ライフサイエンスコーパス: interatomic

1 This distortion of electron density off an interatomic axis is often described as a 'banana-bond.'

2 island growth mode because of the high Rh-Rh interatomic binding energy.

3 the unit cell volume, as well as in specific interatomic bond lengths and bond angles.

4 (6) polyhedra are highly distorted, with the interatomic bond lengths ranging from 1.690 to 1.847 A a

5 rain boundary, the large Bi atoms weaken the interatomic bonding by pushing apart the Cu atoms at the

6 Interatomic bonding is stronger in Cr2AlC than Zr2AlC bu

7 for characterizing the atomic structure and interatomic bonding of molecules associated with extraor

8 es calculations on the electronic structure, interatomic bonding, optical, and mechanical properties

9 by informing them of the physical nature of interatomic bonding.

10 s are retained on large deformation but weak interatomic bonds lead to compromised strength.

11 Surface atoms have fewer interatomic bonds than those in the bulk that they often

12 ield sensitivity of the anharmonicity of the interatomic bonds that govern the probability of phonon-

13 nitrogen exhibits one of the strongest known interatomic bonds, while xenon possesses a closed-shell

14 that provide quantitative information on the interatomic connectivity and distance distributions.

15 energy based on accessible surface area and interatomic contact areas.

16 ital interactions that fail to explain short interatomic contact distances.

17 revealed a docking strategy, and associated interatomic contacts, which was notably distinct from th

18 positions 10 and 97, which corresponds to 13 interatomic contacts.

19 Auger decay, the long-lived ones decay by an interatomic Coulombic decay between two iodine atoms, du

20 A well-known example is interatomic Coulombic decay, where an excited atom relax

21 We demonstrate that the interatomic coupling between two two-dimensional crystal

22 We parametrise interatomic coupling for carbon atoms by studying twiste

23 ), large static disorder and dynamical bond (interatomic) disorder that is poorly modeled within the

24 non-local van der Waals density functionals, interatomic dispersion models within many-body and pairw

25 on, coupled with a >30 A decrease in maximum interatomic distance (D(max)) by small angle x-ray scatt

26 rience a progressive increase in the average interatomic distance and gradually settle to form dome-s

27 This is because the increased interatomic distance at dislocation cores raises the mig

28 orobenzo[g]chrysene, where the short 2.055 A interatomic distance between bay-region F-9 and H-8, dow

29 y barrier arising from the decreased average interatomic distance between the A-site cation and iodid

30 um exceeding 1000 quanta per particle and an interatomic distance comparable to the cyclotron orbit.

31 R methods, specifically in sorting ambiguous interatomic distance constraints into classes that defin

32 The interatomic distance constraints were all consistent wit

33 the crystal structure of ADP-kinesin, and by interatomic distance constraints.

34 e fundamental to further analysis, including interatomic distance distribution calculation and low-re

35 e break-junction technique, we find that the interatomic distance in platinum atomic wires is shorter

36 lysine-lysine (K-K) cross-linkers to obtain interatomic distance information.

37 mean free path is approximately equal to the interatomic distance is a challenging problem.

38 y different from uncondensed atoms, with the interatomic distance larger than the average by about 10

39 spectroscopy could be broadly applicable for interatomic distance measurements in other spin-7/2-spin

40 Experimental data, such as interatomic distance measurements, are then used to sele

41 red amorphous Se(0) with a first shell Se-Se interatomic distance of 2.339 +/- 0.003 A.

42 structure (EXAFS) spectroscopy showed a Cu-S interatomic distance of 2.55 A.

43 sters embedded in helium droplets reveals an interatomic distance of 3.65 A, much closer to the value

44 ies was improved by the use of time-averaged interatomic distance restraints derived from (1)H NMR.

45 The 7-fold increase of density brings the interatomic distance to 1.74 angstrom well within the in

46 served on the globally derived Dmax (maximal interatomic distance), although under comparable conditi

47 es and functions were supported by sequence, interatomic distance, and B-factor information on intera

48 ciated with typical orbital characteristics, interatomic distance, and stability.

49 The extent of interaction is measured by interatomic distance, NBO second-order perturbative anal

50 hat on average scales exponentially with the interatomic distance.

51 ere the phonon mean free path approaches the interatomic distance.

52 etected on the radius of gyration or maximum interatomic distance.

