Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
3526 | 1395 | 31.3 | 50% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Terms with highest relevance score |
rank | Term | termType | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|---|
1 | AFLOW | authKW | 109437 | 0% | 100% | 5 |
2 | POWDER INDEXING | authKW | 109437 | 0% | 100% | 5 |
3 | COMPUTAT DESIGN DISCOVERY NOVEL MAT | address | 97494 | 1% | 64% | 7 |
4 | DERIVATIVE LATTICES | authKW | 87550 | 0% | 100% | 4 |
5 | ORBITAL ELECTRONEGATIVITY | authKW | 70038 | 0% | 80% | 4 |
6 | PSEUDOPOTENTIAL RADIUS | authKW | 70038 | 0% | 80% | 4 |
7 | ENSEMBLES OF FEED FORWARD NEURAL NETWORKS | authKW | 65662 | 0% | 100% | 3 |
8 | INDEXING PROGRAMS | authKW | 65662 | 0% | 100% | 3 |
9 | NSF INT MAT | address | 65662 | 0% | 100% | 3 |
10 | REDUCED CELL | authKW | 65662 | 0% | 100% | 3 |
Web of Science journal categories |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | Crystallography | 2623 | 12% | 0% | 170 |
2 | Physics, Atomic, Molecular & Chemical | 2386 | 17% | 0% | 240 |
3 | Chemistry, Physical | 2235 | 28% | 0% | 395 |
4 | Metallurgy & Metallurgical Engineering | 914 | 9% | 0% | 131 |
5 | Materials Science, Multidisciplinary | 847 | 20% | 0% | 278 |
6 | Physics, Condensed Matter | 517 | 12% | 0% | 168 |
7 | Chemistry, Multidisciplinary | 281 | 12% | 0% | 168 |
8 | Microscopy | 165 | 1% | 0% | 18 |
9 | Materials Science, Characterization, Testing | 147 | 1% | 0% | 20 |
10 | Mining & Mineral Processing | 126 | 1% | 0% | 15 |
Address terms |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | COMPUTAT DESIGN DISCOVERY NOVEL MAT | 97494 | 1% | 64% | 7 |
2 | NSF INT MAT | 65662 | 0% | 100% | 3 |
3 | YULIN BRANCH | 65662 | 0% | 100% | 3 |
4 | COMPUTAT DESIGN DISCOVERY NOVEL MAT MA | 56263 | 1% | 21% | 12 |
5 | MAT GENOM MAT SCI ELECT ENGN PHYS CHEM | 49245 | 0% | 75% | 3 |
6 | ARGONNE LEADERSHIP COMP IL | 45614 | 1% | 15% | 14 |
7 | KHARKOV ENGN PHYS | 43775 | 0% | 100% | 2 |
8 | MAT INFORMAT INTEGRAT | 35007 | 1% | 20% | 8 |
9 | LUBRICANT | 32828 | 0% | 50% | 3 |
10 | COMBINATORIAL MAT SCI MAT INFORMAT | 29182 | 0% | 67% | 2 |
Journals |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | KRISTALLOGRAFIYA | 4731 | 2% | 1% | 29 |
2 | JOURNAL OF RESEARCH OF THE NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY | 4446 | 1% | 1% | 14 |
3 | JOURNAL OF CHEMICAL PHYSICS | 3458 | 9% | 0% | 119 |
4 | ACTA CRYSTALLOGRAPHICA SECTION A | 3449 | 1% | 1% | 19 |
5 | MRS BULLETIN | 2917 | 1% | 1% | 17 |
6 | JOM | 2273 | 1% | 1% | 15 |
7 | COMPUTATIONAL MATERIALS SCIENCE | 2203 | 2% | 0% | 27 |
8 | ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES | 2073 | 1% | 1% | 11 |
9 | INDUSTRIAL LABORATORY | 1684 | 1% | 1% | 10 |
10 | JOURNAL OF APPLIED CRYSTALLOGRAPHY | 1676 | 2% | 0% | 21 |
Author Key Words |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
LCSH search | Wikipedia search |
---|---|---|---|---|---|---|---|
1 | AFLOW | 109437 | 0% | 100% | 5 | Search AFLOW | Search AFLOW |
2 | POWDER INDEXING | 109437 | 0% | 100% | 5 | Search POWDER+INDEXING | Search POWDER+INDEXING |
3 | DERIVATIVE LATTICES | 87550 | 0% | 100% | 4 | Search DERIVATIVE+LATTICES | Search DERIVATIVE+LATTICES |
