided in polynomial O(N³) time via the rank and congruence relations of that matrix, uses it to construct minimal complete pools (MCPs), proposes MB-ADAPT-VQE (adding a batch of k operators per iteration) to cut measurement overhead and accelerate convergence in quantum chemistry, and extends the fixed-ansatz NI-DUCC-VQE method, previously limited to N≤14 qubits by the MCP construction bottleneck, to a 26-qubit H2O system.
The authors introduce a general framework based on Lie-algebraic properties that maps a pool of Pauli operators to a binary matrix ΓA over F2, proves that pool completeness and minimality can be decided in polynomial O(N³) time via the rank and congruence relations of that matrix, uses it to construct minimal complete pools (MCPs), proposes MB-ADAPT-VQE (adding a batch of k operators per iteration) to cut measurement overhead and accelerate convergence in quantum chemistry, and extends the fixed-ansatz NI-DUCC-VQE method, previously limited to N≤14 qubits by the MCP construction bottleneck, to a 26-qubit H2O system.
Mapping Pauli pools to F2 binary matrices lets the authors certify minimal complete pools in O(N³) by matrix rank and push NI-DUCC-VQE to a 26-qubit H2O
The authors introduce a general framework based on Lie-algebraic properties that maps a pool of Pauli operators to a binary matrix ΓA over F2, proves that pool completeness and minimality can be decided in polynomial O(N³) time via the rank and congruence relations of that matrix, uses it to construct minimal complete pools (MCPs), proposes MB-ADAPT-VQE (adding a batch of k operators per iteration) to cut measurement overhead and accelerate convergence in quantum chemistry, and extends the fixed-ansatz NI-DUCC-VQE method, previously limited to N≤14 qubits by the MCP construction bottleneck, to a 26-qubit H2O system.
The authors introduce a general framework based on Lie-algebraic properties that maps a pool of Pauli operators to a binary matrix ΓA over F2, proves that pool completeness and minimality can be decided in polynomial O(N³) time via the rank and congruence relations of that matrix, uses it to construct minimal complete pools (MCPs), proposes MB-ADAPT-VQE (adding a batch of k operators per iteration) to cut measurement overhead and accelerate convergence in quantum chemistry, and extends the fixed-ansatz NI-DUCC-VQE method, previously limited to N≤14 qubits by the MCP construction bottleneck, to a 26-qubit H2O system.
PRX Intelligence Sep 24, 2026
The work introduces SMARTERS, an Attention U-Net encoder-decoder trained on simulated TERS hyperspectral images of 1,840 planar small molecules, which maps vibrational spectral images directly to 2D atomic position maps (mean test Dice similarity coefficient 0.842) and to chemically resolved maps per element (H, C, N, O; mean test 0.810), showing that automated molecular structure identification from TERS images is feasible on simulated data without conventional manual comparison and case-by-case quantum-chemistry calculations.
The work introduces SMARTERS, an Attention U-Net encoder-decoder trained on simulated TERS hyperspectral images of 1,840 planar small molecules, which maps vibrational spectral images directly to 2D atomic position maps (mean test Dice similarity coefficient 0.842) and to chemically resolved maps per element (H, C, N, O; mean test 0.810), showing that automated molecular structure identification from TERS images is feasible on simulated data without conventional manual comparison and case-by-case quantum-chemistry calculations.
SMARTERS uses an Attention U-Net to predict planar molecular structures directly from simulated TERS hyperspectral images, reaching a mean test Dice of 0.842
The work introduces SMARTERS, an Attention U-Net encoder-decoder trained on simulated TERS hyperspectral images of 1,840 planar small molecules, which maps vibrational spectral images directly to 2D atomic position maps (mean test Dice similarity coefficient 0.842) and to chemically resolved maps per element (H, C, N, O; mean test 0.810), showing that automated molecular structure identification from TERS images is feasible on simulated data without conventional manual comparison and case-by-case quantum-chemistry calculations.