53 binding of the two metals at an ultra-short interatomic distance.

54 irregular oscillations as a function of the interatomic distance.

55 tself as a stationary state at a preordained interatomic distance.

56 ngs (13.8 +/- 1.4 Hz for surface silica) and interatomic distances (3.04 +/- 0.08 A for surface silic

57 Deduced interatomic distances agreed closely with previous radia

58 s is the most common feature that alters the interatomic distances and band structure, providing a ne

59 The evolution of bond angle distributions, interatomic distances and coordination numbers are exami

60 aled a strong relationship between predicted interatomic distances and empirically observed thermodyn

61 rimental noise, FoXS explicitly computes all interatomic distances and implicitly models the first hy

62 of 2.3041(12) and 2.1949(28) A for the As-P interatomic distances and the P-P interatomic distances,

63 but technically challenging due to the small interatomic distances and the similar atomic numbers.

64 n function shows redistribution of the Zr-Zr interatomic distances and their shift towards smaller va

65 Although the interatomic distances are suggestive of agostic-type int

66 )/H(N), H(N)/H(alpha), and H(alpha)/H(alpha) interatomic distances as well as (1)H NMR chemical shift

67 following: (i) very close agreement between interatomic distances at the metal coordination site for

68 ates the possibility of engineering specific interatomic distances between lone pair-bearing cations

69 The anion is essentially linear with interatomic distances C-N = 1.150(6) angstrom and C-Te =

70 esonance spectroscopy, from which long-range interatomic distances can be estimated.

71 The interatomic distances constrain the Trp41 side-chain con

72 of two highly excited Rydberg atoms-feature interatomic distances easily exceeding optical wavelengt

73 The Ge-Se interatomic distances extracted from XAS data show a two

74 cture reconstruction from precise unassigned interatomic distances for a range of clusters.

75 methodology for the measurement of specific interatomic distances from a combination of theoretical

76 nstrating the use of (17)O NMR to quantitate interatomic distances in a fully labeled dipeptide.

77 (FRET) provides a unique means of measuring interatomic distances in biological molecules in real ti

78 ls and already display significantly shorter interatomic distances in comparison to van der Waals (vd

79 ray absorption edge, can be used to identify interatomic distances in materials.

80 ents such as (H)CF, (H)CHF, and FF can yield interatomic distances in the 8-16 angstrom range.

81 to the structure, light-triggered changes in interatomic distances in the azobenzene moiety are able

82 the prediction of Cr oxidation states, mean interatomic distances in the first coordination sphere,

83 For example, the surface groups control interatomic distances in the MXene lattice, and Ti (n) (

84 ies at intermediate angles, corresponding to interatomic distances in the range of 5-20 A, are partic

85 Analysis of the interatomic distances in the superconducting substance K

86 riments reveal a strong sensitivity of Tc to interatomic distances in the underdoped regime (x </= 0.

87 king of intermetallics: correlations between interatomic distances lead to the inability of a phase t

88 aphy; (ii) similarly close agreement between interatomic distances measured by EXAFS for the Pb(2+)-G

89 bonds of halonium ions show Bondi normalized interatomic distances of 0.6-0.7 and possess both charge

90 eptides showed significant deviations in the interatomic distances of critical electrophile-binding a

91 The lifetime and interatomic distances of the isomer are consistent with

92 t, relatively large cutoffs for matching the interatomic distances of the stem residues have to be us

93 n with fragments roaming at relatively large interatomic distances rather than following conventional

94 are in stoichiometric compounds with precise interatomic distances rather than random alloys.

95 ructures with intralayer halogen bonds, with interatomic distances shorter than the sum of the van de

96 cluded were partial atomic charges and three interatomic distances that define the relative spatial d

97 honon mean free path reaches parity with the interatomic distances therein.