4 | ORBITAL ELECTRONEGATIVITY | 70038 | 0% | 80% | 4 | Search ORBITAL+ELECTRONEGATIVITY | Search ORBITAL+ELECTRONEGATIVITY |
5 | PSEUDOPOTENTIAL RADIUS | 70038 | 0% | 80% | 4 | Search PSEUDOPOTENTIAL+RADIUS | Search PSEUDOPOTENTIAL+RADIUS |
6 | ENSEMBLES OF FEED FORWARD NEURAL NETWORKS | 65662 | 0% | 100% | 3 | Search ENSEMBLES+OF+FEED+FORWARD+NEURAL+NETWORKS | Search ENSEMBLES+OF+FEED+FORWARD+NEURAL+NETWORKS |
7 | INDEXING PROGRAMS | 65662 | 0% | 100% | 3 | Search INDEXING+PROGRAMS | Search INDEXING+PROGRAMS |
8 | REDUCED CELL | 65662 | 0% | 100% | 3 | Search REDUCED+CELL | Search REDUCED+CELL |
9 | SPACE GROUP REVISION | 65662 | 0% | 100% | 3 | Search SPACE+GROUP+REVISION | Search SPACE+GROUP+REVISION |
10 | MATERIALS INFORMATICS | 61122 | 1% | 31% | 9 | Search MATERIALS+INFORMATICS | Search MATERIALS+INFORMATICS |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
Rank | Reference | # ref. in cl. |
Shr. of ref. in cl. |
Citations |
---|---|---|---|---|
1 | BEHLER, J , (2015) CONSTRUCTING HIGH-DIMENSIONAL NEURAL NETWORK POTENTIALS: A TUTORIAL REVIEW.INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY. VOL. 115. ISSUE 16. P. 1032 -1050 | 50 | 53% | 23 |
2 | BEHLER, J , (2014) REPRESENTING POTENTIAL ENERGY SURFACES BY HIGH-DIMENSIONAL NEURAL NETWORK POTENTIALS.JOURNAL OF PHYSICS-CONDENSED MATTER. VOL. 26. ISSUE 18. P. - | 67 | 35% | 42 |
3 | BEHLER, J , (2011) NEURAL NETWORK POTENTIAL-ENERGY SURFACES IN CHEMISTRY: A TOOL FOR LARGE-SCALE SIMULATIONS.PHYSICAL CHEMISTRY CHEMICAL PHYSICS. VOL. 13. ISSUE 40. P. 17930 -17955 | 58 | 43% | 97 |
4 | BEHLER, J , (2011) ATOM-CENTERED SYMMETRY FUNCTIONS FOR CONSTRUCTING HIGH-DIMENSIONAL NEURAL NETWORK POTENTIALS.JOURNAL OF CHEMICAL PHYSICS. VOL. 134. ISSUE 7. P. - | 34 | 79% | 55 |
5 | HANDLEY, CM , POPELIER, PLA , (2010) POTENTIAL ENERGY SURFACES FITTED BY ARTIFICIAL NEURAL NETWORKS.JOURNAL OF PHYSICAL CHEMISTRY A. VOL. 114. ISSUE 10. P. 3371-3383 | 33 | 79% | 75 |
6 | JAIN, A , HAUTIER, G , ONG, SP , PERSSON, K , (2016) NEW OPPORTUNITIES FOR MATERIALS INFORMATICS: RESOURCES AND DATA MINING TECHNIQUES FOR UNCOVERING HIDDEN RELATIONSHIPS.JOURNAL OF MATERIALS RESEARCH. VOL. 31. ISSUE 8. P. 977 -994 | 44 | 49% | 2 |
7 | GASTEGGER, M , MARQUETAND, P , (2015) HIGH-DIMENSIONAL NEURAL NETWORK POTENTIALS FOR ORGANIC REACTIONS AND AN IMPROVED TRAINING ALGORITHM.JOURNAL OF CHEMICAL THEORY AND COMPUTATION. VOL. 11. ISSUE 5. P. 2187 -2198 | 43 | 52% | 7 |
8 | BEHLER, J , (2016) PERSPECTIVE: MACHINE LEARNING POTENTIALS FOR ATOMISTIC SIMULATIONS.JOURNAL OF CHEMICAL PHYSICS. VOL. 145. ISSUE 17. P. - | 33 | 62% | 2 |
9 | SEKO, A , TAKAHASHI, A , TANAKA, I , (2015) FIRST-PRINCIPLES INTERATOMIC POTENTIALS FOR TEN ELEMENTAL METALS VIA COMPRESSED SENSING.PHYSICAL REVIEW B. VOL. 92. ISSUE 5. P. - | 36 | 64% | 1 |
10 | MALSHE, M , PUKRITTAYAKAMEE, A , RAFF, LM , HAGAN, M , BUKKAPATNAM, S , KOMANDURI, R , (2009) ACCURATE PREDICTION OF HIGHER-LEVEL ELECTRONIC STRUCTURE ENERGIES FOR LARGE DATABASES USING NEURAL NETWORKS, HARTREE-FOCK ENERGIES, AND SMALL SUBSETS OF THE DATABASE.JOURNAL OF CHEMICAL PHYSICS. VOL. 131. ISSUE 12. P. - | 34 | 77% | 5 |
Classes with closest relation at Level 2 |