The work introduces SMARTERS, an Attention U-Net encoder-decoder trained on simulated TERS hyperspectral images of 1,840 planar small molecules, which maps vibrational spectral images directly to 2D atomic position maps (mean test Dice similarity coefficient 0.842) and to chemically resolved maps per element (H, C, N, O; mean test 0.810), showing that automated molecular structure identification from TERS images is feasible on simulated data without conventional manual comparison and case-by-case quantum-chemistry calculations.
arXiv Sep 24, 2026
Using Fisher information and random matrix theory, the authors derive a closed-form expression for the noise-induced error of chaotic/diffusive reconstructive spectrometers, linking the variance bound σ²_ε Tr[(AᵀA)⁺] to the spectral correlation length Γ_corr, mean transmittance T₀, and the numbers of frequency channels N and measurement channels M, establish conditions for super-resolution, and validate the theory with a random matrix model and full-wave FDTD simulations, where the predicted optimal on-chip cavity size is about 17.9 µm.
Using Fisher information and random matrix theory, the authors derive a closed-form expression for the noise-induced error of chaotic/diffusive reconstructive spectrometers, linking the variance bound σ²_ε Tr[(AᵀA)⁺] to the spectral correlation length Γ_corr, mean transmittance T₀, and the numbers of frequency channels N and measurement channels M, establish conditions for super-resolution, and validate the theory with a random matrix model and full-wave FDTD simulations, where the predicted optimal on-chip cavity size is about 17.9 µm.
Random matrix theory yields a closed-form noise-error bound for reconstructive spectrometers and predicts a 17.9 µm optimal cavity in on-chip FDTD
Using Fisher information and random matrix theory, the authors derive a closed-form expression for the noise-induced error of chaotic/diffusive reconstructive spectrometers, linking the variance bound σ²_ε Tr[(AᵀA)⁺] to the spectral correlation length Γ_corr, mean transmittance T₀, and the numbers of frequency channels N and measurement channels M, establish conditions for super-resolution, and validate the theory with a random matrix model and full-wave FDTD simulations, where the predicted optimal on-chip cavity size is about 17.9 µm.
Using Fisher information and random matrix theory, the authors derive a closed-form expression for the noise-induced error of chaotic/diffusive reconstructive spectrometers, linking the variance bound σ²_ε Tr[(AᵀA)⁺] to the spectral correlation length Γ_corr, mean transmittance T₀, and the numbers of frequency channels N and measurement channels M, establish conditions for super-resolution, and validate the theory with a random matrix model and full-wave FDTD simulations, where the predicted optimal on-chip cavity size is about 17.9 µm.
arXiv (Cornell University) Sep 24, 2026
This work reports that bimetallic nanoparticles can form a thermodynamically controlled "shell-dimer" architecture; using Au-Rh as a model system, atomic-resolution imaging and molecular dynamics show that an ultrathin Au overlayer forms on Rh, stabilized by competition among surface, interfacial, and strain energies, with anisotropic strain limiting its growth to the subnanometer scale and changes in surface chemistry able to destabilize it altogether; across a range of bimetallic nanoparticles, overlayer formation is associated with elemental immiscibility and lattice mismatch.
This work reports that bimetallic nanoparticles can form a thermodynamically controlled "shell-dimer" architecture; using Au-Rh as a model system, atomic-resolution imaging and molecular dynamics show that an ultrathin Au overlayer forms on Rh, stabilized by competition among surface, interfacial, and strain energies, with anisotropic strain limiting its growth to the subnanometer scale and changes in surface chemistry able to destabilize it altogether; across a range of bimetallic nanoparticles, overlayer formation is associated with elemental immiscibility and lattice mismatch.
Au-Rh bimetallic nanoparticles spontaneously form subnanometer Au overlayers whose thickness is limited by anisotropic strain
This work reports that bimetallic nanoparticles can form a thermodynamically controlled "shell-dimer" architecture; using Au-Rh as a model system, atomic-resolution imaging and molecular dynamics show that an ultrathin Au overlayer forms on Rh, stabilized by competition among surface, interfacial, and strain energies, with anisotropic strain limiting its growth to the subnanometer scale and changes in surface chemistry able to destabilize it altogether; across a range of bimetallic nanoparticles, overlayer formation is associated with elemental immiscibility and lattice mismatch.
This work reports that bimetallic nanoparticles can form a thermodynamically controlled "shell-dimer" architecture; using Au-Rh as a model system, atomic-resolution imaging and molecular dynamics show that an ultrathin Au overlayer forms on Rh, stabilized by competition among surface, interfacial, and strain energies, with anisotropic strain limiting its growth to the subnanometer scale and changes in surface chemistry able to destabilize it altogether; across a range of bimetallic nanoparticles, overlayer formation is associated with elemental immiscibility and lattice mismatch.