98 d-state NMR spectroscopy primarily relies on interatomic distances up to 8 angstrom, extracted from (

99 ion fine structure data revealed that As...C interatomic distances were relatively longer in arsenate

100 ifts ((13)C and (15)N NMR) and corresponding interatomic distances which are combined into a 3D abstr

101 ich allows for a systematic variation of the interatomic distances while maintaining the same number

102 he capping agent, we identify three distinct interatomic distances within 2.5 angstrom from the parti

103 rt direct determination of how variations in interatomic distances within individual crystalline unit

104 differences were noted in the kringle/ligand interatomic distances within the monomeric components of

105 structural insights on ligand coordination, interatomic distances, and positioning of catalytic amin

106 ion on the distribution of electron density, interatomic distances, and the orientation dependence of

107 ynamic parameters, can profoundly change the interatomic distances, electronic interactions, chemical

108 the recolliding electron is on the order of interatomic distances, i.e., approximately 1.5 A, small

109 otoluene in DNA/RNA have indicated, based on interatomic distances, possible hydrogen bonding interac

110 an updated value of 2.1994(3) A for the P-P interatomic distances, reconciling conflicting literatur

111 r the As-P interatomic distances and the P-P interatomic distances, respectively.

112 an analysis of the lattice periodicities and interatomic distances, we rationalize why the Ba phases

113 l shifts in terms of polynomial functions of interatomic distances.

114 uding chemical shifts, torsional angles, and interatomic distances.

115 d angles, dihedral angles, bond lengths, and interatomic distances.

116 rbonyl group with a strong dependency on the interatomic distances.

117 cs-derived structures reproduced NMR-derived interatomic distances.

118 on lifetimes and mean free paths approaching interatomic distances.

119 ime-dependent changes in the distribution of interatomic distances.

120 lecular electron transfer process over large interatomic distances.

121 be weaker than deduced from the non-hydrogen interatomic distances.

122 ion at other contacts, resulting in nonideal interatomic distances.

123 ous native structures of proteins arise from interatomic driving forces encoded within their amino ac

124 ferromagnetic Gd(2)CCl caused by attenuating interatomic exchange interactions, consistent with theor

125 zation indices and quantum chemical topology interatomic exchange-correlation energies that are measu

126 e Allen-Feldman model in glasses, leveraging interatomic force constants and normal-mode linewidths c

127 A pronounced disparity in interatomic force constants gives rise to highly localiz

128 lattice dynamics, we compute the anharmonic interatomic force constants up to the fourth order and u

129 Upon folding, proteins develop a peak in the interatomic force distributions that falls on a universa

130 Architector leverages metal-center symmetry, interatomic force fields, and tight binding methods to b

131 etical predictions, enabling us to probe the interatomic force parameters that are crucial to the pro

132 rdering of the lattice can occur because the interatomic forces are modified due to the excitation of

133 ing to 'learn' potential-energy surfaces and interatomic forces from reference calculations and then

134 At high excitation densities, the interatomic forces that bind solids and determine many o

135 protein based on classical approximations of interatomic forces, giving researchers insight into prot

136 e by the number of atoms within the range of interatomic forces, is difficult to visualize directly b

137 with parametrized equations to describe the interatomic forces.

138 onding, which translates into changes in the interatomic forces.

139 g and statistical mechanics to determine the interatomic interaction energies of a molecular system e

140 Interatomic interaction features extracted by InteracTor

141 ent metastable state of Ge2Sb2Te5 with muted interatomic interaction induced by a weakening of resona

142 The key influence of the soft Fe-Y interatomic interaction is investigated by ab-initio cal

143 re-prediction protocols require a customized interatomic interaction model on which the quality of th

144 These materials are characterized by weak interatomic interactions (van der Waals forces) between

145 on a physically meaningful separation of the interatomic interactions - and demonstrate its utility b

146 The considerations of interatomic interactions alone cannot explain the fractu

147 of non-crystalline materials using accurate interatomic interactions and experimental information.

148 ion is shown to be superfluous when suitable interatomic interactions are present.

149 nd physical systems as a result of competing interatomic interactions can be used as templates for fa

150 more itinerant electrons to soften repulsive interatomic interactions in a tight space.

151 three-dimensional (3D) structures, including interatomic interactions like hydrogen bonds, van der Wa

152 and (2) that potential sets used to describe interatomic interactions may be sufficiently accurate to

153 ling a significant influence of strong S...S interatomic interactions on the intramolecular distance

154 other proteins, and DNA, depend on specific interatomic interactions that can be classified on the b

155 In contrast, for C(2)H(2), the interatomic interactions that create bonds prevail over

156 Tuning the interatomic interactions that drive condensation, we sho

157 -bent and linear structures prevail over the interatomic interactions that induce bond formation.