Angewandte Chemie International Edition Sep 23, 2026
Using atomistic simulations with an ab initio-quality machine learning potential, this work investigates aqueous LiMn2O4 (LMO) interfaces across varying lithiation states and shows that local Li content determines surface Mn oxidation states and governs interfacial acid-base chemistry, identifies the O-H stretching band as a sensitive spectroscopic probe of the surface electronic structure whose oxidation-state-dependent shifts reveal that the mixed-valence spinel surface hosts coexisting Lewis-acidic centers and neighboring oxygen sites susceptible to electrophilic attack, extending the conventional acid-centric view of Mn dissolution toward a dual-site mechanism.
Using atomistic simulations with an ab initio-quality machine learning potential, this work investigates aqueous LiMn2O4 (LMO) interfaces across varying lithiation states and shows that local Li content determines surface Mn oxidation states and governs interfacial acid-base chemistry, identifies the O-H stretching band as a sensitive spectroscopic probe of the surface electronic structure whose oxidation-state-dependent shifts reveal that the mixed-valence spinel surface hosts coexisting Lewis-acidic centers and neighboring oxygen sites susceptible to electrophilic attack, extending the conventional acid-centric view of Mn dissolution toward a dual-site mechanism.
Machine-learning-potential simulations show that local Li content sets Mn oxidation states at LiMn2O4 surfaces and that the O-H stretch band exposes a dual-site acid-attack vulnerability
Using atomistic simulations with an ab initio-quality machine learning potential, this work investigates aqueous LiMn2O4 (LMO) interfaces across varying lithiation states and shows that local Li content determines surface Mn oxidation states and governs interfacial acid-base chemistry, identifies the O-H stretching band as a sensitive spectroscopic probe of the surface electronic structure whose oxidation-state-dependent shifts reveal that the mixed-valence spinel surface hosts coexisting Lewis-acidic centers and neighboring oxygen sites susceptible to electrophilic attack, extending the conventional acid-centric view of Mn dissolution toward a dual-site mechanism.
Using atomistic simulations with an ab initio-quality machine learning potential, this work investigates aqueous LiMn2O4 (LMO) interfaces across varying lithiation states and shows that local Li content determines surface Mn oxidation states and governs interfacial acid-base chemistry, identifies the O-H stretching band as a sensitive spectroscopic probe of the surface electronic structure whose oxidation-state-dependent shifts reveal that the mixed-valence spinel surface hosts coexisting Lewis-acidic centers and neighboring oxygen sites susceptible to electrophilic attack, extending the conventional acid-centric view of Mn dissolution toward a dual-site mechanism.
Nature News Sep 23, 2026
A team at the National University of Singapore built a single-ion optical clock from the rare-earth metal lutetium that is reported as the most accurate timekeeper yet, four times more accurate than the previous best calcium-ion clock, and verified it by comparing two lutetium clocks whose ticks matched to the 19th digit, a result published in Nature and framed as potentially underpinning a redefinition of the second and gravity mapping.
A team at the National University of Singapore built a single-ion optical clock from the rare-earth metal lutetium that is reported as the most accurate timekeeper yet, four times more accurate than the previous best calcium-ion clock, and verified it by comparing two lutetium clocks whose ticks matched to the 19th digit, a result published in Nature and framed as potentially underpinning a redefinition of the second and gravity mapping.
A lutetium-ion optical clock sets a new accuracy mark, with two clocks agreeing to the 19th digit
A team at the National University of Singapore built a single-ion optical clock from the rare-earth metal lutetium that is reported as the most accurate timekeeper yet, four times more accurate than the previous best calcium-ion clock, and verified it by comparing two lutetium clocks whose ticks matched to the 19th digit, a result published in Nature and framed as potentially underpinning a redefinition of the second and gravity mapping.
A team at the National University of Singapore built a single-ion optical clock from the rare-earth metal lutetium that is reported as the most accurate timekeeper yet, four times more accurate than the previous best calcium-ion clock, and verified it by comparing two lutetium clocks whose ticks matched to the 19th digit, a result published in Nature and framed as potentially underpinning a redefinition of the second and gravity mapping.
Nature News Sep 23, 2026
Using a two-step route that first reacts boron with sodium under high pressure and then heats the mixture at 400 °C under vacuum to almost completely remove sodium, researchers prepared a new boron allotrope, Imma-B60, whose boron-atom network retains open space where sodium atoms once sat, enabling dislocation slip so the material stretches to 23% of its original length before breaking without springing back, and whose electrical conductivity exceeds that of typical boron materials by more than a million times.
Using a two-step route that first reacts boron with sodium under high pressure and then heats the mixture at 400 °C under vacuum to almost completely remove sodium, researchers prepared a new boron allotrope, Imma-B60, whose boron-atom network retains open space where sodium atoms once sat, enabling dislocation slip so the material stretches to 23% of its original length before breaking without springing back, and whose electrical conductivity exceeds that of typical boron materials by more than a million times.
A New Boron Allotrope, Imma-B60: Deformable and a Million Times More Conductive
Using a two-step route that first reacts boron with sodium under high pressure and then heats the mixture at 400 °C under vacuum to almost completely remove sodium, researchers prepared a new boron allotrope, Imma-B60, whose boron-atom network retains open space where sodium atoms once sat, enabling dislocation slip so the material stretches to 23% of its original length before breaking without springing back, and whose electrical conductivity exceeds that of typical boron materials by more than a million times.
Using a two-step route that first reacts boron with sodium under high pressure and then heats the mixture at 400 °C under vacuum to almost completely remove sodium, researchers prepared a new boron allotrope, Imma-B60, whose boron-atom network retains open space where sodium atoms once sat, enabling dislocation slip so the material stretches to 23% of its original length before breaking without springing back, and whose electrical conductivity exceeds that of typical boron materials by more than a million times.
Nature News Sep 22, 2026
This evidence bundle centres on a Nature news feature reporting that Bruker will ship GAIA, described as the first scanning transmission electron microscope to operate stably near absolute zero with liquid helium, to three laboratories in Canada, Germany and the United States, where it can image materials at about −266 °C (7 kelvin) for 30 hours or more, while tracing the earlier route: a 2025 US-reported TEM attachment reaching −253 °C (20 kelvin) with atomic-resolution imaging stable for more than ten hours, a condenZero liquid-helium attachment at around 4 kelvin for 24 hours that did not aim for atomic resolution, and Idrobo's 2021 comment on aberration correction combined with further instrument developments.
This evidence bundle centres on a Nature news feature reporting that Bruker will ship GAIA, described as the first scanning transmission electron microscope to operate stably near absolute zero with liquid helium, to three laboratories in Canada, Germany and the United States, where it can image materials at about −266 °C (7 kelvin) for 30 hours or more, while tracing the earlier route: a 2025 US-reported TEM attachment reaching −253 °C (20 kelvin) with atomic-resolution imaging stable for more than ten hours, a condenZero liquid-helium attachment at around 4 kelvin for 24 hours that did not aim for atomic resolution, and Idrobo's 2021 comment on aberration correction combined with further instrument developments.
Ultra-cold microscopy reaches the lab: the liquid-helium STEM GAIA and the road to atomic-resolution cryogenic imaging
This evidence bundle centres on a Nature news feature reporting that Bruker will ship GAIA, described as the first scanning transmission electron microscope to operate stably near absolute zero with liquid helium, to three laboratories in Canada, Germany and the United States, where it can image materials at about −266 °C (7 kelvin) for 30 hours or more, while tracing the earlier route: a 2025 US-reported TEM attachment reaching −253 °C (20 kelvin) with atomic-resolution imaging stable for more than ten hours, a condenZero liquid-helium attachment at around 4 kelvin for 24 hours that did not aim for atomic resolution, and Idrobo's 2021 comment on aberration correction combined with further instrument developments.
This evidence bundle centres on a Nature news feature reporting that Bruker will ship GAIA, described as the first scanning transmission electron microscope to operate stably near absolute zero with liquid helium, to three laboratories in Canada, Germany and the United States, where it can image materials at about −266 °C (7 kelvin) for 30 hours or more, while tracing the earlier route: a 2025 US-reported TEM attachment reaching −253 °C (20 kelvin) with atomic-resolution imaging stable for more than ten hours, a condenZero liquid-helium attachment at around 4 kelvin for 24 hours that did not aim for atomic resolution, and Idrobo's 2021 comment on aberration correction combined with further instrument developments.

Page 3 · showing 10