158 e critical tests of our understanding of the interatomic interactions that underlie molecular biology

159 rect access to accurate bonded and nonbonded interatomic interactions via the Hellman-Feynman theorem

160 ulations of an optical lattice potential and interatomic interactions, and results in domains of atom

161 ode and structural compensations for altered interatomic interactions, in which lost TCR-peptide inte

162 nderstanding of the fundamental chemistry of interatomic interactions, the deep learning network is r

163 Using simple models for electronic and interatomic interactions, we show how crystals with iden

164 lattices, even in the presence of anharmonic interatomic interactions-a direct consequence of the Fer

165 ng, as is information on the nature of their interatomic interactions.

166 m size and shape is strongly affected by the interatomic interactions.

167 nts on the nanometer-scale are used to learn interatomic interactions.

168 diffusion probabilistic models for learning interatomic interactions.

169 elopment of efficient and accurate models of interatomic interactions.

170 pectroscopy was performed to demonstrate the interatomic interactions.

171 us overcoming usual requirement for a strong interatomic interactions.

172 ather than approximating them from models of interatomic interactions.

173 temperatures, arising from the hierarchy of interatomic interactions.

174 ing performance via targeted manipulation of interatomic/intermolecular interactions and resulting ph

175 e ratio of the interplanar spacing c and the interatomic, intraplanar spacing a of the h.c.p. lattice

176 Here, we argue that actually simple interatomic magnetic exchange interaction already contai

177 noble-metal nanomaterials due to the strong interatomic metallic bonding.

178 theoretical calculations are reported for an interatomic multi-atom resonant photoemission (MARPE) ef

179 sis, the target genes were mapped in complex interatomic networks representing molecular pathways, ce

180 Interatomic or intermolecular Coulombic decay (ICD) is a

181 landscape, can be related to the form of the interatomic or intermolecular potential.

182 of the metal-metal (M-M) bond distances and interatomic order-of Pt nanoclusters supported on a gamm

183 we propose High-order Tensor message Passing interatomic Potential (HotPP), an E(n) equivariant messa

184 resent the development of a machine learning interatomic potential (MLIP) called SuperSalt, which tar

185 Machine-learned interatomic potential (MLIP) coupled with replica-exchan

186 t (AQuaRef) based on AIMNet2 machine learned interatomic potential (MLIP) mimicking QM at substantial

187 ient, and widely applicable machine learning interatomic potential (MLIP) trained on 86 diverse exper

188 A machine-learned spin-lattice interatomic potential (MSLP) for magnetic iron is develo

189 rictly local equivariant deep neural network interatomic potential architecture that simultaneously e

190 n femtosecond timescales have shown that the interatomic potential can be perturbed at sufficiently h

191 molecular dynamic methods to provide precise interatomic potential energy calculations for disordered

192 amics simulations with a deep learning-based interatomic potential energy model, we uncover the micro

193 llowing quantitative characterization of the interatomic potential energy surface of the highly excit

194 The motion of atoms on interatomic potential energy surfaces is fundamental to

195 Here we develop a machine learning interatomic potential for a model ionic system: LiF.

196 We propose a machine-learning interatomic potential for multi-component magnetic mater

197 Traditionally, deriving interatomic potential function relies on extensive prior

198 simulations depends on the precision of the interatomic potential function, which dictates the calcu

199 Limitations stem from the way the interatomic potential is described and the inadequate co

200 Here a machine-learned interatomic potential is utilised to generate an ensembl

201 led mapping of the carrier density-dependent interatomic potential of bismuth approaching a solid-sol

202 Expressing the free energy as a function of interatomic potential parameters is actively sought in m

203 lectron microscopy (TEM) combined with a new interatomic potential simulation(27,28), we show several

204 , we show through training a machine-learned interatomic potential that the Au nanospheres exhibit a

205 demonstrate how a machine-learning reactive interatomic potential trained on PaiNN architecture can

206 The employed interatomic potential was developed according to the emb

207 Utilizing a preliminary interatomic potential, this work represents an initial e

208 theory (DFT) data, in conjunction with an ML interatomic potential, we identify a-CO(x) structures co

209 ulations with a high-fidelity neural network interatomic potential, which also yield thermal boundary

210 ts the strength of the repulsive part of the interatomic potential, which can be determined from the

211 Here, we present a fast interatomic potential, which reproduces the molecular hy

212 based on a highly-accurate machine-learning interatomic potential.

213 ry based calculations and a machine learning interatomic potential.

214 ictions based on an accurately parameterized interatomic potential.

215 with our recently developed machine learning interatomic potential.

216 ideration of the finite-strain energy or the interatomic potential.

217 Machine learning interatomic potentials (MLIPs) have become a workhorse o

218 Machine learning interatomic potentials (MLIPs) have become an efficient

219 In this study, we utilize machine-learning interatomic potentials (MLIPs) integrated with an active

220 However, standard machine learning interatomic potentials (MLIPs) often rely on short-range

221 Combining these methods with machine-learned interatomic potentials (MLPs) can extend their reach.

222 This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neu

223 Although universal machine-learning interatomic potentials (uMLIPs), also known as atomistic

224 We believe that, by improving (i) existing interatomic potentials and (ii) currently available enha

225 lculations serve to test the validity of two interatomic potentials and to extend the scope of the DF

226 Traditional interatomic potentials are based on physical intuition b

227 However, using highly accurate interatomic potentials based on quantum mechanics (QM) i

228 ggest that simulations using machine-learned interatomic potentials could eventually be employed as i

229 Interatomic potentials derived with Machine Learning alg

230 Most of the current machine learning interatomic potentials do not distinguish between differ

231 ure reliability, we develop machine learning interatomic potentials for both metals, carefully traine

232 variant neural network approach for learning interatomic potentials from ab-initio calculations for m

233 k (NN)-based methods for the construction of interatomic potentials from discrete samples (such as ab

234 earning" electronic-structure data, ML-based interatomic potentials give access to atomistic simulati

235 Recent strides in ML-based interatomic potentials have paved the way for accurate m

236 re the development and wider use of ML-based interatomic potentials in diverse areas of materials res

237 y furthermore explored the impact of various interatomic potentials on the thermal conductivity of th

238 ter simulations of materials heavily rely on interatomic potentials predicting the energy and Newtoni

239 Neural network (NN) interatomic potentials provide fast prediction of potent

240 However, developing machine-learned interatomic potentials requires high-quality training da

241 icular to highly accurate and robust learned interatomic potentials that can be used in condensed-pha

242 ines a new genetic algorithm using empirical interatomic potentials to explore the configurational ph

243 m carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total

244 nsity functional theory with machine-learned interatomic potentials to investigate the autoionization

245 cture prediction with ephemeral data-derived interatomic potentials to sample over 200,000 different

246 significant advancement in machine learning interatomic potentials, allowing efficient exploration o

247 ng selected studies of electronic structure, interatomic potentials, and chemical compound space in c

248 Here, we show how ultra-fast machine-learned interatomic potentials, based on the atomic cluster expa

249 rties: in particular, on the construction of interatomic potentials, or force fields, in the Gaussian

250 accurate and high-efficient machine learning interatomic potentials, we perform multiscale simulation

251 Using atomistic simulations with model interatomic potentials, we reveal a transition in the as

252 s, made possible by machine-learned reactive interatomic potentials.

253 tic calculations leveraging machine learning interatomic potentials.

254 o far been based on the use of semiempirical interatomic potentials.

255 An analysis of its ML-CP-derived interatomic pressures traces the origins of the structur

256 ct that for superdense plasma mixtures, both interatomic radiative transitions and dipole-forbidden t

257 r within a free (noncoordinated) ligand: the interatomic separation between the N-donor metal-binding

258 and iodine fragments as a function of their interatomic separation set by the NIR-x-ray delay.

259 ke excitations with wavelengths extending to interatomic separations deep in the supercritical state

260 By analyzing the wave functions and interatomic separations, we provide a detailed character

261 trogen bond, and the close match between its interatomic spacing and the size of water molecules.

262 essure allows control over the unit cell and interatomic spacing of materials without any need for ne

263 ibrational scattering length on the order of interatomic spacing, and high electrical conductivities

264 spatial wavelengths of the order of several interatomic spacings, rather than the macroscopic scales

265 fingers in two separate in vitro assays, and interatomic surface molecular modeling docked the compou

266 -) and the pyrimidine dimer by the method of interatomic tunneling currents.

267 DNA photolyase molecule, using the method of interatomic tunneling currents.